==> Building on shinx ==> Checking for remote environment... ==> Syncing package to remote host... sending incremental file list created directory packages/python-dask ./ PKGBUILD 2,556 100% 0.00kB/s 0:00:00 2,556 100% 0.00kB/s 0:00:00 (xfr#1, to-chk=1/3) python-dask-2022.12.1-1.log 243 100% 237.30kB/s 0:00:00 243 100% 237.30kB/s 0:00:00 (xfr#2, to-chk=0/3) sent 1,431 bytes received 100 bytes 1,020.67 bytes/sec total size is 2,748 speedup is 1.79 ==> Running extra-riscv64-build -- -d /home/felix/packages/riscv64-pkg-cache:/var/cache/pacman/pkg -l root2 on remote host... [?25l:: Synchronizing package databases... core downloading... extra downloading... community downloading... :: Starting full system upgrade... there is nothing to do [?25h==> Building in chroot for [extra] (riscv64)... ==> Synchronizing chroot copy [/var/lib/archbuild/extra-riscv64/root] -> [root2]...done ==> Making package: python-dask 2022.12.1-1 (Tue Apr 18 08:18:40 2023) ==> Retrieving sources...  -> Downloading python-dask-2022.12.1.tar.gz... % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 8040k 0 8040k 0 0 7299k 0 --:--:-- 0:00:01 --:--:-- 9758k ==> Validating source files with sha256sums... python-dask-2022.12.1.tar.gz ... Passed ==> Making package: python-dask 2022.12.1-1 (Tue Apr 18 08:18:50 2023) ==> Checking runtime dependencies... ==> Installing missing dependencies... [?25lresolving dependencies... looking for conflicting packages... Package (12) New Version Net Change Download Size core/libnsl 2.0.0-3 0.06 MiB extra/libyaml 0.2.5-2 0.15 MiB community/python-locket 1.0.0-1 0.02 MiB extra/mpdecimal 2.5.1-1 1.78 MiB core/python 3.10.10-1 81.41 MiB community/python-click 8.1.3-1 0.89 MiB community/python-cloudpickle 2.2.0-5 0.17 MiB community/python-fsspec 2022.5.0-1 1.24 MiB extra/python-packaging 23.0-1 0.32 MiB community/python-partd 1.3.0-1 0.14 MiB community/python-toolz 0.12.0-2 0.57 MiB 0.11 MiB community/python-yaml 6.0-1 0.68 MiB Total Download Size: 0.11 MiB Total Installed Size: 87.42 MiB :: Proceed with installation? [Y/n] :: Retrieving packages... python-toolz-0.12.0-2-any downloading... checking keyring... checking package integrity... loading package files... checking for file conflicts... :: Processing package changes... installing libnsl... installing python... Optional dependencies for python python-setuptools python-pip sqlite [installed] mpdecimal: for decimal [pending] xz: for lzma [installed] tk: for tkinter installing python-click... installing python-cloudpickle... installing python-fsspec... installing python-packaging... installing python-locket... installing python-toolz... installing python-partd... Optional dependencies for python-partd python-blosc python-numpy python-pandas python-pyzmq installing libyaml... installing python-yaml... installing mpdecimal... [?25h==> Checking buildtime dependencies... ==> Installing missing dependencies... [?25lresolving dependencies... looking for conflicting packages... warning: dependency cycle detected: warning: harfbuzz will be installed before its freetype2 dependency Package (196) New Version Net Change Download Size community/abseil-cpp 20230125.1-2 5.29 MiB extra/aom 3.6.0-1 4.43 MiB community/apache-orc 1.8.1-1 1.26 MiB 0.39 MiB community/arrow 10.0.1-1 33.35 MiB 7.06 MiB extra/avahi 0.8+22+gfd482a7-3 1.70 MiB extra/blas 3.11.0-2 0.20 MiB community/blosc 1.21.3-1 0.06 MiB extra/boost-libs 1.81.0-3 6.59 MiB extra/c-ares 1.19.0-1 0.44 MiB extra/cairo 1.17.8-2 1.33 MiB extra/cblas 3.11.0-2 0.17 MiB community/cython 0.29.34-1 7.53 MiB extra/dav1d 1.1.0-1 0.56 MiB core/dbus 1.14.6-2 0.77 MiB extra/double-conversion 3.2.1-1 0.16 MiB extra/fontconfig 2:2.14.2-1 1.00 MiB extra/freetype2 2.13.0-1 1.53 MiB extra/fribidi 1.0.12-1 0.20 MiB extra/gd 2.3.3-6 0.55 MiB extra/gdk-pixbuf2 2.42.10-2 2.90 MiB community/gflags 2.2.2-4 1.57 MiB extra/ghostscript 10.01.0-1 42.27 MiB extra/giflib 5.2.1-2 0.22 MiB community/google-glog 0.6.0-1 0.23 MiB extra/graphite 1:1.3.14-3 0.17 MiB extra/graphviz 8.0.2-1 10.28 MiB 3.87 MiB community/grpc 1.53.0-1 15.52 MiB 3.88 MiB extra/gsfonts 20200910-3 3.11 MiB extra/gts 0.7.6.121130-2 0.50 MiB extra/harfbuzz 7.1.0-1 3.29 MiB community/hdf5 1.12.2-1 9.57 MiB extra/http-parser 2.9.4-1 0.06 MiB extra/ijs 0.35-5 0.11 MiB extra/jbig2dec 0.19-1 0.12 MiB extra/jemalloc 1:5.3.0-1 5.50 MiB extra/lapack 3.11.0-2 4.26 MiB extra/lcms2 2.15-1 0.58 MiB community/libaec 1.0.6-1 0.09 MiB community/libavif 0.11.1-1 0.29 MiB extra/libcups 1:2.4.2-6 0.74 MiB extra/libdaemon 0.14-5 0.05 MiB extra/libdatrie 0.2.13-2 0.05 MiB extra/libde265 1.0.11-2 0.57 MiB extra/libgit2 1:1.6.4-1 2.28 MiB 0.82 MiB extra/libheif 1.15.2-1 0.70 MiB extra/libice 1.1.1-2 0.33 MiB extra/libidn 1.41-1 0.75 MiB community/libimagequant 4.1.1-1 0.56 MiB extra/libjpeg-turbo 2.1.5.1-1 1.38 MiB community/liblzf 3.6-4 0.04 MiB 0.02 MiB extra/libpaper 2.0.12-1 0.05 MiB 0.02 MiB extra/libpng 1.6.39-1 0.50 MiB extra/libraqm 0.10.1-1 0.18 MiB extra/librsvg 2:2.56.0-1 11.54 MiB extra/libsm 1.2.4-1 0.25 MiB extra/libthai 0.1.29-2 0.64 MiB extra/libtiff 4.5.0-3 6.01 MiB community/libutf8proc 2.8.0-1 0.36 MiB extra/libwebp 1.3.0-2 0.73 MiB extra/libx11 1.8.4-1 9.84 MiB extra/libxau 1.0.11-2 0.02 MiB extra/libxcb 1.15-2 3.60 MiB extra/libxdmcp 1.1.4-2 0.12 MiB extra/libxext 1.3.5-1 0.29 MiB extra/libxft 2.3.7-1 0.11 MiB extra/libxpm 3.5.15-1 0.13 MiB extra/libxrender 0.9.11-1 0.08 MiB extra/libxt 1.3.0-1 1.96 MiB community/libyuv r2322+3aebf69d-1 1.06 MiB core/lzo 2.10-5 0.34 MiB extra/netpbm 10.73.43-1 5.18 MiB extra/openjpeg2 2.5.0-2 13.14 MiB extra/pango 1:1.50.14-1 2.18 MiB extra/pixman 0.42.2-1 0.40 MiB extra/poppler-data 0.4.12-1 12.34 MiB extra/protobuf 21.12-1 7.69 MiB community/python-aiosignal 1.3.1-1 0.02 MiB extra/python-appdirs 1.4.4-7 0.07 MiB community/python-asttokens 2.2.1-1 0.16 MiB community/python-async-timeout 4.0.2-1 0.02 MiB extra/python-attrs 22.2.0-1 0.44 MiB community/python-autocommand 2.2.2-1 0.07 MiB community/python-backcall 0.2.0-7 0.08 MiB community/python-certifi 2022.12.07-1 0.01 MiB extra/python-cffi 1.15.1-1 1.00 MiB extra/python-chardet 5.1.0-1 2.49 MiB community/python-charset-normalizer 3.1.0-1 0.33 MiB 0.07 MiB community/python-contourpy 1.0.6-1 0.47 MiB extra/python-cryptography 40.0.1-1 3.80 MiB community/python-cycler 0.11.0-1 0.04 MiB community/python-dask 2022.6.1-1 11.46 MiB community/python-dateutil 2.8.2-4 0.82 MiB community/python-decorator 5.1.1-2 0.05 MiB community/python-exceptiongroup 1.1.1-1 0.09 MiB community/python-executing 1.2.0-1 0.17 MiB community/python-fastjsonschema 2.16.3-1 0.20 MiB community/python-fonttools 4.39.3-1 14.08 MiB community/python-frozenlist 1.3.3-1 0.10 MiB community/python-greenlet 2.0.2-1 0.74 MiB community/python-heapdict 1.0.1-5 0.01 MiB extra/python-idna 3.4-1 0.67 MiB community/python-inflect 6.0.4-1 0.28 MiB community/python-iniconfig 2.0.0-2 0.03 MiB community/python-jaraco.context 4.3.0-1 0.03 MiB community/python-jaraco.functools 3.6.0-1 0.05 MiB community/python-jaraco.text 3.11.1-1 0.07 MiB community/python-jedi 0.18.2-1 5.60 MiB community/python-jmespath 1.0.1-1 0.16 MiB community/python-joblib 1.2.0-1 2.01 MiB 0.40 MiB community/python-kiwisolver 1.4.4-2 0.11 MiB extra/python-markupsafe 2.1.2-1 0.06 MiB community/python-matplotlib-inline 0.1.6-2 0.04 MiB 0.01 MiB community/python-more-itertools 9.1.1-1 0.50 MiB community/python-msgpack 1.0.4-1 0.22 MiB community/python-multidict 6.0.3-2 0.13 MiB extra/python-ordered-set 4.1.0-1 0.06 MiB community/python-parso 1:0.8.3-1 0.74 MiB community/python-pexpect 4.8.0-6 0.31 MiB community/python-pickleshare 0.7.5-8 0.02 MiB community/python-pillow 9.4.0-2 2.95 MiB extra/python-platformdirs 3.2.0-1 0.14 MiB community/python-pluggy 1.0.0-2 0.10 MiB extra/python-ply 3.11-10 0.31 MiB community/python-pooch 1.7.0-1 0.56 MiB community/python-prompt_toolkit 3.0.38-1 3.55 MiB community/python-ptyprocess 0.7.0-4 0.06 MiB community/python-pure-eval 0.2.2-2 0.07 MiB extra/python-pycparser 2.21-3 1.39 MiB community/python-pydantic 1.10.7-2 5.84 MiB community/python-pygments 2.14.0-2 12.19 MiB extra/python-pyparsing 3.0.9-1 0.96 MiB community/python-pyrsistent 0.19.3-1 0.48 MiB community/python-pytz 2022.7.1-1 0.14 MiB community/python-responses 0.23.1-1 0.51 MiB 0.08 MiB community/python-s3transfer 0.6.0-4 0.72 MiB extra/python-six 1.16.0-6 0.09 MiB community/python-sortedcontainers 2.4.0-3 0.33 MiB community/python-stack-data 0.6.2-1 0.17 MiB community/python-tblib 1.7.0-5 0.09 MiB community/python-threadpoolctl 3.1.0-1 0.12 MiB 0.02 MiB extra/python-tomli 2.0.1-1 0.08 MiB community/python-tornado 6.2.0-2 4.07 MiB community/python-traitlets 5.9.0-1 1.28 MiB extra/python-trove-classifiers 2023.3.9-1 0.11 MiB community/python-typing_extensions 4.5.0-1 0.23 MiB extra/python-urllib3 1.26.7-5 0.69 MiB extra/python-validate-pyproject 0.12.2-1 0.22 MiB community/python-wcwidth 0.2.5-6 0.47 MiB community/python-werkzeug 2.2.3-1 2.06 MiB community/python-xmltodict 0.13.0-2 0.04 MiB community/python-yarl 1.8.2-1 0.21 MiB community/python-zict 2.0.0-5 0.08 MiB extra/qhull 2020.2-4 8.11 MiB community/rapidjson 1.1.0-5 0.62 MiB extra/rav1e 0.6.3-1 4.33 MiB extra/re2 1:20230301-1 0.32 MiB extra/shared-mime-info 2.2+13+ga2ffb28-1 4.51 MiB extra/snappy 1.1.9-2 0.07 MiB extra/svt-av1 1.4.1-1 3.34 MiB community/thrift 0.18.1-1 5.24 MiB 1.79 MiB community/uriparser 0.9.7-1 0.16 MiB extra/x265 3.5-3 3.62 MiB extra/xcb-proto 1.15.2-2 0.88 MiB extra/xorgproto 2022.2-1 1.43 MiB community/xsimd 11.0.0-1 1.06 MiB 0.10 MiB community/xxhash 0.8.1-4 0.36 MiB community/ipython 8.9.0-1 6.17 MiB community/python-aiohttp 3.8.3-2 2.05 MiB community/python-boto3 1.26.89-1 1.34 MiB community/python-botocore 1.29.89-1 79.90 MiB community/python-cytoolz 0.12.1-1 0.82 MiB 0.24 MiB community/python-distributed 2022.6.1-1 5.82 MiB community/python-graphviz 0.20.1-2 0.34 MiB 0.06 MiB community/python-h5py 3.8.0-1 4.40 MiB community/python-httpretty 1.1.4-3 0.21 MiB 0.05 MiB community/python-jinja 1:3.1.2-2 1.28 MiB community/python-jsonschema 4.17.3-1 0.95 MiB community/python-lz4 3.1.10-7 0.18 MiB community/python-matplotlib 3.7.1-3 22.49 MiB community/python-moto 4.1.1-1 28.89 MiB community/python-numexpr 2.8.4-1 0.48 MiB extra/python-numpy 1.24.2-1 30.13 MiB community/python-pandas 1.4.1-1 57.59 MiB community/python-psutil 5.9.4-1 2.10 MiB community/python-pyarrow 8.0.0-1 13.00 MiB 2.90 MiB community/python-pytables 3.7.0-3 14.54 MiB 1.53 MiB community/python-pytest 7.3.0-1 2.83 MiB community/python-pytest-rerunfailures 11.1.2-1 0.08 MiB 0.02 MiB extra/python-requests 2.28.2-1 0.46 MiB community/python-scikit-learn 1.2.2-1 36.84 MiB 6.71 MiB community/python-scipy 1.10.1-1 75.03 MiB extra/python-setuptools 1:67.6.1-1 3.34 MiB community/python-snappy 0.6.1-2 0.10 MiB 0.03 MiB community/python-sqlalchemy 1.4.44-1 16.09 MiB community/python-xarray 2023.01.0-1 6.84 MiB 0.76 MiB community/python-xxhash 3.2.0-1 0.05 MiB 0.02 MiB Total Download Size: 30.83 MiB Total Installed Size: 790.51 MiB :: Proceed with installation? [Y/n] :: Retrieving packages... arrow-10.0.1-1-riscv64 downloading... python-scikit-learn-1.2.2-1-riscv64 downloading... grpc-1.53.0-1-riscv64 downloading... graphviz-8.0.2-1-riscv64 downloading... python-pyarrow-8.0.0-1-riscv64 downloading... thrift-0.18.1-1-riscv64 downloading... python-pytables-3.7.0-3-riscv64 downloading... libgit2-1:1.6.4-1-riscv64 downloading... python-xarray-2023.01.0-1-any downloading... python-joblib-1.2.0-1-any downloading... apache-orc-1.8.1-1-riscv64 downloading... python-cytoolz-0.12.1-1-riscv64 downloading... xsimd-11.0.0-1-any downloading... python-responses-0.23.1-1-any downloading... python-charset-normalizer-3.1.0-1-any downloading... python-graphviz-0.20.1-2-any downloading... python-httpretty-1.1.4-3-any downloading... python-snappy-0.6.1-2-riscv64 downloading... python-threadpoolctl-3.1.0-1-any downloading... libpaper-2.0.12-1-riscv64 downloading... python-pytest-rerunfailures-11.1.2-1-any downloading... liblzf-3.6-4-riscv64 downloading... python-xxhash-3.2.0-1-riscv64 downloading... python-matplotlib-inline-0.1.6-2-any downloading... checking keyring... checking package integrity... loading package files... checking for file conflicts... :: Processing package changes... installing python-more-itertools... installing python-jaraco.functools... installing python-jaraco.context... installing python-autocommand... installing python-typing_extensions... installing python-pydantic... Optional dependencies for python-pydantic python-dotenv: for .env file support python-email-validator: for email validation installing python-inflect... installing python-jaraco.text... installing python-ordered-set... installing python-platformdirs... installing python-tomli... installing python-fastjsonschema... installing python-trove-classifiers... installing python-validate-pyproject... installing python-setuptools... installing python-decorator... installing python-traitlets... installing python-ptyprocess... installing python-pexpect... installing python-pickleshare... installing python-pygments... installing python-wcwidth... installing python-prompt_toolkit... installing python-parso... installing python-jedi... installing python-backcall... installing python-matplotlib-inline... Optional dependencies for python-matplotlib-inline python-matplotlib [pending] installing python-six... installing python-asttokens... installing python-executing... installing python-pure-eval... installing python-stack-data... installing ipython... Optional dependencies for ipython python-black: to auto format with Black yapf: to auto format with YAPF installing python-exceptiongroup... installing python-iniconfig... installing python-pluggy... installing python-pytest... installing python-pytest-rerunfailures... Optional dependencies for python-pytest-rerunfailures python-pytest-xdist: for recovering from crashes installing python-chardet... installing python-multidict... installing python-async-timeout... installing python-idna... installing python-yarl... installing python-attrs... installing python-charset-normalizer... installing python-frozenlist... installing python-aiosignal... installing python-aiohttp... Optional dependencies for python-aiohttp gunicorn: to deploy using Gunicorn python-aiodns: for fast DNS resolving python-cchardet: for faster encoding detection python-brotli: for Brotli transfer-encodings support installing python-certifi... installing python-dateutil... installing python-jmespath... installing python-urllib3... Optional dependencies for python-urllib3 python-pysocks: SOCKS support python-brotli: Brotli support python-pyopenssl: security support python-idna: security support [installed] installing python-botocore... Optional dependencies for python-botocore python-awscrt installing python-s3transfer... Optional dependencies for python-s3transfer python-awscrt installing python-boto3... installing cython... installing python-cytoolz... installing python-dask... Optional dependencies for python-dask python-distributed: distributed computing [pending] python-numpy: arrays and dataframes support [pending] python-pandas: dataframes support [pending] python-psutil: more accurate CPU count [pending] python-pyarrow: Apache Arrow, for parquet support [pending] python-sqlalchemy: writing and reading from SQL databases [pending] python-xxhash: faster hashing of arrays [pending] installing python-markupsafe... installing python-jinja... Optional dependencies for python-jinja python-babel: for i18n support installing python-msgpack... installing python-psutil... installing python-sortedcontainers... installing python-tblib... installing python-tornado... Optional dependencies for python-tornado python-pycurl: for tornado.curl_httpclient python-twisted: for tornado.platform.twisted installing python-heapdict... installing python-zict... installing python-distributed... installing graphite... Optional dependencies for graphite graphite-docs: Documentation installing harfbuzz... Optional dependencies for harfbuzz harfbuzz-utils: utilities installing libpng... installing freetype2... installing fontconfig... Creating fontconfig configuration... Rebuilding fontconfig cache... installing xorgproto... installing libice... installing libsm... installing xcb-proto... installing libxdmcp... installing libxau... installing libxcb... installing libx11... installing libxt... installing libxext... installing libxpm... installing libjpeg-turbo... Optional dependencies for libjpeg-turbo java-runtime>11: for TurboJPEG Java wrapper installing libtiff... Optional dependencies for libtiff freeglut: for using tiffgt installing giflib... installing libwebp... installing aom... installing dav1d... Optional dependencies for dav1d dav1d-doc: HTML documentation installing http-parser... installing libgit2... installing rav1e... installing svt-av1... installing libyuv... installing libavif... installing libde265... Optional dependencies for libde265 ffmpeg: for sherlock265 qt5-base: for sherlock265 sdl: dec265 YUV overlay output installing x265... installing libheif... Optional dependencies for libheif libjpeg: for heif-convert and heif-enc [installed] libpng: for heif-convert and heif-enc [installed] installing gd... Optional dependencies for gd perl: bdftogd script [installed] installing libxrender... installing lzo... installing pixman... installing cairo... installing shared-mime-info... installing gdk-pixbuf2... Optional dependencies for gdk-pixbuf2 libwmf: Load .wmf and .apm libopenraw: Load .dng, .cr2, .crw, .nef, .orf, .pef, .arw, .erf, .mrw, and .raf libavif: Load .avif [installed] libheif: Load .heif, .heic, and .avif [installed] libjxl: Load .jxl librsvg: Load .svg, .svgz, and .svg.gz [pending] webp-pixbuf-loader: Load .webp installing fribidi... installing libdatrie... installing libthai... installing libxft... installing pango... installing librsvg... installing libdaemon... installing dbus... installing avahi... Optional dependencies for avahi gtk3: avahi-discover, avahi-discover-standalone, bshell, bssh, bvnc qt5-base: qt5 bindings libevent: libevent bindings [installed] nss-mdns: NSS support for mDNS python-twisted: avahi-bookmarks python-gobject: avahi-bookmarks, avahi-discover python-dbus: avahi-bookmarks, avahi-discover installing libcups... installing jbig2dec... installing lcms2... installing libpaper... installing ijs... installing openjpeg2... installing libidn... installing poppler-data... installing ghostscript... Optional dependencies for ghostscript texlive-core: needed for dvipdf gtk3: needed for gsx installing netpbm... installing gts... installing gsfonts... installing graphviz... Warning: Could not load "/usr/lib/graphviz/libgvplugin_gdk.so.6" - It was found, so perhaps one of its dependents was not. Try ldd. Warning: Could not load "/usr/lib/graphviz/libgvplugin_gtk.so.6" - It was found, so perhaps one of its dependents was not. Try ldd. Warning: Could not load "/usr/lib/graphviz/libgvplugin_gdk.so.6" - It was found, so perhaps one of its dependents was not. Try ldd. Warning: Could not load "/usr/lib/graphviz/libgvplugin_gtk.so.6" - It was found, so perhaps one of its dependents was not. Try ldd. Optional dependencies for graphviz mono: sharp bindings guile: guile bindings [installed] lua: lua bindings ocaml: ocaml bindings perl: perl bindings [installed] python: python bindings [installed] r: r bindings tcl: tcl bindings qt5-base: gvedit gtk2: gtk output plugin xterm: vimdot installing python-graphviz... installing libaec... installing hdf5... installing liblzf... installing blas... installing cblas... installing lapack... installing python-numpy... Optional dependencies for python-numpy openblas: faster linear algebra installing python-h5py... installing python-httpretty... installing python-pyrsistent... installing python-jsonschema... Optional dependencies for python-jsonschema python-isoduration: for duration format python-fqdn: for hostname format python-idna: for idn-hostname format [installed] python-jsonpointer: for json-pointer & relative-json-pointer format python-rfc3339-validator: for date-time format python-rfc3987: for iri, iri-reference, uri & uri-reference format python-uri-template: for uri-template format python-webcolors: for color format installing python-lz4... installing python-contourpy... Optional dependencies for python-contourpy python-matplotlib: matplotlib renderer [pending] installing python-cycler... installing python-fonttools... Optional dependencies for python-fonttools python-brotli: to compress/decompress WOFF 2.0 web fonts python-fs: to read/write UFO source files python-lxml: faster backend for XML files reading/writing python-lz4: for graphite type tables in ttLib/tables [installed] python-matplotlib: for visualizing DesignSpaceDocument and resulting VariationModel [pending] python-pyqt5: for drawing glyphs with Qt’s QPainterPath python-reportlab: to drawing glyphs as PNG images python-scipy: for finding wrong contour/component order between different masters [pending] python-sympy: for symbolic font statistics analysis python-uharfbuzz: to use the Harfbuzz Repacker for packing GSUB/GPOS tables python-unicodedata2: for displaying the Unicode character names when dumping the cmap table with ttx python-zopfli: faster backend fom WOFF 1.0 web fonts compression installing python-kiwisolver... installing libraqm... installing libimagequant... installing python-pillow... Optional dependencies for python-pillow libwebp: for webp images [installed] tk: for the ImageTK module python-olefile: OLE2 file support python-pyqt5: for the ImageQt module installing python-pyparsing... Optional dependencies for python-pyparsing python-railroad-diagrams: for generating Railroad Diagrams python-jinja: for generating Railroad Diagrams [installed] installing qhull... installing python-matplotlib... Optional dependencies for python-matplotlib tk: Tk{Agg,Cairo} backends pyside2: alternative for Qt5{Agg,Cairo} backends pyside6: alternative for Qt6{Agg,Cairo} backends python-pyqt5: Qt5{Agg,Cairo} backends python-pyqt6: Qt6{Agg,Cairo} backends python-gobject: for GTK{3,4}{Agg,Cairo} backend python-wxpython: WX{Agg,Cairo} backend python-cairo: {GTK{3,4},Qt{5,6},Tk,WX}Cairo backends python-cairocffi: alternative for Cairo backends python-tornado: WebAgg backend [installed] ffmpeg: for saving movies imagemagick: for saving animated gifs ghostscript: usetex dependencies [installed] texlive-bin: usetex dependencies texlive-latexextra: usetex usage with pdflatex python-certifi: https support [installed] installing python-ply... installing python-pycparser... installing python-cffi... installing python-cryptography... installing python-requests... Optional dependencies for python-requests python-pysocks: SOCKS proxy support installing python-xmltodict... installing python-werkzeug... installing python-responses... installing python-moto... Optional dependencies for python-moto python-yaml: for apigatewayv2, cloudformation, s3 and ssm [installed] python-jose: for apigateway, cloudformation and cognitoidp python-openapi-spec-validator: for apigateway and cloudformation python-docker: for awslambda, batch, cloudformation, dynamodb2 and dynamodbstreams python-graphql-core: For appsync and cloudformation python-jsondiff: for iotdata and cloudformation python-aws-xray-sdk: for xray and cloudformation python-cfn-lint: for cloudformation python-sshpubkeys: for ec2, ebs, efs, directoryservice and cloudformation python-pyparsing: for glue and cloudformation [installed] python-flask: for moto_server python-flask-cors: for moto_server installing python-numexpr... installing python-pytz... installing python-pandas... Optional dependencies for python-pandas python-pandas-datareader: pandas.io.data replacement (recommended) python-numexpr: needed for accelerating certain numerical operations (recommended) [installed] python-bottleneck: needed for accelerating certain types of nan evaluations (recommended) python-beautifulsoup4: needed for read_html function python-jinja: needed for conditional HTML formatting [installed] python-pyqt5: needed for read_clipboard function (only one needed) python-pytables: needed for HDF5-based storage [pending] python-sqlalchemy: needed for SQL database support [pending] python-scipy: needed for miscellaneous statistical functions [pending] python-xlsxwriter: alternative Excel XLSX output python-blosc: for msgpack compression using blosc python-html5lib: needed for read_hmlt function (and/or python-lxml) python-lxml: needed for read_html function (and/or python-html5lib) python-matplotlib: needed for plotting [installed] python-openpyxl: needed for Excel XLSX input/output python-psycopg2: needed for PostgreSQL engine for sqlalchemy python-pymysql: needed for MySQL engine for sqlalchemy python-qtpy: needed for read_clipboard function (only one needed) python-tabulate: needed for printing in Markdown-friendly format python-fsspec: needed for handling files aside from local and HTTP [installed] xclip: needed for read_clipboard function (only one needed) python-xlrd: needed for Excel XLS input python-xlwt: needed for Excel XLS output xsel: needed for read_clipboard function (only one needed) zlib: needed for compression for msgpack [installed] installing protobuf... installing snappy... installing apache-orc... installing boost-libs... Optional dependencies for boost-libs openmpi: for mpi support installing double-conversion... installing c-ares... installing gflags... installing re2... installing abseil-cpp... installing grpc... installing google-glog... installing jemalloc... Optional dependencies for jemalloc perl: for jeprof [installed] installing libutf8proc... installing rapidjson... installing thrift... Optional dependencies for thrift qt5-base: TQTcpServer (Qt5) support installing uriparser... installing xsimd... installing arrow... installing python-pyarrow... Optional dependencies for python-pyarrow python-fsspec [installed] installing blosc... installing python-pytables... installing python-joblib... Optional dependencies for python-joblib python-numpy: for array manipulation [installed] python-lz4: for compressed serialization [installed] installing python-appdirs... installing python-pooch... installing python-scipy... Optional dependencies for python-scipy python-pillow: for image saving module [installed] installing python-threadpoolctl... installing python-scikit-learn... Optional dependencies for python-scikit-learn python-matplotlib: plotting capabilities [installed] installing python-snappy... installing python-greenlet... installing python-sqlalchemy... Optional dependencies for python-sqlalchemy python-psycopg2: connect to PostgreSQL database installing python-xarray... Optional dependencies for python-xarray python-netcdf4: netCDF4 support python-scipy: interpolation features & fallback for netCDF3 support [installed] python-cftime: datetimes support for non-standard calendars or distant dates python-bottleneck: faster NaN-skipping and rolling window aggregations python-dask: parallel computation [installed] python-distributed: parallel computation [installed] python-matplotlib: plotting support [installed] python-seaborn: better color palettes for plots python-pint: units of measure support installing xxhash... installing python-xxhash... :: Running post-transaction hooks... (1/7) Updating the MIME type database... (2/7) Updating fontconfig configuration... (3/7) Reloading system bus configuration... call to execv failed (No such file or directory) error: command failed to execute correctly (4/7) Warn about old perl modules (5/7) Updating fontconfig cache... (6/7) Probing GDK-Pixbuf loader modules... (7/7) Updating the info directory file... [?25h==> Retrieving sources...  -> Found python-dask-2022.12.1.tar.gz ==> WARNING: Skipping all source file integrity checks. ==> Extracting sources...  -> Extracting python-dask-2022.12.1.tar.gz with bsdtar ==> Starting build()... running build running build_py creating build creating build/lib creating build/lib/dask copying dask/__init__.py -> build/lib/dask copying dask/__main__.py -> build/lib/dask copying dask/_version.py -> build/lib/dask copying dask/backends.py -> build/lib/dask copying dask/base.py -> build/lib/dask copying dask/blockwise.py -> build/lib/dask copying dask/cache.py -> build/lib/dask copying dask/callbacks.py -> build/lib/dask copying dask/cli.py -> build/lib/dask copying dask/compatibility.py -> build/lib/dask copying dask/config.py -> build/lib/dask copying dask/context.py -> build/lib/dask copying dask/core.py -> build/lib/dask copying dask/datasets.py -> build/lib/dask copying dask/delayed.py -> build/lib/dask copying dask/distributed.py -> build/lib/dask copying dask/dot.py -> build/lib/dask copying dask/graph_manipulation.py -> build/lib/dask copying dask/hashing.py -> build/lib/dask copying dask/highlevelgraph.py -> build/lib/dask copying dask/layers.py -> build/lib/dask copying dask/local.py -> build/lib/dask copying dask/ml.py -> build/lib/dask copying dask/multiprocessing.py -> build/lib/dask copying dask/optimization.py -> build/lib/dask copying dask/order.py -> build/lib/dask copying dask/rewrite.py -> build/lib/dask copying dask/sizeof.py -> build/lib/dask copying dask/system.py -> build/lib/dask copying dask/threaded.py -> build/lib/dask copying dask/typing.py -> build/lib/dask copying dask/utils.py -> build/lib/dask copying dask/utils_test.py -> build/lib/dask creating build/lib/dask/array copying dask/array/__init__.py -> build/lib/dask/array copying dask/array/backends.py -> build/lib/dask/array copying dask/array/blockwise.py -> build/lib/dask/array copying dask/array/chunk.py -> build/lib/dask/array copying dask/array/chunk_types.py -> build/lib/dask/array copying dask/array/core.py -> build/lib/dask/array copying dask/array/creation.py -> build/lib/dask/array copying dask/array/cupy_entry_point.py -> build/lib/dask/array copying dask/array/dispatch.py -> build/lib/dask/array copying dask/array/einsumfuncs.py -> build/lib/dask/array copying dask/array/fft.py -> build/lib/dask/array copying dask/array/gufunc.py -> build/lib/dask/array copying dask/array/image.py -> build/lib/dask/array copying dask/array/linalg.py -> build/lib/dask/array copying dask/array/ma.py -> build/lib/dask/array copying dask/array/numpy_compat.py -> build/lib/dask/array copying dask/array/optimization.py -> build/lib/dask/array copying dask/array/overlap.py -> build/lib/dask/array copying dask/array/percentile.py -> build/lib/dask/array copying dask/array/random.py -> build/lib/dask/array copying dask/array/rechunk.py -> build/lib/dask/array copying dask/array/reductions.py -> build/lib/dask/array copying dask/array/reshape.py -> build/lib/dask/array copying dask/array/routines.py -> build/lib/dask/array copying dask/array/slicing.py -> build/lib/dask/array copying dask/array/stats.py -> build/lib/dask/array copying dask/array/svg.py -> build/lib/dask/array copying dask/array/tiledb_io.py -> build/lib/dask/array copying dask/array/ufunc.py -> build/lib/dask/array copying dask/array/utils.py -> build/lib/dask/array copying dask/array/wrap.py -> build/lib/dask/array creating build/lib/dask/bag copying dask/bag/__init__.py -> build/lib/dask/bag copying dask/bag/avro.py -> build/lib/dask/bag copying dask/bag/chunk.py -> build/lib/dask/bag copying dask/bag/core.py -> build/lib/dask/bag copying dask/bag/random.py -> build/lib/dask/bag copying dask/bag/text.py -> build/lib/dask/bag copying dask/bag/utils.py -> build/lib/dask/bag creating build/lib/dask/bytes copying dask/bytes/__init__.py -> build/lib/dask/bytes copying dask/bytes/core.py -> build/lib/dask/bytes copying dask/bytes/utils.py -> build/lib/dask/bytes creating build/lib/dask/dataframe copying dask/dataframe/__init__.py -> build/lib/dask/dataframe copying dask/dataframe/_compat.py -> build/lib/dask/dataframe copying dask/dataframe/_dtypes.py -> build/lib/dask/dataframe copying dask/dataframe/_pyarrow_compat.py -> build/lib/dask/dataframe copying dask/dataframe/accessor.py -> build/lib/dask/dataframe copying dask/dataframe/backends.py -> build/lib/dask/dataframe copying dask/dataframe/categorical.py -> build/lib/dask/dataframe copying dask/dataframe/core.py -> build/lib/dask/dataframe copying dask/dataframe/dispatch.py -> build/lib/dask/dataframe copying dask/dataframe/extensions.py -> build/lib/dask/dataframe copying dask/dataframe/groupby.py -> build/lib/dask/dataframe copying dask/dataframe/hyperloglog.py -> build/lib/dask/dataframe copying dask/dataframe/indexing.py -> build/lib/dask/dataframe copying dask/dataframe/methods.py -> build/lib/dask/dataframe copying dask/dataframe/multi.py -> build/lib/dask/dataframe copying dask/dataframe/numeric.py -> build/lib/dask/dataframe copying dask/dataframe/optimize.py -> build/lib/dask/dataframe copying dask/dataframe/partitionquantiles.py -> build/lib/dask/dataframe copying dask/dataframe/reshape.py -> build/lib/dask/dataframe copying dask/dataframe/rolling.py -> build/lib/dask/dataframe copying dask/dataframe/shuffle.py -> build/lib/dask/dataframe copying dask/dataframe/utils.py -> build/lib/dask/dataframe creating build/lib/dask/dataframe/io copying dask/dataframe/io/__init__.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/csv.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/demo.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/hdf.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/io.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/json.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/sql.py -> build/lib/dask/dataframe/io copying dask/dataframe/io/utils.py -> build/lib/dask/dataframe/io creating build/lib/dask/dataframe/tseries copying dask/dataframe/tseries/__init__.py -> build/lib/dask/dataframe/tseries copying dask/dataframe/tseries/resample.py -> build/lib/dask/dataframe/tseries creating build/lib/dask/diagnostics copying dask/diagnostics/__init__.py -> build/lib/dask/diagnostics copying dask/diagnostics/profile.py -> build/lib/dask/diagnostics copying dask/diagnostics/profile_visualize.py -> build/lib/dask/diagnostics copying dask/diagnostics/progress.py -> build/lib/dask/diagnostics creating build/lib/dask/tests copying dask/tests/__init__.py -> build/lib/dask/tests copying dask/tests/test_backends.py -> build/lib/dask/tests copying dask/tests/test_base.py -> build/lib/dask/tests copying dask/tests/test_cache.py -> build/lib/dask/tests copying dask/tests/test_callbacks.py -> build/lib/dask/tests copying dask/tests/test_ci.py -> build/lib/dask/tests copying dask/tests/test_cli.py -> build/lib/dask/tests copying dask/tests/test_compatibility.py -> build/lib/dask/tests copying dask/tests/test_config.py -> build/lib/dask/tests copying dask/tests/test_context.py -> build/lib/dask/tests copying dask/tests/test_core.py -> build/lib/dask/tests copying dask/tests/test_datasets.py -> build/lib/dask/tests copying dask/tests/test_delayed.py -> build/lib/dask/tests copying dask/tests/test_distributed.py -> build/lib/dask/tests copying dask/tests/test_docs.py -> build/lib/dask/tests copying dask/tests/test_dot.py -> build/lib/dask/tests copying dask/tests/test_graph_manipulation.py -> build/lib/dask/tests copying dask/tests/test_hashing.py -> build/lib/dask/tests copying dask/tests/test_highgraph.py -> build/lib/dask/tests copying dask/tests/test_layers.py -> build/lib/dask/tests copying dask/tests/test_local.py -> build/lib/dask/tests copying dask/tests/test_ml.py -> build/lib/dask/tests copying dask/tests/test_multiprocessing.py -> build/lib/dask/tests copying dask/tests/test_optimization.py -> build/lib/dask/tests copying dask/tests/test_order.py -> build/lib/dask/tests copying dask/tests/test_rewrite.py -> build/lib/dask/tests copying dask/tests/test_sizeof.py -> build/lib/dask/tests copying dask/tests/test_spark_compat.py -> build/lib/dask/tests copying dask/tests/test_system.py -> build/lib/dask/tests copying dask/tests/test_threaded.py -> build/lib/dask/tests copying dask/tests/test_typing.py -> build/lib/dask/tests copying dask/tests/test_utils.py -> build/lib/dask/tests copying dask/tests/test_utils_test.py -> build/lib/dask/tests creating build/lib/dask/array/tests copying dask/array/tests/__init__.py -> build/lib/dask/array/tests copying dask/array/tests/test_array_core.py -> build/lib/dask/array/tests copying dask/array/tests/test_array_function.py -> build/lib/dask/array/tests copying dask/array/tests/test_array_utils.py -> build/lib/dask/array/tests copying dask/array/tests/test_atop.py -> build/lib/dask/array/tests copying dask/array/tests/test_chunk.py -> build/lib/dask/array/tests copying dask/array/tests/test_creation.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_core.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_creation.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_gufunc.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_linalg.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_overlap.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_percentile.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_random.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_reductions.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_routines.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_slicing.py -> build/lib/dask/array/tests copying dask/array/tests/test_cupy_sparse.py -> build/lib/dask/array/tests copying dask/array/tests/test_dispatch.py -> build/lib/dask/array/tests copying dask/array/tests/test_fft.py -> build/lib/dask/array/tests copying dask/array/tests/test_gufunc.py -> build/lib/dask/array/tests copying dask/array/tests/test_image.py -> build/lib/dask/array/tests copying dask/array/tests/test_linalg.py -> build/lib/dask/array/tests copying dask/array/tests/test_masked.py -> build/lib/dask/array/tests copying dask/array/tests/test_numpy_compat.py -> build/lib/dask/array/tests copying dask/array/tests/test_optimization.py -> build/lib/dask/array/tests copying dask/array/tests/test_overlap.py -> build/lib/dask/array/tests copying dask/array/tests/test_percentiles.py -> build/lib/dask/array/tests copying dask/array/tests/test_random.py -> build/lib/dask/array/tests copying dask/array/tests/test_rechunk.py -> build/lib/dask/array/tests copying dask/array/tests/test_reductions.py -> build/lib/dask/array/tests copying dask/array/tests/test_reshape.py -> build/lib/dask/array/tests copying dask/array/tests/test_routines.py -> build/lib/dask/array/tests copying dask/array/tests/test_slicing.py -> build/lib/dask/array/tests copying dask/array/tests/test_sparse.py -> build/lib/dask/array/tests copying dask/array/tests/test_stats.py -> build/lib/dask/array/tests copying dask/array/tests/test_svg.py -> build/lib/dask/array/tests copying dask/array/tests/test_testing.py -> build/lib/dask/array/tests copying dask/array/tests/test_ufunc.py -> build/lib/dask/array/tests copying dask/array/tests/test_wrap.py -> build/lib/dask/array/tests copying dask/array/tests/test_xarray.py -> build/lib/dask/array/tests creating build/lib/dask/bag/tests copying dask/bag/tests/__init__.py -> build/lib/dask/bag/tests copying dask/bag/tests/test_avro.py -> build/lib/dask/bag/tests copying dask/bag/tests/test_bag.py -> build/lib/dask/bag/tests copying dask/bag/tests/test_random.py -> build/lib/dask/bag/tests copying dask/bag/tests/test_text.py -> build/lib/dask/bag/tests creating build/lib/dask/bytes/tests copying dask/bytes/tests/__init__.py -> build/lib/dask/bytes/tests copying dask/bytes/tests/test_bytes_utils.py -> build/lib/dask/bytes/tests copying dask/bytes/tests/test_compression.py -> build/lib/dask/bytes/tests copying dask/bytes/tests/test_http.py -> build/lib/dask/bytes/tests copying dask/bytes/tests/test_local.py -> build/lib/dask/bytes/tests copying dask/bytes/tests/test_s3.py -> build/lib/dask/bytes/tests creating build/lib/dask/dataframe/tests copying dask/dataframe/tests/__init__.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_accessors.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_arithmetics_reduction.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_boolean.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_categorical.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_dataframe.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_extensions.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_format.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_groupby.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_hashing.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_hyperloglog.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_indexing.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_merge_column_and_index.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_multi.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_numeric.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_optimize_dataframe.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_pyarrow_compat.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_reshape.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_rolling.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_shuffle.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_ufunc.py -> build/lib/dask/dataframe/tests copying dask/dataframe/tests/test_utils_dataframe.py -> build/lib/dask/dataframe/tests creating build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/__init__.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_csv.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_demo.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_hdf.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_io.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_json.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_orc.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_parquet.py -> build/lib/dask/dataframe/io/tests copying dask/dataframe/io/tests/test_sql.py -> build/lib/dask/dataframe/io/tests creating build/lib/dask/dataframe/tseries/tests copying dask/dataframe/tseries/tests/__init__.py -> build/lib/dask/dataframe/tseries/tests copying dask/dataframe/tseries/tests/test_resample.py -> build/lib/dask/dataframe/tseries/tests creating build/lib/dask/diagnostics/tests copying dask/diagnostics/tests/__init__.py -> build/lib/dask/diagnostics/tests copying dask/diagnostics/tests/test_profiler.py -> build/lib/dask/diagnostics/tests copying dask/diagnostics/tests/test_progress.py -> build/lib/dask/diagnostics/tests running egg_info creating dask.egg-info writing dask.egg-info/PKG-INFO writing dependency_links to dask.egg-info/dependency_links.txt writing entry points to dask.egg-info/entry_points.txt writing requirements to dask.egg-info/requires.txt writing top-level names to dask.egg-info/top_level.txt writing manifest file 'dask.egg-info/SOURCES.txt' reading manifest file 'dask.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' adding license file 'LICENSE.txt' adding license file 'dask/array/NUMPY_LICENSE.txt' writing manifest file 'dask.egg-info/SOURCES.txt' /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.array.lib' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.array.lib' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.array.lib' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.array.lib' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.dataframe.io.orc' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.dataframe.io.orc' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.dataframe.io.orc' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.dataframe.io.orc' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.dataframe.io.parquet' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.dataframe.io.parquet' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.dataframe.io.parquet' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.dataframe.io.parquet' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.widgets' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.widgets' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.widgets' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.widgets' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.widgets.templates' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.widgets.templates' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.widgets.templates' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.widgets.templates' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.widgets.tests' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.widgets.tests' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.widgets.tests' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.widgets.tests' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'dask.widgets.tests.templates' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'dask.widgets.tests.templates' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'dask.widgets.tests.templates' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'dask.widgets.tests.templates' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) copying dask/dask-schema.yaml -> build/lib/dask copying dask/dask.yaml -> build/lib/dask copying dask/py.typed -> build/lib/dask creating build/lib/dask/widgets copying dask/widgets/__init__.py -> build/lib/dask/widgets copying dask/widgets/widgets.py -> build/lib/dask/widgets creating build/lib/dask/widgets/templates copying dask/widgets/templates/array.html.j2 -> build/lib/dask/widgets/templates copying dask/widgets/templates/dataframe.html.j2 -> build/lib/dask/widgets/templates copying dask/widgets/templates/highlevelgraph.html.j2 -> build/lib/dask/widgets/templates copying dask/widgets/templates/highlevelgraph_layer.html.j2 -> build/lib/dask/widgets/templates creating build/lib/dask/widgets/tests copying dask/widgets/tests/test_widgets.py -> build/lib/dask/widgets/tests creating build/lib/dask/widgets/tests/templates copying dask/widgets/tests/templates/bytes.html.j2 -> build/lib/dask/widgets/tests/templates copying dask/widgets/tests/templates/custom_filter.html.j2 -> build/lib/dask/widgets/tests/templates copying dask/widgets/tests/templates/example.html.j2 -> build/lib/dask/widgets/tests/templates copying dask/array/NUMPY_LICENSE.txt -> build/lib/dask/array creating build/lib/dask/array/lib copying dask/array/lib/__init__.py -> build/lib/dask/array/lib copying dask/array/lib/stride_tricks.py -> build/lib/dask/array/lib creating build/lib/dask/dataframe/io/orc copying dask/dataframe/io/orc/__init__.py -> build/lib/dask/dataframe/io/orc copying dask/dataframe/io/orc/arrow.py -> build/lib/dask/dataframe/io/orc copying dask/dataframe/io/orc/core.py -> build/lib/dask/dataframe/io/orc copying dask/dataframe/io/orc/utils.py -> build/lib/dask/dataframe/io/orc creating build/lib/dask/dataframe/io/parquet copying dask/dataframe/io/parquet/__init__.py -> build/lib/dask/dataframe/io/parquet copying dask/dataframe/io/parquet/arrow.py -> build/lib/dask/dataframe/io/parquet copying dask/dataframe/io/parquet/core.py -> build/lib/dask/dataframe/io/parquet copying dask/dataframe/io/parquet/fastparquet.py -> build/lib/dask/dataframe/io/parquet copying dask/dataframe/io/parquet/utils.py -> build/lib/dask/dataframe/io/parquet UPDATING build/lib/dask/_version.py set build/lib/dask/_version.py to '2022.12.1' ==> Starting check()... ============================= test session starts ============================== platform linux -- Python 3.10.10, pytest-7.3.0, pluggy-1.0.0 -- /usr/bin/python cachedir: .pytest_cache rootdir: /build/python-dask/src/dask-2022.12.1 configfile: setup.cfg plugins: rerunfailures-11.1.2 collecting ... collected 10355 items / 21 skipped dask/tests/test_backends.py::test_CreationDispatch_error_informative_message[pandas] PASSED [ 0%] dask/tests/test_backends.py::test_CreationDispatch_error_informative_message[cudf] SKIPPED (could not import 'cudf': No module named 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dask/tests/test_config.py::test_schema_is_complete PASSED [ 1%] dask/tests/test_config.py::test_deprecations PASSED [ 1%] dask/tests/test_config.py::test_get_override_with PASSED [ 1%] dask/tests/test_config.py::test_config_serialization PASSED [ 1%] dask/tests/test_config.py::test_config_inheritance PASSED [ 1%] dask/tests/test_config.py::test__get_paths PASSED [ 1%] dask/tests/test_config.py::test_default_search_paths PASSED [ 1%] dask/tests/test_context.py::test_with_get PASSED [ 1%] dask/tests/test_context.py::test_globalmethod PASSED [ 1%] dask/tests/test_core.py::test_istask PASSED [ 1%] dask/tests/test_core.py::test_has_tasks PASSED [ 1%] dask/tests/test_core.py::test_preorder_traversal PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_badkey <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_nested_badkey <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_data_not_in_dict_is_ok <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get_with_list <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get_with_list_top_level <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get_with_nested_list <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get_works_with_unhashables_in_values <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_nested_tasks <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_get_stack_limit <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::TestGet::test_with_HighLevelGraph <- dask/utils_test.py PASSED [ 1%] dask/tests/test_core.py::test_GetFunctionTestMixin_class PASSED [ 1%] dask/tests/test_core.py::test_get_dependencies_nested PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_empty PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_list PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_task PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_nothing PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_many PASSED [ 2%] dask/tests/test_core.py::test_get_dependencies_task_none PASSED [ 2%] dask/tests/test_core.py::test_get_deps PASSED [ 2%] dask/tests/test_core.py::test_flatten PASSED [ 2%] dask/tests/test_core.py::test_subs PASSED [ 2%] dask/tests/test_core.py::test_subs_no_key_data_eq PASSED [ 2%] dask/tests/test_core.py::test_subs_with_unfriendly_eq PASSED [ 2%] dask/tests/test_core.py::test_subs_with_surprisingly_friendly_eq PASSED [ 2%] dask/tests/test_core.py::test_subs_unexpected_hashable_key PASSED [ 2%] dask/tests/test_core.py::test_quote PASSED [ 2%] dask/tests/test_core.py::test_literal_serializable PASSED [ 2%] dask/tests/test_core.py::test_getcycle PASSED [ 2%] dask/tests/test_datasets.py::test_mimesis SKIPPED (could not import 'mimesis': No module named 'mimesis') [ 2%] dask/tests/test_datasets.py::test_full_dataset SKIPPED (could not import 'mimesis': No module named 'mimesis') [ 2%] dask/tests/test_datasets.py::test_make_dataset_with_processes SKIPPED (could not import 'mimesis': No module named 'mimesis') [ 2%] dask/tests/test_datasets.py::test_no_mimesis PASSED [ 2%] dask/tests/test_datasets.py::test_deterministic SKIPPED (could not import 'mimesis': No module named 'mimesis') [ 2%] dask/tests/test_delayed.py::test_to_task_dask PASSED [ 2%] dask/tests/test_delayed.py::test_delayed PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_namedtuple PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass[ANonFrozenDataClass] PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass[AFrozenDataClass] PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass_with_custom_init PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass_with_eager_custom_init PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_eager_dataclass_with_set_init_false_field PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass_with_set_init_false_field PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_with_dataclass_with_unset_init_false_field PASSED [ 2%] dask/tests/test_delayed.py::test_operators PASSED [ 2%] dask/tests/test_delayed.py::test_methods PASSED [ 2%] dask/tests/test_delayed.py::test_attributes PASSED [ 2%] dask/tests/test_delayed.py::test_method_getattr_call_same_task PASSED [ 2%] dask/tests/test_delayed.py::test_np_dtype_of_delayed PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_visualise_warn PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_errors PASSED [ 2%] dask/tests/test_delayed.py::test_common_subexpressions PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_optimize PASSED [ 2%] dask/tests/test_delayed.py::test_lists PASSED [ 2%] dask/tests/test_delayed.py::test_literates PASSED [ 2%] dask/tests/test_delayed.py::test_literates_keys PASSED [ 2%] dask/tests/test_delayed.py::test_lists_are_concrete PASSED [ 2%] dask/tests/test_delayed.py::test_iterators PASSED [ 2%] dask/tests/test_delayed.py::test_traverse_false PASSED [ 2%] dask/tests/test_delayed.py::test_pure PASSED [ 2%] dask/tests/test_delayed.py::test_pure_global_setting PASSED [ 2%] dask/tests/test_delayed.py::test_nout PASSED [ 2%] dask/tests/test_delayed.py::test_nout_with_tasks[x0] PASSED [ 2%] dask/tests/test_delayed.py::test_nout_with_tasks[x1] PASSED [ 2%] dask/tests/test_delayed.py::test_nout_with_tasks[x2] PASSED [ 2%] dask/tests/test_delayed.py::test_nout_with_tasks[x3] PASSED [ 2%] dask/tests/test_delayed.py::test_nout_with_tasks[x4] PASSED [ 2%] dask/tests/test_delayed.py::test_kwargs PASSED [ 2%] dask/tests/test_delayed.py::test_custom_delayed PASSED [ 2%] dask/tests/test_delayed.py::test_array_delayed PASSED [ 2%] dask/tests/test_delayed.py::test_array_bag_delayed PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_picklable PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_compute_forward_kwargs PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_method_descriptor PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_callable PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_name_on_call PASSED [ 2%] dask/tests/test_delayed.py::test_callable_obj PASSED [ 2%] dask/tests/test_delayed.py::test_name_consistent_across_instances PASSED [ 2%] dask/tests/test_delayed.py::test_sensitive_to_partials PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_name PASSED [ 2%] dask/tests/test_delayed.py::test_finalize_name PASSED [ 2%] dask/tests/test_delayed.py::test_keys_from_array PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_decorator_on_method PASSED [ 2%] dask/tests/test_delayed.py::test_attribute_of_attribute PASSED [ 2%] dask/tests/test_delayed.py::test_check_meta_flag PASSED [ 2%] dask/tests/test_delayed.py::test_pickle[modlevel_eager] PASSED [ 2%] dask/tests/test_delayed.py::test_pickle[modlevel_delayed1] XFAIL (#3369) [ 2%] dask/tests/test_delayed.py::test_pickle[modlevel_delayed2] XFAIL (#3369) [ 2%] dask/tests/test_delayed.py::test_cloudpickle[modlevel_eager] PASSED [ 2%] dask/tests/test_delayed.py::test_cloudpickle[modlevel_delayed1] PASSED [ 2%] dask/tests/test_delayed.py::test_cloudpickle[modlevel_delayed2] PASSED [ 2%] dask/tests/test_delayed.py::test_dask_layers PASSED [ 2%] dask/tests/test_delayed.py::test_annotations_survive_optimization PASSED [ 2%] dask/tests/test_delayed.py::test_delayed_function_attributes_forwarded PASSED [ 2%] dask/tests/test_docs.py::test_development_guidelines_matches_ci PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_checkpoint[False] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_checkpoint[True] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_checkpoint_collections PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_wait_on_one[False] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_wait_on_one[True] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_wait_on_many[False] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_wait_on_many[True] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_wait_on_collections PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_clone[False] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_clone[True] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_blockwise_clone_with_literals[1] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_blockwise_clone_with_literals[literal1] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_blockwise_clone_with_literals[literal2] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_blockwise_clone_with_literals[literal3] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_blockwise_clone_with_literals[literal4] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_bind[False] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_bind[True] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_bind_clone_collections[bind] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_bind_clone_collections[clone] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_split_every[2-299] PASSED [ 2%] dask/tests/test_graph_manipulation.py::test_split_every[3-250] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every[8-215] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every[None-215] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every[8.1-215] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every[1000000000.0-201] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every[False-201] PASSED [ 3%] dask/tests/test_graph_manipulation.py::test_split_every_invalid PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[abc] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x1] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x2] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x3] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x4] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x5] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer[x6] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[abc] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x1] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x2] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x3] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x4] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x5] PASSED [ 3%] dask/tests/test_hashing.py::test_hash_buffer_hex[x6] PASSED [ 3%] dask/tests/test_hashing.py::test_hashers[_hash_xxhash] PASSED [ 3%] dask/tests/test_hashing.py::test_hashers[_hash_sha1] PASSED [ 3%] dask/tests/test_highgraph.py::test_visualize PASSED [ 3%] dask/tests/test_highgraph.py::test_basic PASSED [ 3%] dask/tests/test_highgraph.py::test_keys_values_items_to_dict_methods PASSED [ 3%] dask/tests/test_highgraph.py::test_getitem PASSED [ 3%] dask/tests/test_highgraph.py::test_copy PASSED [ 3%] dask/tests/test_highgraph.py::test_cull PASSED [ 3%] dask/tests/test_highgraph.py::test_cull_layers PASSED [ 3%] dask/tests/test_highgraph.py::test_repr_html_hlg_layers PASSED [ 3%] dask/tests/test_highgraph.py::test_single_annotation[annotation0] PASSED [ 3%] dask/tests/test_highgraph.py::test_single_annotation[annotation1] PASSED [ 3%] dask/tests/test_highgraph.py::test_multiple_annotations PASSED [ 3%] dask/tests/test_highgraph.py::test_annotation_pack_unpack PASSED [ 3%] dask/tests/test_highgraph.py::test_materializedlayer_cull_preserves_annotations PASSED [ 3%] dask/tests/test_highgraph.py::test_blockwise_cull[True] PASSED [ 3%] dask/tests/test_highgraph.py::test_blockwise_cull[False] PASSED [ 3%] dask/tests/test_highgraph.py::test_len_does_not_materialize PASSED [ 3%] dask/tests/test_highgraph.py::test_node_tooltips_exist PASSED [ 3%] dask/tests/test_local.py::test_start_state PASSED [ 3%] dask/tests/test_local.py::test_start_state_looks_at_cache PASSED [ 3%] dask/tests/test_local.py::test_start_state_with_redirects PASSED [ 3%] dask/tests/test_local.py::test_start_state_with_independent_but_runnable_tasks PASSED [ 3%] dask/tests/test_local.py::test_start_state_with_tasks_no_deps PASSED [ 3%] dask/tests/test_local.py::test_finish_task PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_badkey <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_nested_badkey <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_data_not_in_dict_is_ok <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_with_list <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_with_list_top_level <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_with_nested_list <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_works_with_unhashables_in_values <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_nested_tasks <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_stack_limit <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_with_HighLevelGraph <- dask/utils_test.py PASSED [ 3%] dask/tests/test_local.py::TestGetAsync::test_get_sync_num_workers PASSED [ 3%] dask/tests/test_local.py::test_cache_options PASSED [ 3%] dask/tests/test_local.py::test_sort_key PASSED [ 3%] dask/tests/test_local.py::test_callback PASSED [ 3%] dask/tests/test_local.py::test_exceptions_propagate PASSED [ 3%] dask/tests/test_local.py::test_ordering PASSED [ 3%] dask/tests/test_local.py::test_complex_ordering PASSED [ 3%] dask/tests/test_ml.py::test_basic PASSED [ 3%] dask/tests/test_multiprocessing.py::test_pickle_globals PASSED [ 3%] dask/tests/test_multiprocessing.py::test_pickle_locals PASSED [ 3%] dask/tests/test_multiprocessing.py::test_out_of_band_pickling PASSED [ 3%] dask/tests/test_multiprocessing.py::test_errors_propagate PASSED [ 3%] dask/tests/test_multiprocessing.py::test_remote_exception PASSED [ 3%] dask/tests/test_multiprocessing.py::test_lambda_with_cloudpickle PASSED [ 3%] dask/tests/test_multiprocessing.py::test_lambda_results_with_cloudpickle PASSED [ 3%] dask/tests/test_multiprocessing.py::test_unpicklable_args_generate_errors PASSED [ 3%] dask/tests/test_multiprocessing.py::test_reuse_pool[Pool] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_reuse_pool[ProcessPoolExecutor] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_dumps_loads PASSED [ 3%] dask/tests/test_multiprocessing.py::test_fuse_doesnt_clobber_intermediates PASSED [ 3%] dask/tests/test_multiprocessing.py::test_optimize_graph_false PASSED [ 3%] dask/tests/test_multiprocessing.py::test_works_with_highlevel_graph PASSED [ 3%] dask/tests/test_multiprocessing.py::test_random_seeds[numpy] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_random_seeds[random] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_process_initializer[threading-None-expected_results0] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_process_initializer[processes-None-expected_results1] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_process_initializer[processes-proc_init-expected_results2] PASSED [ 3%] dask/tests/test_multiprocessing.py::test_custom_context_used_python3_posix PASSED [ 3%] dask/tests/test_multiprocessing.py::test_get_context_using_python3_posix PASSED [ 3%] dask/tests/test_multiprocessing.py::test_custom_context_ignored_elsewhere SKIPPED (POSIX supports different contexts) [ 3%] dask/tests/test_multiprocessing.py::test_get_context_always_default SKIPPED (POSIX supports different contexts) [ 3%] dask/tests/test_optimization.py::test_cull PASSED [ 3%] dask/tests/test_optimization.py::test_fuse PASSED [ 3%] dask/tests/test_optimization.py::test_fuse_keys PASSED [ 3%] dask/tests/test_optimization.py::test_inline PASSED [ 3%] dask/tests/test_optimization.py::test_inline_functions PASSED [ 3%] dask/tests/test_optimization.py::test_inline_ignores_curries_and_partials PASSED [ 3%] dask/tests/test_optimization.py::test_inline_functions_non_hashable PASSED [ 3%] dask/tests/test_optimization.py::test_inline_doesnt_shrink_fast_functions_at_top PASSED [ 3%] dask/tests/test_optimization.py::test_inline_traverses_lists PASSED [ 3%] dask/tests/test_optimization.py::test_inline_functions_protects_output_keys PASSED [ 3%] dask/tests/test_optimization.py::test_functions_of PASSED [ 3%] dask/tests/test_optimization.py::test_inline_cull_dependencies PASSED [ 3%] dask/tests/test_optimization.py::test_fuse_reductions_single_input PASSED [ 3%] dask/tests/test_optimization.py::test_fuse_stressed PASSED [ 3%] dask/tests/test_optimization.py::test_fuse_reductions_multiple_input PASSED [ 3%] dask/tests/test_optimization.py::test_SubgraphCallable PASSED [ 3%] dask/tests/test_optimization.py::test_SubgraphCallable_with_numpy PASSED [ 4%] dask/tests/test_optimization.py::test_SubgraphCallable_eq PASSED [ 4%] dask/tests/test_optimization.py::test_fuse_subgraphs PASSED [ 4%] dask/tests/test_optimization.py::test_fuse_subgraphs_linear_chains_of_duplicate_deps PASSED [ 4%] dask/tests/test_optimization.py::test_dont_fuse_numpy_arrays PASSED [ 4%] dask/tests/test_optimization.py::test_fuse_config PASSED [ 4%] dask/tests/test_optimization.py::test_fused_keys_max_length PASSED [ 4%] dask/tests/test_order.py::test_ordering_keeps_groups_together[abcde] PASSED [ 4%] dask/tests/test_order.py::test_ordering_keeps_groups_together[edcba] PASSED [ 4%] dask/tests/test_order.py::test_avoid_broker_nodes[abcde] PASSED [ 4%] dask/tests/test_order.py::test_avoid_broker_nodes[edcba] PASSED [ 4%] dask/tests/test_order.py::test_base_of_reduce_preferred[abcde] PASSED [ 4%] dask/tests/test_order.py::test_base_of_reduce_preferred[edcba] PASSED [ 4%] dask/tests/test_order.py::test_avoid_upwards_branching[abcde] XFAIL (Can't please 'em all) [ 4%] dask/tests/test_order.py::test_avoid_upwards_branching[edcba] XFAIL (Can't please 'em all) [ 4%] dask/tests/test_order.py::test_avoid_upwards_branching_complex[abcde] PASSED [ 4%] dask/tests/test_order.py::test_avoid_upwards_branching_complex[edcba] PASSED [ 4%] dask/tests/test_order.py::test_deep_bases_win_over_dependents[abcde] PASSED [ 4%] dask/tests/test_order.py::test_deep_bases_win_over_dependents[edcba] PASSED [ 4%] dask/tests/test_order.py::test_prefer_deep[abcde] PASSED [ 4%] dask/tests/test_order.py::test_prefer_deep[edcba] PASSED [ 4%] dask/tests/test_order.py::test_stacklimit[abcde] PASSED [ 4%] dask/tests/test_order.py::test_stacklimit[edcba] PASSED [ 4%] dask/tests/test_order.py::test_break_ties_by_str[abcde] PASSED [ 4%] dask/tests/test_order.py::test_break_ties_by_str[edcba] PASSED [ 4%] dask/tests/test_order.py::test_order_doesnt_fail_on_mixed_type_keys[abcde] PASSED [ 4%] dask/tests/test_order.py::test_order_doesnt_fail_on_mixed_type_keys[edcba] PASSED [ 4%] dask/tests/test_order.py::test_gh_3055 PASSED [ 4%] dask/tests/test_order.py::test_type_comparisions_ok[abcde] PASSED [ 4%] dask/tests/test_order.py::test_type_comparisions_ok[edcba] PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_dependents[abcde] PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_dependents[edcba] PASSED [ 4%] dask/tests/test_order.py::test_run_smaller_sections[abcde] XFAIL (This is challenging to do precisely) [ 4%] dask/tests/test_order.py::test_run_smaller_sections[edcba] XFAIL (This is challenging to do precisely) [ 4%] dask/tests/test_order.py::test_local_parents_of_reduction[abcde] PASSED [ 4%] dask/tests/test_order.py::test_local_parents_of_reduction[edcba] PASSED [ 4%] dask/tests/test_order.py::test_nearest_neighbor[abcde] PASSED [ 4%] dask/tests/test_order.py::test_nearest_neighbor[edcba] PASSED [ 4%] dask/tests/test_order.py::test_string_ordering PASSED [ 4%] dask/tests/test_order.py::test_string_ordering_dependents PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_narrow[abcde] PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_narrow[edcba] PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_ancestor[abcde] PASSED [ 4%] dask/tests/test_order.py::test_prefer_short_ancestor[edcba] PASSED [ 4%] dask/tests/test_order.py::test_map_overlap[abcde] PASSED [ 4%] dask/tests/test_order.py::test_map_overlap[edcba] PASSED [ 4%] dask/tests/test_order.py::test_use_structure_not_keys[abcde] PASSED [ 4%] dask/tests/test_order.py::test_use_structure_not_keys[edcba] PASSED [ 4%] dask/tests/test_order.py::test_dont_run_all_dependents_too_early[abcde] PASSED [ 4%] dask/tests/test_order.py::test_dont_run_all_dependents_too_early[edcba] PASSED [ 4%] dask/tests/test_order.py::test_many_branches_use_ndependencies[abcde] PASSED [ 4%] dask/tests/test_order.py::test_many_branches_use_ndependencies[edcba] PASSED [ 4%] dask/tests/test_order.py::test_order_cycle PASSED [ 4%] dask/tests/test_order.py::test_order_empty PASSED [ 4%] dask/tests/test_order.py::test_switching_dependents[abcde] PASSED [ 4%] dask/tests/test_order.py::test_switching_dependents[edcba] PASSED [ 4%] dask/tests/test_order.py::test_order_with_equal_dependents[abcde] PASSED [ 4%] dask/tests/test_order.py::test_order_with_equal_dependents[edcba] PASSED [ 4%] dask/tests/test_order.py::test_terminal_node_backtrack PASSED [ 4%] dask/tests/test_order.py::test_array_store_final_order SKIPPED (could not import 'zarr': No module named 'zarr') [ 4%] dask/tests/test_order.py::test_eager_to_compute_dependent_to_free_parent PASSED [ 4%] dask/tests/test_order.py::test_diagnostics[abcde] PASSED [ 4%] dask/tests/test_order.py::test_diagnostics[edcba] PASSED [ 4%] dask/tests/test_rewrite.py::test_head PASSED [ 4%] dask/tests/test_rewrite.py::test_args PASSED [ 4%] dask/tests/test_rewrite.py::test_traverser PASSED [ 4%] dask/tests/test_rewrite.py::test_RewriteRule PASSED [ 4%] dask/tests/test_rewrite.py::test_RewriteRuleSubs PASSED [ 4%] dask/tests/test_rewrite.py::test_RuleSet PASSED [ 4%] dask/tests/test_rewrite.py::test_matches PASSED [ 4%] dask/tests/test_rewrite.py::test_rewrite PASSED [ 4%] dask/tests/test_sizeof.py::test_base PASSED [ 4%] dask/tests/test_sizeof.py::test_name PASSED [ 4%] dask/tests/test_sizeof.py::test_containers PASSED [ 4%] dask/tests/test_sizeof.py::test_bytes_like PASSED [ 4%] dask/tests/test_sizeof.py::test_numpy PASSED [ 4%] dask/tests/test_sizeof.py::test_numpy_0_strided PASSED [ 4%] dask/tests/test_sizeof.py::test_pandas PASSED [ 4%] dask/tests/test_sizeof.py::test_pandas_multiindex PASSED [ 4%] dask/tests/test_sizeof.py::test_pandas_repeated_column PASSED [ 4%] dask/tests/test_sizeof.py::test_sparse_matrix PASSED [ 4%] dask/tests/test_sizeof.py::test_serires_object_dtype PASSED [ 4%] dask/tests/test_sizeof.py::test_dataframe_object_dtype PASSED [ 4%] dask/tests/test_sizeof.py::test_empty PASSED [ 4%] dask/tests/test_sizeof.py::test_pyarrow_table SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 4%] dask/tests/test_sizeof.py::test_dict PASSED [ 4%] dask/tests/test_sizeof.py::test_register_backend_entrypoint PASSED [ 4%] dask/tests/test_system.py::test_cpu_count PASSED [ 4%] dask/tests/test_system.py::test_cpu_count_cgroups[cpuacct,cpu] PASSED [ 4%] dask/tests/test_system.py::test_cpu_count_cgroups[cpu,cpuacct] PASSED [ 4%] dask/tests/test_system.py::test_cpu_count_cgroups[None] PASSED [ 4%] dask/tests/test_threaded.py::test_get PASSED [ 4%] dask/tests/test_threaded.py::test_nested_get PASSED [ 4%] dask/tests/test_threaded.py::test_get_without_computation PASSED [ 4%] dask/tests/test_threaded.py::test_broken_callback PASSED [ 4%] dask/tests/test_threaded.py::test_exceptions_rise_to_top PASSED [ 4%] dask/tests/test_threaded.py::test_reuse_pool[ThreadPool] PASSED [ 4%] dask/tests/test_threaded.py::test_reuse_pool[ThreadPoolExecutor] PASSED [ 4%] dask/tests/test_threaded.py::test_pool_kwarg[ThreadPool] PASSED [ 4%] dask/tests/test_threaded.py::test_pool_kwarg[ThreadPoolExecutor] PASSED [ 4%] dask/tests/test_threaded.py::test_threaded_within_thread PASSED [ 4%] dask/tests/test_threaded.py::test_dont_spawn_too_many_threads PASSED [ 4%] dask/tests/test_threaded.py::test_dont_spawn_too_many_threads_CPU_COUNT PASSED [ 4%] dask/tests/test_threaded.py::test_thread_safety PASSED [ 5%] dask/tests/test_threaded.py::test_interrupt SKIPPED (need --runslow option to run) [ 5%] dask/tests/test_typing.py::test_isinstance_core[DaskCollection] PASSED [ 5%] dask/tests/test_typing.py::test_isinstance_core[HLGDaskCollection] PASSED [ 5%] dask/tests/test_typing.py::test_isinstance_custom PASSED [ 5%] dask/tests/test_typing.py::test_parameter_passing PASSED [ 5%] dask/tests/test_typing.py::test_inheriting_class PASSED [ 5%] dask/tests/test_utils.py::test_ensure_bytes PASSED [ 5%] dask/tests/test_utils.py::test_ensure_bytes_ndarray PASSED [ 5%] dask/tests/test_utils.py::test_ensure_bytes_pyarrow_buffer SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 5%] dask/tests/test_utils.py::test_ensure_unicode PASSED [ 5%] dask/tests/test_utils.py::test_ensure_unicode_ndarray PASSED [ 5%] dask/tests/test_utils.py::test_ensure_unicode_pyarrow_buffer SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 5%] dask/tests/test_utils.py::test_getargspec PASSED [ 5%] dask/tests/test_utils.py::test_takes_multiple_arguments PASSED [ 5%] dask/tests/test_utils.py::test_dispatch PASSED [ 5%] dask/tests/test_utils.py::test_dispatch_kwargs PASSED [ 5%] dask/tests/test_utils.py::test_dispatch_variadic_on_first_argument PASSED [ 5%] dask/tests/test_utils.py::test_dispatch_lazy PASSED [ 5%] dask/tests/test_utils.py::test_dispatch_lazy_walks_mro PASSED [ 5%] dask/tests/test_utils.py::test_random_state_data PASSED [ 5%] dask/tests/test_utils.py::test_memory_repr PASSED [ 5%] dask/tests/test_utils.py::test_method_caller PASSED [ 5%] dask/tests/test_utils.py::test_skip_doctest PASSED [ 5%] dask/tests/test_utils.py::test_extra_titles PASSED [ 5%] dask/tests/test_utils.py::test_asciitable PASSED [ 5%] dask/tests/test_utils.py::test_SerializableLock PASSED [ 5%] dask/tests/test_utils.py::test_SerializableLock_name_collision PASSED [ 5%] dask/tests/test_utils.py::test_SerializableLock_locked PASSED [ 5%] dask/tests/test_utils.py::test_SerializableLock_acquire_blocking PASSED [ 5%] dask/tests/test_utils.py::test_funcname PASSED [ 5%] dask/tests/test_utils.py::test_funcname_long PASSED [ 5%] dask/tests/test_utils.py::test_funcname_toolz PASSED [ 5%] dask/tests/test_utils.py::test_funcname_multipledispatch SKIPPED (could not import 'multipledispatch': No module named 'multipledispatch') [ 5%] dask/tests/test_utils.py::test_funcname_numpy_vectorize PASSED [ 5%] dask/tests/test_utils.py::test_ndeepmap PASSED [ 5%] dask/tests/test_utils.py::test_ensure_dict PASSED [ 5%] dask/tests/test_utils.py::test_ensure_set PASSED [ 5%] dask/tests/test_utils.py::test_itemgetter PASSED [ 5%] dask/tests/test_utils.py::test_partial_by_order PASSED [ 5%] dask/tests/test_utils.py::test_has_keyword PASSED [ 5%] dask/tests/test_utils.py::test_derived_from PASSED [ 5%] dask/tests/test_utils.py::test_derived_from_func PASSED [ 5%] dask/tests/test_utils.py::test_derived_from_dask_dataframe PASSED [ 5%] dask/tests/test_utils.py::test_parse_bytes PASSED [ 5%] dask/tests/test_utils.py::test_parse_timedelta PASSED [ 5%] dask/tests/test_utils.py::test_is_arraylike PASSED [ 5%] dask/tests/test_utils.py::test_iter_chunks PASSED [ 5%] dask/tests/test_utils.py::test_stringify PASSED [ 5%] dask/tests/test_utils.py::test_stringify_collection_keys PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[0-0 B] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[920-920 B] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[930-0.91 kiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[943339.52-921.23 kiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[953579.52-0.91 MiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[965979668.48-921.23 MiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[976465428.48-0.91 GiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[989163180523.52-921.23 GiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[999900598763.52-0.91 TiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[1012903096856084.5-921.23 TiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[1023898213133844.5-0.91 PiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_bytes[1152921504606846976-1024.00 PiB] PASSED [ 5%] dask/tests/test_utils.py::test_format_time PASSED [ 5%] dask/tests/test_utils.py::test_deprecated PASSED [ 5%] dask/tests/test_utils.py::test_deprecated_version PASSED [ 5%] dask/tests/test_utils.py::test_deprecated_after_version PASSED [ 5%] dask/tests/test_utils.py::test_deprecated_category PASSED [ 5%] dask/tests/test_utils.py::test_deprecated_message PASSED [ 5%] dask/tests/test_utils.py::test_typename PASSED [ 5%] dask/tests/test_utils.py::test_typename_on_instances PASSED [ 5%] dask/tests/test_utils.py::test_cached_cumsum PASSED [ 5%] dask/tests/test_utils.py::test_cached_cumsum_nan PASSED [ 5%] dask/tests/test_utils.py::test_cached_cumsum_non_tuple PASSED [ 5%] dask/tests/test_utils.py::test_tmpfile_naming PASSED [ 5%] dask/tests/test_utils_test.py::test_hlg_layer PASSED [ 5%] dask/tests/test_utils_test.py::test_hlg_layer_topological PASSED [ 5%] dask/tests/test_utils_test.py::test__check_warning PASSED [ 5%] dask/array/tests/test_array_core.py::test_graph_from_arraylike[True] PASSED [ 5%] dask/array/tests/test_array_core.py::test_graph_from_arraylike[False] PASSED [ 5%] dask/array/tests/test_array_core.py::test_top PASSED [ 5%] dask/array/tests/test_array_core.py::test_top_with_kwargs PASSED [ 5%] dask/array/tests/test_array_core.py::test_top_supports_broadcasting_rules PASSED [ 5%] dask/array/tests/test_array_core.py::test_top_literals PASSED [ 5%] dask/array/tests/test_array_core.py::test_blockwise_literals PASSED [ 5%] dask/array/tests/test_array_core.py::test_blockwise_1_in_shape_I PASSED [ 5%] dask/array/tests/test_array_core.py::test_blockwise_1_in_shape_II PASSED [ 5%] dask/array/tests/test_array_core.py::test_blockwise_1_in_shape_III PASSED [ 5%] dask/array/tests/test_array_core.py::test_concatenate3_on_scalars PASSED [ 5%] dask/array/tests/test_array_core.py::test_chunked_dot_product PASSED [ 5%] dask/array/tests/test_array_core.py::test_chunked_transpose_plus_one PASSED [ 5%] dask/array/tests/test_array_core.py::test_broadcast_dimensions_works_with_singleton_dimensions PASSED [ 5%] dask/array/tests/test_array_core.py::test_broadcast_dimensions PASSED [ 5%] dask/array/tests/test_array_core.py::test_Array PASSED [ 5%] dask/array/tests/test_array_core.py::test_uneven_chunks PASSED [ 5%] dask/array/tests/test_array_core.py::test_numblocks_suppoorts_singleton_block_dims PASSED [ 5%] dask/array/tests/test_array_core.py::test_keys PASSED [ 5%] dask/array/tests/test_array_core.py::test_Array_computation PASSED [ 5%] dask/array/tests/test_array_core.py::test_Array_numpy_gufunc_call__array_ufunc__01 PASSED [ 5%] dask/array/tests/test_array_core.py::test_Array_numpy_gufunc_call__array_ufunc__02 PASSED [ 5%] dask/array/tests/test_array_core.py::test_stack PASSED [ 5%] dask/array/tests/test_array_core.py::test_stack_zero_size PASSED [ 5%] dask/array/tests/test_array_core.py::test_short_stack PASSED [ 5%] dask/array/tests/test_array_core.py::test_stack_scalars PASSED [ 5%] dask/array/tests/test_array_core.py::test_stack_promote_type PASSED [ 5%] dask/array/tests/test_array_core.py::test_stack_rechunk PASSED [ 6%] dask/array/tests/test_array_core.py::test_stack_unknown_chunksizes PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_types[dtypes0] PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_types[dtypes1] PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_unknown_axes PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_flatten PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_rechunk PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_fixlen_strings PASSED [ 6%] dask/array/tests/test_array_core.py::test_concatenate_zero_size PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_simple_row_wise PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_simple_column_wise PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_with_1d_arrays_row_wise PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_with_1d_arrays_multiple_rows PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_with_1d_arrays_column_wise PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_mixed_1d_and_2d PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_complicated PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_nested PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_3d PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_with_mismatched_shape PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_no_lists PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_invalid_nesting PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_empty_lists PASSED [ 6%] dask/array/tests/test_array_core.py::test_block_tuple PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_shapes PASSED [ 6%] dask/array/tests/test_array_core.py::test_elemwise_on_scalars PASSED [ 6%] dask/array/tests/test_array_core.py::test_elemwise_with_ndarrays PASSED [ 6%] dask/array/tests/test_array_core.py::test_elemwise_differently_chunked PASSED [ 6%] dask/array/tests/test_array_core.py::test_elemwise_dtype PASSED [ 6%] dask/array/tests/test_array_core.py::test_operators PASSED [ 6%] dask/array/tests/test_array_core.py::test_operator_dtype_promotion PASSED [ 6%] dask/array/tests/test_array_core.py::test_field_access PASSED [ 6%] dask/array/tests/test_array_core.py::test_field_access_with_shape PASSED [ 6%] dask/array/tests/test_array_core.py::test_matmul PASSED [ 6%] dask/array/tests/test_array_core.py::test_matmul_array_ufunc PASSED [ 6%] dask/array/tests/test_array_core.py::test_T PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_to PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_to_array PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_to_scalar PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_to_chunks PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_arrays PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_arrays_uneven_chunks PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape0-v_shape0] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape1-v_shape1] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape2-v_shape2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape3-v_shape3] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape4-v_shape4] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape5-v_shape5] PASSED [ 6%] dask/array/tests/test_array_core.py::test_broadcast_operator[u_shape6-v_shape6] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape0-new_shape0-chunks0] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape1-new_shape1-5] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape2-new_shape2-5] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape3-new_shape3-12] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape4-new_shape4-12] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape5-new_shape5-chunks5] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape6-new_shape6-4] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape7-new_shape7-4] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape8-new_shape8-4] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape9-new_shape9-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape10-new_shape10-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape11-new_shape11-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape12-new_shape12-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape13-new_shape13-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape14-new_shape14-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape15-new_shape15-2] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape16-new_shape16-chunks16] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape17-new_shape17-3] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape18-new_shape18-4] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape19-new_shape19-chunks19] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape20-new_shape20-1] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape21-new_shape21-1] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape22-new_shape22-24] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape23-new_shape23-6] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape24-new_shape24-6] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape25-new_shape25-6] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape26-new_shape26-chunks26] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape27-new_shape27-chunks27] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape28-new_shape28-chunks28] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape29-new_shape29-chunks29] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape30-new_shape30-chunks30] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape31-new_shape31-chunks31] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape32-new_shape32-chunks32] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape33-new_shape33-chunks33] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape[original_shape34-new_shape34-chunks34] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_exceptions PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_splat PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_not_implemented_error PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_unknown_dimensions PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape0-chunks0-reshape_size0-None] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape0-chunks0-reshape_size0-134217728] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape0-chunks0-reshape_size0-67108864] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape1-chunks1-reshape_size1-None] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape1-chunks1-reshape_size1-134217728] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_avoids_large_chunks[shape1-chunks1-reshape_size1-67108864] PASSED [ 6%] dask/array/tests/test_array_core.py::test_reshape_warns_by_default_if_it_is_producing_large_chunks PASSED [ 6%] dask/array/tests/test_array_core.py::test_full PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks2 PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_block_info PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_block_info_with_new_axis PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_block_info_with_drop_axis PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_block_info_with_broadcast PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_with_constants PASSED [ 6%] dask/array/tests/test_array_core.py::test_map_blocks_with_kwargs PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_infer_chunks_broadcast PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_with_chunks PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_dtype_inference PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_infer_newaxis PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_no_array_args PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_unique_name_chunks_dtype PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_unique_name_drop_axis PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_unique_name_new_axis PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_optimize_blockwise[0] PASSED [ 7%] dask/array/tests/test_array_core.py::test_map_blocks_optimize_blockwise[1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_repr PASSED [ 7%] dask/array/tests/test_array_core.py::test_repr_meta SKIPPED (could not import 'sparse': No module named 'sparse') [ 7%] dask/array/tests/test_array_core.py::test_repr_html_array_highlevelgraph PASSED [ 7%] dask/array/tests/test_array_core.py::test_slicing_with_ellipsis PASSED [ 7%] dask/array/tests/test_array_core.py::test_slicing_with_ndarray PASSED [ 7%] dask/array/tests/test_array_core.py::test_slicing_flexible_type PASSED [ 7%] dask/array/tests/test_array_core.py::test_slicing_with_object_dtype PASSED [ 7%] dask/array/tests/test_array_core.py::test_dtype PASSED [ 7%] dask/array/tests/test_array_core.py::test_blockdims_from_blockshape PASSED [ 7%] dask/array/tests/test_array_core.py::test_coerce PASSED [ 7%] dask/array/tests/test_array_core.py::test_bool PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_kwargs PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_delayed_target PASSED [ 7%] dask/array/tests/test_array_core.py::test_store PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_regions PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_compute_false PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_nocompute_regions PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_locks PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_method_return PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_multiprocessing_lock XFAIL (can't lock with multiprocessing) [ 7%] dask/array/tests/test_array_core.py::test_store_deterministic_keys[False-False] PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_deterministic_keys[False-True] PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_deterministic_keys[True-False] PASSED [ 7%] dask/array/tests/test_array_core.py::test_store_deterministic_keys[True-True] PASSED [ 7%] dask/array/tests/test_array_core.py::test_to_hdf5 PASSED [ 7%] dask/array/tests/test_array_core.py::test_to_dask_dataframe PASSED [ 7%] dask/array/tests/test_array_core.py::test_np_array_with_zero_dimensions PASSED [ 7%] dask/array/tests/test_array_core.py::test_dtype_complex PASSED [ 7%] dask/array/tests/test_array_core.py::test_astype PASSED [ 7%] dask/array/tests/test_array_core.py::test_astype_gh1151 PASSED [ 7%] dask/array/tests/test_array_core.py::test_astype_gh9318 PASSED [ 7%] dask/array/tests/test_array_core.py::test_astype_gh9316 XFAIL (Github issue https://github.com/dask/dask/issues/9316) [ 7%] dask/array/tests/test_array_core.py::test_arithmetic PASSED [ 7%] dask/array/tests/test_array_core.py::test_elemwise_consistent_names PASSED [ 7%] dask/array/tests/test_array_core.py::test_optimize PASSED [ 7%] dask/array/tests/test_array_core.py::test_slicing_with_non_ndarrays PASSED [ 7%] dask/array/tests/test_array_core.py::test_getter PASSED [ 7%] dask/array/tests/test_array_core.py::test_size PASSED [ 7%] dask/array/tests/test_array_core.py::test_nbytes PASSED [ 7%] dask/array/tests/test_array_core.py::test_itemsize PASSED [ 7%] dask/array/tests/test_array_core.py::test_Array_normalizes_dtype PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_with_lock[True] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_with_lock[False] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[True-x0-chunks0] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[True-x1--1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[True-x2-1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[True-x3-1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[False-x0-chunks0] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[False-x1--1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[False-x2-1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_tasks_always_call_getter[False-x3-1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x0] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x2] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x3] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x4] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_onechunk[x5] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_ndarray_getitem PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_list[x0] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_list[x1] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_list[x2] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[bool] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[bytes] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[complex] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[float] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[int] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[bool_] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[bytes_] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[complex128] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[complex256] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[complex64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[datetime64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[float128] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[float16] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[float32] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[float64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[int16] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[int32] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[int64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[int8] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[longlong] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[object_] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[str_] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[timedelta64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[uint16] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[uint32] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[uint64] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[uint8] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[ulonglong] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[void] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_scalar[str] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_no_asarray[True-True-ndarray] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_no_asarray[True-False-matrix] PASSED [ 7%] dask/array/tests/test_array_core.py::test_from_array_no_asarray[False-True-ndarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_no_asarray[False-False-matrix] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_getitem[True-True] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_getitem[True-False] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_getitem[False-True] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_getitem[False-False] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_minus_one PASSED [ 8%] dask/array/tests/test_array_core.py::test_array_copy_noop[-1] PASSED [ 8%] dask/array/tests/test_array_core.py::test_array_copy_noop[2] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_dask_array PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_dask_collection_warns PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_inline PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray[asarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray[asanyarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_dask_dataframe[asarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_dask_dataframe[asanyarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_h5py[True-asarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_h5py[True-asanyarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_h5py[False-asarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_h5py[False-asanyarray] PASSED [ 8%] dask/array/tests/test_array_core.py::test_asarray_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_asanyarray PASSED [ 8%] dask/array/tests/test_array_core.py::test_asanyarray_dataframe PASSED [ 8%] dask/array/tests/test_array_core.py::test_asanyarray_datetime64 PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_func PASSED [ 8%] dask/array/tests/test_array_core.py::test_concatenate3_2 PASSED [ 8%] dask/array/tests/test_array_core.py::test_concatenate3_nep18_dispatching[True] PASSED [ 8%] dask/array/tests/test_array_core.py::test_concatenate3_nep18_dispatching[False] PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks3 PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_with_missing_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_normalize_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_align_chunks_to_previous_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_raise_on_no_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_chunks_is_immutable PASSED [ 8%] dask/array/tests/test_array_core.py::test_raise_on_bad_kwargs PASSED [ 8%] dask/array/tests/test_array_core.py::test_long_slice PASSED [ 8%] dask/array/tests/test_array_core.py::test_h5py_newaxis PASSED [ 8%] dask/array/tests/test_array_core.py::test_ellipsis_slicing PASSED [ 8%] dask/array/tests/test_array_core.py::test_point_slicing PASSED [ 8%] dask/array/tests/test_array_core.py::test_point_slicing_with_full_slice PASSED [ 8%] dask/array/tests/test_array_core.py::test_slice_with_floats PASSED [ 8%] dask/array/tests/test_array_core.py::test_slice_with_integer_types PASSED [ 8%] dask/array/tests/test_array_core.py::test_index_with_integer_types PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_basic PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_nd PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_negative PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_errors PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_merge PASSED [ 8%] dask/array/tests/test_array_core.py::test_vindex_identity PASSED [ 8%] dask/array/tests/test_array_core.py::test_empty_array PASSED [ 8%] dask/array/tests/test_array_core.py::test_memmap PASSED [ 8%] dask/array/tests/test_array_core.py::test_to_npy_stack PASSED [ 8%] dask/array/tests/test_array_core.py::test_view PASSED [ 8%] dask/array/tests/test_array_core.py::test_view_fortran PASSED [ 8%] dask/array/tests/test_array_core.py::test_h5py_tokenize PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_with_changed_dimension PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_with_negative_drop_axis PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_with_invalid_drop_axis PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_with_changed_dimension_and_broadcast_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_broadcast_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_chunks_error PASSED [ 8%] dask/array/tests/test_array_core.py::test_array_compute_forward_kwargs PASSED [ 8%] dask/array/tests/test_array_core.py::test_dont_fuse_outputs PASSED [ 8%] dask/array/tests/test_array_core.py::test_dont_dealias_outputs PASSED [ 8%] dask/array/tests/test_array_core.py::test_timedelta_op PASSED [ 8%] dask/array/tests/test_array_core.py::test_to_delayed PASSED [ 8%] dask/array/tests/test_array_core.py::test_to_delayed_optimize_graph PASSED [ 8%] dask/array/tests/test_array_core.py::test_cumulative PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_delayed PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_delayed_meta PASSED [ 8%] dask/array/tests/test_array_core.py::test_A_property PASSED [ 8%] dask/array/tests/test_array_core.py::test_copy_mutate PASSED [ 8%] dask/array/tests/test_array_core.py::test_npartitions PASSED [ 8%] dask/array/tests/test_array_core.py::test_elemwise_name PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_name PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_token_deprecated PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_names SKIPPED (could not import 'distributed': cannot import name 'factors' from 'dask.utils' (/build/python-dask/src/dask-2022.12.1/dask/utils.py)) [ 8%] dask/array/tests/test_array_core.py::test_array_picklable[array0] PASSED [ 8%] dask/array/tests/test_array_core.py::test_array_picklable[array1] PASSED [ 8%] dask/array/tests/test_array_core.py::test_from_array_raises_on_bad_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_concatenate_axes PASSED [ 8%] dask/array/tests/test_array_core.py::test_blockwise_concatenate PASSED [ 8%] dask/array/tests/test_array_core.py::test_common_blockdim PASSED [ 8%] dask/array/tests/test_array_core.py::test_uneven_chunks_that_fit_neatly PASSED [ 8%] dask/array/tests/test_array_core.py::test_elemwise_uneven_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_uneven_chunks_blockwise PASSED [ 8%] dask/array/tests/test_array_core.py::test_warn_bad_rechunking PASSED [ 8%] dask/array/tests/test_array_core.py::test_concatenate_stack_dont_warn PASSED [ 8%] dask/array/tests/test_array_core.py::test_map_blocks_delayed PASSED [ 8%] dask/array/tests/test_array_core.py::test_no_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_no_chunks_2d PASSED [ 8%] dask/array/tests/test_array_core.py::test_no_chunks_yes_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_raise_informative_errors_no_chunks PASSED [ 8%] dask/array/tests/test_array_core.py::test_no_chunks_slicing_2d PASSED [ 8%] dask/array/tests/test_array_core.py::test_index_array_with_array_1d PASSED [ 8%] dask/array/tests/test_array_core.py::test_index_array_with_array_2d PASSED [ 8%] dask/array/tests/test_array_core.py::test_index_array_with_array_3d_2d XFAIL (Chunking does not align well) [ 8%] dask/array/tests/test_array_core.py::test_setitem_1d PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_hardmask PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_2d PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_extended_API_0d PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index0--1] PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index1--2] PASSED [ 8%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index2--3] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index3-value3] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index4--4] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index5-value5] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index6--5] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index7--6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index8--4] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index9--5] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index10-value10] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_1d[index11-value11] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index0--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index1--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index2--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index3--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index4--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[5--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index6-value6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[3-value7] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index8-value8] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index9-value9] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index10-value10] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index11-value11] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index12-value12] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index13-value13] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index14--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index15--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index16--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index17--1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index18-value18] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index19--99] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index20-value20] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index21--98] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d[index22-value22] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d_rhs_func_of_lhs PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d_mask[index0-value0] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_extended_API_2d_mask[index1-value1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_on_read_only_blocks PASSED [ 9%] dask/array/tests/test_array_core.py::test_setitem_errs PASSED [ 9%] dask/array/tests/test_array_core.py::test_zero_slice_dtypes PASSED [ 9%] dask/array/tests/test_array_core.py::test_zero_sized_array_rechunk PASSED [ 9%] dask/array/tests/test_array_core.py::test_blockwise_zero_shape PASSED [ 9%] dask/array/tests/test_array_core.py::test_blockwise_zero_shape_new_axes PASSED [ 9%] dask/array/tests/test_array_core.py::test_broadcast_against_zero_shape PASSED [ 9%] dask/array/tests/test_array_core.py::test_from_array_name PASSED [ 9%] dask/array/tests/test_array_core.py::test_concatenate_errs PASSED [ 9%] dask/array/tests/test_array_core.py::test_stack_errs PASSED [ 9%] dask/array/tests/test_array_core.py::test_blockwise_with_numpy_arrays PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other0-100] PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other0-6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other1-100] PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other1-6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other2-100] PASSED [ 9%] dask/array/tests/test_array_core.py::test_elemwise_with_lists[other2-6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_constructor_plugin PASSED [ 9%] dask/array/tests/test_array_core.py::test_no_warnings_on_metadata PASSED [ 9%] dask/array/tests/test_array_core.py::test_delayed_array_key_hygeine PASSED [ 9%] dask/array/tests/test_array_core.py::test_empty_chunks_in_array_len PASSED [ 9%] dask/array/tests/test_array_core.py::test_meta[None] PASSED [ 9%] dask/array/tests/test_array_core.py::test_meta[dtype1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[100-10-expected0] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[20-10-expected1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[20-5-expected2] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[24-5-expected3] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[23-5-expected4] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_1d[1000-167-expected5] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_2d[shape0-chunks0-20-expected0] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_2d[shape1-chunks1-20-expected1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_2d[shape2-auto-10-expected2] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_auto_3d PASSED [ 9%] dask/array/tests/test_array_core.py::test_constructors_chunks_dict PASSED [ 9%] dask/array/tests/test_array_core.py::test_from_array_chunks_dict PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_object_dtype[object] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_object_dtype[dtype1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_tuples_of_tuples PASSED [ 9%] dask/array/tests/test_array_core.py::test_normalize_chunks_nan PASSED [ 9%] dask/array/tests/test_array_core.py::test_pandas_from_dask_array PASSED [ 9%] dask/array/tests/test_array_core.py::test_from_zarr_unique_name SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_from_zarr_name SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_roundtrip SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_roundtrip_with_path_like SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_return_stored[False] SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_return_stored[True] SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_inline_array[True] SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_inline_array[False] SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_existing_array SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_to_zarr_unknown_chunks_raises SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_read_zarr_chunks SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_pass_mapper SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_group SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data0] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data1] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data2] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data3] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data4] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data5] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data6] PASSED [ 9%] dask/array/tests/test_array_core.py::test_regular_chunks[data7] PASSED [ 9%] dask/array/tests/test_array_core.py::test_zarr_nocompute SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_zarr_regions SKIPPED (could not import 'zarr': No module named 'zarr') [ 9%] dask/array/tests/test_array_core.py::test_tiledb_roundtrip SKIPPED (could not import 'tiledb': No module named 'tiledb') [ 9%] dask/array/tests/test_array_core.py::test_tiledb_multiattr SKIPPED (could not import 'tiledb': No module named 'tiledb') [ 9%] dask/array/tests/test_array_core.py::test_blockview PASSED [ 9%] dask/array/tests/test_array_core.py::test_blocks_indexer PASSED [ 9%] dask/array/tests/test_array_core.py::test_partitions_indexer PASSED [ 9%] dask/array/tests/test_array_core.py::test_dask_array_holds_scipy_sparse_containers PASSED [ 10%] dask/array/tests/test_array_core.py::test_scipy_sparse_concatenate[0] PASSED [ 10%] dask/array/tests/test_array_core.py::test_scipy_sparse_concatenate[1] PASSED [ 10%] dask/array/tests/test_array_core.py::test_3851 PASSED [ 10%] dask/array/tests/test_array_core.py::test_3925 PASSED [ 10%] dask/array/tests/test_array_core.py::test_map_blocks_large_inputs_delayed PASSED [ 10%] dask/array/tests/test_array_core.py::test_blockwise_large_inputs_delayed PASSED [ 10%] dask/array/tests/test_array_core.py::test_slice_reversed PASSED [ 10%] dask/array/tests/test_array_core.py::test_map_blocks_chunks PASSED [ 10%] dask/array/tests/test_array_core.py::test_nbytes_auto PASSED [ 10%] dask/array/tests/test_array_core.py::test_auto_chunks_h5py PASSED [ 10%] dask/array/tests/test_array_core.py::test_no_warnings_from_blockwise PASSED [ 10%] dask/array/tests/test_array_core.py::test_from_array_meta SKIPPED (could not import 'sparse': No module named 'sparse') [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_2d_array PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_3d_array PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_rechunk PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_to_zarr SKIPPED (could not import 'zarr': No module named 'zarr') [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_to_svg PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_concatenate PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_reduction PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_reshape PASSED [ 10%] dask/array/tests/test_array_core.py::test_compute_chunk_sizes_warning_fixes_slicing PASSED [ 10%] dask/array/tests/test_array_core.py::test_rechunk_auto PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_assignment_invalidates_cached_properties PASSED [ 10%] dask/array/tests/test_array_core.py::test_map_blocks_series PASSED [ 10%] dask/array/tests/test_array_core.py::test_map_blocks_dataframe XFAIL (need to remove singleton index dimension) [ 10%] dask/array/tests/test_array_core.py::test_dask_layers PASSED [ 10%] dask/array/tests/test_array_core.py::test_len_object_with_unknown_size PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_shape_broadcast[0] PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_shape_broadcast[1] PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_shape_broadcast[3] PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_shape_broadcast[8] PASSED [ 10%] dask/array/tests/test_array_core.py::test_chunk_non_array_like PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[0] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[1] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[2] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[3] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[4] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[5] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[6] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[7] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[8] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[9] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[10] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[11] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[12] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[13] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[14] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[15] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[16] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[17] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[18] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[19] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_dask[20] PASSED [ 10%] dask/array/tests/test_array_function.py::test_stack_functions_require_sequence_of_arrays[0] PASSED [ 10%] dask/array/tests/test_array_function.py::test_stack_functions_require_sequence_of_arrays[1] PASSED [ 10%] dask/array/tests/test_array_function.py::test_stack_functions_require_sequence_of_arrays[2] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_fft[fft] PASSED [ 10%] dask/array/tests/test_array_function.py::test_array_function_fft[fft2] PASSED [ 10%] 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dask/array/tests/test_array_function.py::test_array_function_cupy_svd[chunks1] SKIPPED (could not import 'cupy': No module named 'cupy') [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[0] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[1] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[2] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[3] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[4] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[5] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[6] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[7] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[8] PASSED [ 10%] dask/array/tests/test_array_function.py::test_unregistered_func[9] PASSED [ 10%] 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dask/array/tests/test_array_utils.py::test_meta_from_array_literal[float-str2] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_meta_from_array_type_inputs PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_checks_dtype[a0-1.0] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_checks_dtype[a1-b1] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_checks_dtype[a2-b2] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_scheduler[1.0-1.0] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_scheduler[a1-b1] PASSED [ 11%] dask/array/tests/test_array_utils.py::test_assert_eq_scheduler[a2-b2] PASSED [ 11%] dask/array/tests/test_atop.py::test_rewrite[inputs0-expected0] PASSED [ 11%] dask/array/tests/test_atop.py::test_rewrite[inputs1-expected1] PASSED [ 11%] dask/array/tests/test_atop.py::test_rewrite[inputs2-expected2] PASSED [ 11%] dask/array/tests/test_atop.py::test_rewrite[inputs3-expected3] PASSED [ 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'cupy': No module named 'cupy') [ 11%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-empty-numpy] PASSED [ 11%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 11%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-tuple-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-full_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-full-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-list-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-empty_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-empty-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-ones_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-ones-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-zeros_like-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-zeros-numpy] PASSED [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 12%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-None-shape0-chunks0-asarray-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-tuple-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-ones_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-ones-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-zeros_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-zeros-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-full_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-full-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-empty_like-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-empty-numpy] PASSED [ 13%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-list-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-C-my-name-shape0-chunks0-asarray-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-full_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-full-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-empty_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-empty-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-ones_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-ones-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-zeros_like-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-zeros-numpy] PASSED [ 14%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-tuple-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-list-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-empty-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-ones_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-ones-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-zeros_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-zeros-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-full_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-full-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-empty_like-numpy] PASSED [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 15%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-None-shape0-chunks0-asarray-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-tuple-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-zeros-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-full_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-full-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-empty_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-empty-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-ones_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-ones-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-zeros_like-numpy] PASSED [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 16%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-zeros-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-full_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-full-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-list-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-empty_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-empty-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-ones_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-ones-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-zeros_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-zeros-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-full_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-full-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-tuple-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-empty_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-empty-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-ones_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-ones-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-zeros_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-zeros-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-full_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-full-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-list-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-empty_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-empty_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-empty-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-empty-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-ones_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-ones_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-ones-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-ones-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-zeros_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-zeros_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-zeros-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-zeros-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-full_like-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-full_like-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-full-numpy] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like[i4-F-my-name-shape0-chunks0-asarray-asarray-full-cupy] SKIPPED (could not import 'cupy': No module named 'cupy') [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape0-chunks0-None-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape0-chunks0-None-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape0-chunks0-None-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape0-chunks0-None-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape1-chunks1-out_shape1-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape1-chunks1-out_shape1-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape1-chunks1-out_shape1-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape1-chunks1-out_shape1-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape2-4-20-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape2-4-20-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape2-4-20-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape2-4-20-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape3-chunks3-out_shape3-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape3-chunks3-out_shape3-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape3-chunks3-out_shape3-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape3-chunks3-out_shape3-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape4-None-out_shape4-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape4-None-out_shape4-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape4-None-out_shape4-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape4-None-out_shape4-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape5-chunks5-out_shape5-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape5-chunks5-out_shape5-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape5-chunks5-out_shape5-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape5-chunks5-out_shape5-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape6-chunks6-out_shape6-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape6-chunks6-out_shape6-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape6-chunks6-out_shape6-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape6-chunks6-out_shape6-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape7-auto-out_shape7-empty_like-kwargs0] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape7-auto-out_shape7-ones_like-kwargs1] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape7-auto-out_shape7-zeros_like-kwargs2] PASSED [ 17%] dask/array/tests/test_creation.py::test_arr_like_shape[i4-shape7-auto-out_shape7-full_like-kwargs3] PASSED [ 17%] dask/array/tests/test_creation.py::test_linspace[True] PASSED [ 17%] dask/array/tests/test_creation.py::test_linspace[False] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[0-1-1-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[1.5-2-1-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[1-2.5-1-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[1-2-0.5-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start4-stop4-step4-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start5-stop5-step5-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start6-stop6-step6-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start7-stop7-step7-None] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start8-stop8-step8-uint32] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_dtypes[start9-stop9-step9-uint64] PASSED [ 17%] dask/array/tests/test_creation.py::test_arange_cast_float_int_step XFAIL (Casting floats to ints is not supported since edgebehavior is not specified or guaranteed by NumPy.) [ 17%] dask/array/tests/test_creation.py::test_arange_float_step PASSED [ 17%] dask/array/tests/test_creation.py::test_indices_wrong_chunks PASSED [ 17%] dask/array/tests/test_creation.py::test_indices_dimensions_chunks PASSED [ 17%] dask/array/tests/test_creation.py::test_empty_indices PASSED [ 18%] dask/array/tests/test_creation.py::test_indices PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes0-chunks0] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes1-chunks1] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes2-chunks2] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes3-chunks3] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes4-chunks4] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-ij-shapes5-chunks5] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes0-chunks0] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes1-chunks1] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes2-chunks2] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes3-chunks3] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes4-chunks4] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[False-xy-shapes5-chunks5] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes0-chunks0] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes1-chunks1] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes2-chunks2] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes3-chunks3] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes4-chunks4] PASSED [ 18%] dask/array/tests/test_creation.py::test_meshgrid[True-ij-shapes5-chunks5] PASSED [ 18%] 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dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths3-int16] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths3-float32] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths3-bool] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths4-uint8] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths4-int16] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths4-float32] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[edge-pad_widths4-bool] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[linear_ramp-2-uint8] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[linear_ramp-2-int16] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[linear_ramp-2-float32] PASSED [ 19%] dask/array/tests/test_creation.py::test_pad_3d_data[linear_ramp-2-bool] PASSED [ 19%] 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dask/array/tests/test_creation.py::test_pad_3d_data[maximum-pad_widths3-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[maximum-pad_widths4-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[maximum-pad_widths4-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[maximum-pad_widths4-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[maximum-pad_widths4-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-2-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-2-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-2-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-2-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths1-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths1-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths1-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths1-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths2-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths2-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths2-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths2-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths3-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths3-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths3-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths3-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths4-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths4-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths4-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[mean-pad_widths4-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-2-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-2-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-2-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-2-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths1-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths1-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths1-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths1-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths2-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths2-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths2-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths2-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths3-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths3-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths3-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths3-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths4-uint8] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths4-int16] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths4-float32] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[minimum-pad_widths4-bool] PASSED [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths1-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths1-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths1-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths1-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths3-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths3-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths3-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths3-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths4-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths4-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths4-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[reflect-pad_widths4-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths1-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths1-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths1-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths1-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths3-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths3-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths3-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths3-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths4-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths4-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths4-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 20%] dask/array/tests/test_creation.py::test_pad_3d_data[symmetric-pad_widths4-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths1-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths1-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths1-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths1-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths2-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths2-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths2-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths2-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths3-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths3-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths3-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths3-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths4-uint8] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths4-int16] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths4-float32] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[wrap-pad_widths4-bool] SKIPPED (Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-2-uint8] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-2-int16] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-2-float32] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-2-bool] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths1-uint8] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths1-int16] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths1-float32] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths1-bool] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths2-uint8] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths2-int16] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths2-float32] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths2-bool] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths3-uint8] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths3-int16] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths3-float32] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths3-bool] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths4-uint8] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths4-int16] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths4-float32] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[median-pad_widths4-bool] SKIPPED (Not implemented) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-2-uint8] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-2-int16] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-2-float32] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-2-bool] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths1-uint8] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths1-int16] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths1-float32] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths1-bool] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths2-uint8] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths2-int16] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths2-float32] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths2-bool] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths3-uint8] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths3-int16] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths3-float32] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths3-bool] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths4-uint8] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths4-int16] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths4-float32] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_3d_data[empty-pad_widths4-bool] SKIPPED (Empty leads to undefined values, which may be different) [ 21%] dask/array/tests/test_creation.py::test_pad_udf[kwargs0] PASSED [ 21%] dask/array/tests/test_creation.py::test_pad_udf[kwargs1] PASSED [ 21%] dask/array/tests/test_creation.py::test_auto_chunks PASSED [ 21%] dask/array/tests/test_creation.py::test_string_auto_chunk PASSED [ 21%] dask/array/tests/test_creation.py::test_diagonal_zero_chunks PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-add0] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-eq] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-gt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-ge] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-lt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-le] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-mod] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-mul] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-ne] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-pow] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-sub] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-truediv] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-floordiv] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-add1] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast0-arr_downcast0-subtract] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-add0] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-eq] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-gt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-ge] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-lt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-le] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-mod] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-mul] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-ne] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-pow] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-sub] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-truediv] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-floordiv] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-add1] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast1-arr_downcast1-subtract] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-add0] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-eq] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-gt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-ge] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-lt] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-le] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-mod] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-mul] PASSED [ 21%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-ne] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-pow] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-sub] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-truediv] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-floordiv] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-add1] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_binary_operation_type_precedence[arr_upcast2-arr_downcast2-subtract] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[arr0-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[arr1-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[arr2-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[arr3-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[arr4-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[None-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[0.0-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[0-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_array_chunk[-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[WrappedArray-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[Array-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[EncapsulateNDArray-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[MaskedArray-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[ndarray-True] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[float-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_is_valid_chunk_type[int-False] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_direct_deferral_wrapping_override PASSED [ 22%] dask/array/tests/test_dispatch.py::test_delegation_unknown_scalar_that_understands_arr_ops[arr0] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_delegation_unknown_scalar_that_understands_arr_ops[arr1] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_delegation_unknown_scalar[arr0] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_delegation_unknown_scalar[arr1] PASSED [ 22%] dask/array/tests/test_dispatch.py::test_delegation_specific_cases PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[ifft] PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[rfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[irfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[hfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_cant_fft_chunked_axis[ihfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[ifft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[rfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[irfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[hfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft[ihfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[fft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[ifft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[fftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[ifftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[rfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[irfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[rfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft2n_shapes[irfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[ifft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[rfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[irfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[hfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_n_kwarg[ihfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[ifft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[rfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[irfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[hfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_fft_consistent_names[ihfft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_bad_kind PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-fft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-ifft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-fftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-ifftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-rfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-irfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-rfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float32-irfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-fft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-ifft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-fftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-ifftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-rfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-irfft2] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-rfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_nd_ffts_axes[float64-irfftn] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-fft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-fft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-ifft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-ifft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-rfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-rfft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-irfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-irfft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-hfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-hfft-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `hfft`.) [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-ihfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float32-ihfft-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `ihfft`.) [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-fft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-fft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-ifft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-ifft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-rfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-rfft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-irfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-irfft-scipy.fftpack] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-hfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-hfft-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `hfft`.) [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-ihfft-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_ffts[float64-ihfft-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `ihfft`.) [ 22%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-fft2-numpy.fft] PASSED [ 22%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-fft2-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-ifft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-ifft2-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-fftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-fftn-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-ifftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-ifftn-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-rfft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-rfft2-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `rfft2`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-irfft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-irfft2-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `irfft2`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-rfftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-rfftn-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `rfftn`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-irfftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float32-irfftn-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `irfftn`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-fft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-fft2-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-ifft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-ifft2-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-fftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-fftn-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-ifftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-ifftn-scipy.fftpack] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-rfft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-rfft2-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `rfft2`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-irfft2-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-irfft2-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `irfft2`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-rfftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-rfftn-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `rfftn`.) [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-irfftn-numpy.fft] PASSED [ 23%] dask/array/tests/test_fft.py::test_wrap_fftns[float64-irfftn-scipy.fftpack] SKIPPED (`scipy.fftpack` missing function `irfftn`.) [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-1.0-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-1.0-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-1.0-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-1.0-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-1.0-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-0.5-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-0.5-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-0.5-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-0.5-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-0.5-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-6.283185307179586-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-6.283185307179586-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-6.283185307179586-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-6.283185307179586-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[0-6.283185307179586-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-1.0-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-1.0-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-1.0-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-1.0-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-1.0-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-0.5-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-0.5-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-0.5-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-0.5-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-0.5-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-6.283185307179586-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-6.283185307179586-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-6.283185307179586-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-6.283185307179586-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftfreq[1-6.283185307179586-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-1.0-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-1.0-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-1.0-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-1.0-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-1.0-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-0.5-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-0.5-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-0.5-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-0.5-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-0.5-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-6.283185307179586-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-6.283185307179586-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-6.283185307179586-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-6.283185307179586-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[0-6.283185307179586-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-1.0-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-1.0-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-1.0-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-1.0-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-1.0-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-0.5-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-0.5-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-0.5-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-0.5-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-0.5-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-6.283185307179586-1] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-6.283185307179586-2] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-6.283185307179586-3] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-6.283185307179586-6] PASSED [ 23%] dask/array/tests/test_fft.py::test_rfftfreq[1-6.283185307179586-7] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-None-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-None-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-0-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-0-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-1-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-1-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-2-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-2-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes4-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes4-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes5-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes5-ifftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes6-fftshift] PASSED [ 23%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes6-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes7-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape0-chunks0-axes7-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-None-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-None-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-0-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-0-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-1-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-1-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-2-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-2-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes4-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes4-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes5-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes5-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes6-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes6-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes7-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape1-chunks1-axes7-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-None-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-None-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-0-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-0-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-1-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-1-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-2-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-2-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes4-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes4-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes5-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes5-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes6-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes6-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes7-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift[shape2-chunks2-axes7-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-None-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-None-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-0-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-0-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-1-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-1-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-2-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-2-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes4-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes4-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes5-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes5-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes6-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes6-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes7-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape0-chunks0-axes7-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-None-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-None-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-0-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-0-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-1-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-1-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-2-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-2-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes4-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes4-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes5-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes5-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes6-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes6-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes7-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape1-chunks1-axes7-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-None-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-None-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-0-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-0-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-1-fftshift-ifftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-1-ifftshift-fftshift] PASSED [ 24%] dask/array/tests/test_fft.py::test_fftshift_identity[shape2-chunks2-2-fftshift-ifftshift] PASSED [ 24%] 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dask/array/tests/test_gufunc.py::test_apply_gufunc_axes_two_kept_coredims PASSED [ 25%] dask/array/tests/test_gufunc.py::test_apply_gufunc_via_numba_01 SKIPPED (could not import 'numba': No module named 'numba') [ 25%] dask/array/tests/test_gufunc.py::test_apply_gufunc_via_numba_02 SKIPPED (could not import 'numba': No module named 'numba') [ 25%] dask/array/tests/test_gufunc.py::test_preserve_meta_type SKIPPED (could not import 'sparse': No module named 'sparse') [ 25%] dask/array/tests/test_gufunc.py::test_apply_gufunc_with_meta PASSED [ 25%] dask/array/tests/test_gufunc.py::test_as_gufunc_with_meta PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr[20-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr[20-10-chunks1-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr[20-10-chunks2-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr[40-10-chunks3-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr[128-2-chunks4-None] PASSED [ 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PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[10-5-chunks0-True-False-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[10-5-chunks1-False-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[10-5-chunks2-True-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[40-5-chunks3-True-False-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[40-5-chunks4-False-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[40-5-chunks5-True-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks6-True-False-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks7-True-False-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks8-True-False-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks9-False-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks10-False-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks11-False-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks12-True-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks13-True-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_uncertain[300-10-chunks14-True-True-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_tsqr_zero_height_chunks PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[20-10-10-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[20-10-chunks1-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[20-10-chunks2-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[40-10-chunks3-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[128-2-chunks4-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[129-2-chunks5-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[130-2-chunks6-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[131-2-chunks7-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[300-10-chunks8-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[300-10-chunks9-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[300-10-chunks10-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[10-5-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[5-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[10-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[10-40-chunks14-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[10-40-chunks15-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[10-40-chunks16-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_sfqr[20-20-10-ValueError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[20-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[20-10-chunks1-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[20-10-chunks2-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[40-10-chunks3-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[128-2-chunks4-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[129-2-chunks5-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[130-2-chunks6-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[131-2-chunks7-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[300-10-chunks8-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[300-10-chunks9-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[300-10-chunks10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[10-5-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[5-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[10-10-10-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[10-40-chunks14-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[10-40-chunks15-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[10-40-chunks16-None] PASSED [ 25%] dask/array/tests/test_linalg.py::test_qr[20-20-10-NotImplementedError] PASSED [ 25%] dask/array/tests/test_linalg.py::test_linalg_consistent_names PASSED [ 25%] dask/array/tests/test_linalg.py::test_dask_svd_self_consistent[10-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_dask_svd_self_consistent[15-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_dask_svd_self_consistent[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_compute[power] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_compute[QR] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed[iterator0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed[iterator1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_dtype_preservation[float32-float32] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_dtype_preservation[float64-float64] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float32-chunks0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float32-chunks1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float32-chunks2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float64-chunks0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float64-chunks1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_dtype_preservation[float64-chunks2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_deterministic PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-5-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-5-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-5-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-5-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-10-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-10-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-10-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-10-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-15-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-15-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-15-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-15-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-20-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-20-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks0-5-20-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-5-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-5-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-5-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-5-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-10-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-10-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-10-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-10-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-15-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-15-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-15-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-15-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-20-5] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-20-15] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_compressed_shapes[chunks1-5-20-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_lu_1 PASSED [ 26%] dask/array/tests/test_linalg.py::test_lu_2[10] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_2[20] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_2[30] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_2[50] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_3[50] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_3[100] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_3[200] SKIPPED (need --runslow option to run) [ 26%] dask/array/tests/test_linalg.py::test_lu_errors PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_vector[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_vector[50-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_vector[70-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix[50-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix[50-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix2[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix2[50-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_matrix2[50-20] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_triangular_errors PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve[50-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_inv[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_inv[50-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_assume_a[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_solve_assume_a[30-6] PASSED [ 26%] dask/array/tests/test_linalg.py::test_cholesky[20-10] PASSED [ 26%] dask/array/tests/test_linalg.py::test_cholesky[12-3] PASSED [ 26%] dask/array/tests/test_linalg.py::test_cholesky[30-3] PASSED [ 26%] dask/array/tests/test_linalg.py::test_cholesky[30-6] PASSED [ 26%] dask/array/tests/test_linalg.py::test_lstsq[20-10-5-False] PASSED [ 26%] dask/array/tests/test_linalg.py::test_lstsq[20-10-5-True] PASSED [ 26%] dask/array/tests/test_linalg.py::test_lstsq[100-10-10-False] PASSED [ 26%] dask/array/tests/test_linalg.py::test_lstsq[100-10-10-True] PASSED [ 26%] dask/array/tests/test_linalg.py::test_no_chunks_svd PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks0-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks0-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks0-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks1-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks1-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks1-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks2-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks2-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f4-chunks2-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks0-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks0-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks0-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks1-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks1-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks1-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks2-shape0] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks2-shape1] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_correction[f8-chunks2-shape2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-f2] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-f4] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-f8] PASSED [ 26%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-f16] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-c8] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-c16] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[True-c32] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-f2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-f4] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-f8] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-f16] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-c8] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-c16] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_flip_sign[False-c32] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape0-chunks0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape0-chunks1] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape0-chunks2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape0-chunks3] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape1-chunks0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape1-chunks1] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape1-chunks2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape1-chunks3] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape2-chunks0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape2-chunks1] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape2-chunks2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_supported_array_shapes[shape2-chunks3] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_incompatible_chunking PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_incompatible_dimensions[0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_incompatible_dimensions[1] PASSED [ 27%] dask/array/tests/test_linalg.py::test_svd_incompatible_dimensions[3] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-None-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-None-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-None-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-None-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-1-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-1-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-1-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-1-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--1-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--1-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--1-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--1-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-inf-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-inf-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-inf-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False-inf-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--inf-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--inf-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--inf-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[False--inf-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-None-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-None-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-None-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-None-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-1-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-1-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-1-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-1-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--1-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--1-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--1-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--1-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-inf-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-inf-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-inf-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True-inf-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--inf-shape0-chunks0-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--inf-shape1-chunks1-0] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--inf-shape2-chunks2-axis2] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_ndim[True--inf-shape3-chunks3-None] PASSED [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-None-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-None-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-None-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-None-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-None-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-1-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-1-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-1-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-1-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-1-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--1-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--1-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--1-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--1-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--1-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-inf-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-inf-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-inf-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-inf-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False-inf-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--inf-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--inf-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--inf-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--inf-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[False--inf-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-None-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-None-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-None-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-None-shape3-chunks3] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-None-shape4-chunks4] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-1-shape0-chunks0] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-1-shape1-chunks1] SKIPPED (need --runslow option to run) [ 27%] dask/array/tests/test_linalg.py::test_norm_any_slice[True-1-shape2-chunks2] SKIPPED (need --runslow option to run) [ 27%] 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dask/array/tests/test_masked.py::test_reductions_allmasked[var-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[var-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[std-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[std-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[min-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[min-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[max-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[max-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[any-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[any-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[all-i8] PASSED [ 29%] dask/array/tests/test_masked.py::test_reductions_allmasked[all-f8] PASSED [ 29%] dask/array/tests/test_masked.py::test_arg_reductions[argmin] PASSED [ 29%] dask/array/tests/test_masked.py::test_arg_reductions[argmax] PASSED [ 29%] dask/array/tests/test_masked.py::test_cumulative PASSED [ 29%] dask/array/tests/test_masked.py::test_accessors PASSED [ 29%] dask/array/tests/test_masked.py::test_masked_array PASSED [ 29%] dask/array/tests/test_masked.py::test_set_fill_value PASSED [ 29%] dask/array/tests/test_masked.py::test_average_weights_with_masked_array[False] PASSED [ 29%] dask/array/tests/test_masked.py::test_average_weights_with_masked_array[True] PASSED [ 29%] dask/array/tests/test_masked.py::test_arithmetic_results_in_masked PASSED [ 29%] dask/array/tests/test_masked.py::test_count PASSED [ 29%] dask/array/tests/test_masked.py::test_like_funcs[ones_like] PASSED [ 30%] dask/array/tests/test_masked.py::test_like_funcs[zeros_like] PASSED [ 30%] dask/array/tests/test_masked.py::test_like_funcs[empty_like] PASSED [ 30%] dask/array/tests/test_numpy_compat.py::test_basic PASSED [ 30%] dask/array/tests/test_numpy_compat.py::test_min_max_round_funcs PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[True-True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[True-True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[True-False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[True-False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[False-True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[False-True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[False-False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem[False-False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[True-True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[True-True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[True-False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[True-False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[False-True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[False-True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[False-False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getitem_lock[False-False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_with_getitem_fusion[True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_with_getitem_fusion[False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_slicing[True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_slicing[False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slice PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slice_with_lists PASSED [ 30%] dask/array/tests/test_optimization.py::test_nonfusible_fancy_indexing PASSED [ 30%] dask/array/tests/test_optimization.py::test_hard_fuse_slice_cases[True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_hard_fuse_slice_cases[False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_fuse_numpy_arrays PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slices_with_alias[True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slices_with_alias[True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slices_with_alias[False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_slices_with_alias[False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_fuse_fancy_indexing_in_getter_nofancy[True-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_fuse_fancy_indexing_in_getter_nofancy[True-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_fuse_fancy_indexing_in_getter_nofancy[False-True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_fuse_fancy_indexing_in_getter_nofancy[False-False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getter_with_asarray[10] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getter_with_asarray[5] PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_getter_with_asarray[3] PASSED [ 30%] dask/array/tests/test_optimization.py::test_remove_no_op_slices_for_getitem[True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_remove_no_op_slices_for_getitem[False] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-True-True-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-True-True-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-True-False-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-True-False-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-False-True-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-False-True-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-False-False-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[True-False-False-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-True-True-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-True-True-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-True-False-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-True-False-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-False-True-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-False-True-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-False-False-getter] PASSED [ 30%] dask/array/tests/test_optimization.py::test_dont_remove_no_op_slices_for_getter_or_getter_nofancy[False-False-False-getter_nofancy] PASSED [ 30%] dask/array/tests/test_optimization.py::test_turn_off_fusion XFAIL (blockwise fusion does not respect this, which is ok) [ 30%] dask/array/tests/test_optimization.py::test_disable_lowlevel_fusion PASSED [ 30%] dask/array/tests/test_optimization.py::test_array_creation_blockwise_fusion PASSED [ 30%] dask/array/tests/test_optimization.py::test_gh3937 PASSED [ 30%] dask/array/tests/test_optimization.py::test_double_dependencies PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_roots PASSED [ 30%] dask/array/tests/test_optimization.py::test_fuse_roots_annotations PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_blockwise_duplicate_dependency[True] PASSED [ 30%] dask/array/tests/test_optimization.py::test_optimize_blockwise_duplicate_dependency[False] PASSED [ 30%] dask/array/tests/test_overlap.py::test_overlap_internal PASSED [ 30%] dask/array/tests/test_overlap.py::test_overlap_internal_asymmetric PASSED [ 30%] dask/array/tests/test_overlap.py::test_overlap_internal_asymmetric_small PASSED [ 30%] dask/array/tests/test_overlap.py::test_trim_internal PASSED [ 30%] dask/array/tests/test_overlap.py::test_periodic PASSED [ 30%] dask/array/tests/test_overlap.py::test_reflect PASSED [ 30%] dask/array/tests/test_overlap.py::test_nearest PASSED [ 30%] dask/array/tests/test_overlap.py::test_constant PASSED [ 30%] dask/array/tests/test_overlap.py::test_boundaries PASSED [ 30%] dask/array/tests/test_overlap.py::test_overlap PASSED [ 30%] dask/array/tests/test_overlap.py::test_overlap_allow_rechunk_kwarg PASSED [ 30%] dask/array/tests/test_overlap.py::test_asymmetric_overlap_boundary_exception PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_escapes_to_map_blocks_when_depth_is_zero PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[None] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[reflect] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[periodic] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[nearest] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[none] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_no_depth[0] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray_defaults PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray_different_depths PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray_uneven_numblocks_exception PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray_block_broadcast PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_multiarray_variadic PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis0] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis1] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis2] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis3] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis4] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis5] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[1] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis7] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis8] PASSED [ 30%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis9] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis10] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis11] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[drop_axis12] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_trim_using_drop_axis_and_different_depths[-2] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_assumes_shape_matches_first_array_if_trim_is_false PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_deprecated_signature PASSED [ 31%] dask/array/tests/test_overlap.py::test_nearest_overlap PASSED [ 31%] dask/array/tests/test_overlap.py::test_different_depths_and_boundary_combinations[depth0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_different_depths_and_boundary_combinations[depth1] PASSED [ 31%] dask/array/tests/test_overlap.py::test_different_depths_and_boundary_combinations[depth2] PASSED [ 31%] dask/array/tests/test_overlap.py::test_different_depths_and_boundary_combinations[depth3] PASSED [ 31%] dask/array/tests/test_overlap.py::test_one_chunk_along_axis PASSED [ 31%] dask/array/tests/test_overlap.py::test_constant_boundaries PASSED [ 31%] dask/array/tests/test_overlap.py::test_depth_greater_than_smallest_chunk_combines_chunks[chunks0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_depth_greater_than_smallest_chunk_combines_chunks[chunks1] PASSED [ 31%] dask/array/tests/test_overlap.py::test_depth_greater_than_dim PASSED [ 31%] dask/array/tests/test_overlap.py::test_none_boundaries PASSED [ 31%] dask/array/tests/test_overlap.py::test_overlap_small PASSED [ 31%] dask/array/tests/test_overlap.py::test_no_shared_keys_with_different_depths PASSED [ 31%] dask/array/tests/test_overlap.py::test_overlap_few_dimensions_small PASSED [ 31%] dask/array/tests/test_overlap.py::test_overlap_few_dimensions PASSED [ 31%] dask/array/tests/test_overlap.py::test_trim_boundary[reflect] PASSED [ 31%] dask/array/tests/test_overlap.py::test_trim_boundary[periodic] PASSED [ 31%] dask/array/tests/test_overlap.py::test_trim_boundary[nearest] PASSED [ 31%] dask/array/tests/test_overlap.py::test_trim_boundary[none] PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_rechunks_array_if_needed PASSED [ 31%] dask/array/tests/test_overlap.py::test_map_overlap_rechunks_array_along_multiple_dims_if_needed PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks0-expected0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks1-expected1] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks2-expected2] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks3-expected3] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks4-expected4] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks5-expected5] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks6-expected6] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize[chunks7-expected7] PASSED [ 31%] dask/array/tests/test_overlap.py::test_ensure_minimum_chunksize_raises_error PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape0-chunks0-window_shape0-axis0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape1-5-window_shape1-axis1] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape2-3-window_shape2-axis2] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape3-3-3-0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape4-3-3--1] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape5-3-3-None] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape6-3-window_shape6-None] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape7-3-window_shape7-axis7] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape8-3-window_shape8-axis8] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_view[shape9-3-window_shape9-axis9] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[window_shape0-0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[window_shape1-3] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[-1-0] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[2-axis3] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[2-None] PASSED [ 31%] dask/array/tests/test_overlap.py::test_sliding_window_errors[0-None] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentile[tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentile[dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentile_with_categoricals SKIPPED (unconditional skip) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_empty_arrays[tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_empty_arrays[dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_empty_q[tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_empty_q[dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5-tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5-dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5.00-tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5.00-dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[q2-tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[q2-dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5.01-tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_percentiles_with_scaler_percentile[5.01-dask] PASSED [ 31%] dask/array/tests/test_percentiles.py::test_unknown_chunk_sizes[tdigest] SKIPPED (Requires crick) [ 31%] dask/array/tests/test_percentiles.py::test_unknown_chunk_sizes[dask] PASSED [ 31%] dask/array/tests/test_random.py::test_RandomState PASSED [ 31%] dask/array/tests/test_random.py::test_concurrency PASSED [ 31%] dask/array/tests/test_random.py::test_doc_randomstate PASSED [ 31%] dask/array/tests/test_random.py::test_serializability PASSED [ 31%] dask/array/tests/test_random.py::test_determinisim_through_dask_values PASSED [ 31%] dask/array/tests/test_random.py::test_randomstate_consistent_names PASSED [ 31%] dask/array/tests/test_random.py::test_random PASSED [ 31%] dask/array/tests/test_random.py::test_parametrized_random_function PASSED [ 31%] dask/array/tests/test_random.py::test_kwargs PASSED [ 31%] dask/array/tests/test_random.py::test_unique_names PASSED [ 31%] dask/array/tests/test_random.py::test_docs PASSED [ 31%] dask/array/tests/test_random.py::test_can_make_really_big_random_array PASSED [ 31%] dask/array/tests/test_random.py::test_random_seed PASSED [ 31%] dask/array/tests/test_random.py::test_consistent_across_sizes PASSED [ 31%] dask/array/tests/test_random.py::test_random_all PASSED [ 31%] dask/array/tests/test_random.py::test_array_broadcasting PASSED [ 31%] dask/array/tests/test_random.py::test_multinomial PASSED [ 31%] dask/array/tests/test_random.py::test_choice PASSED [ 31%] dask/array/tests/test_random.py::test_create_with_auto_dimensions PASSED [ 31%] dask/array/tests/test_random.py::test_names PASSED [ 31%] dask/array/tests/test_random.py::test_permutation PASSED [ 31%] dask/array/tests/test_random.py::test_external_randomstate_class SKIPPED (could not import 'randomgen': No module named 'randomgen') [ 31%] dask/array/tests/test_random.py::test_auto_chunks PASSED [ 31%] dask/array/tests/test_random.py::test_randint_dtype PASSED [ 31%] dask/array/tests/test_random.py::test_raises_bad_kwarg PASSED [ 31%] dask/array/tests/test_random.py::test_randomstate_kwargs SKIPPED (could not import 'cupy': No module named 'cupy') [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_internals_1 PASSED [ 31%] dask/array/tests/test_rechunk.py::test_intersect_1 PASSED [ 31%] dask/array/tests/test_rechunk.py::test_intersect_2 PASSED [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_1d PASSED [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_2d PASSED [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_4d PASSED [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_expand PASSED [ 31%] dask/array/tests/test_rechunk.py::test_rechunk_expand2 PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_method PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_blockshape PASSED [ 32%] dask/array/tests/test_rechunk.py::test_dtype PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_with_dict PASSED [ 32%] 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PASSED [ 32%] dask/array/tests/test_rechunk.py::test_intersect_nan_long PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown_from_pandas PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown_from_array PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x0-chunks0] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x1-chunks1] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x2-chunks2] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x3-chunks3] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x4-chunks4] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x5-chunks5] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x6-chunks6] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x7-chunks7] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x8-chunks8] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x9-chunks9] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x10-chunks10] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown[x11-chunks11] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown_explicit PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_unknown_raises PASSED [ 32%] dask/array/tests/test_rechunk.py::test_old_to_new_single PASSED [ 32%] dask/array/tests/test_rechunk.py::test_old_to_new PASSED [ 32%] dask/array/tests/test_rechunk.py::test_old_to_new_large PASSED [ 32%] dask/array/tests/test_rechunk.py::test_changing_raises PASSED [ 32%] dask/array/tests/test_rechunk.py::test_old_to_new_known PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_zero_dim PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_empty_chunks PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_avoid_needless_chunking PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_1d[100-1-10-expected0] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_1d[100-50-10-expected1] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_1d[100-100-10-expected2] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_1d[20-7-10-expected3] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_1d[20-chunks4-5-expected4] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_2d PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_3d PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_image_stack[100] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_auto_image_stack[1000] PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_down PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_zero PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_bad_keys PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_basics PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_chunks_unchanged PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_small PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_n_chunks_size PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_raises PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_basics_2d PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_2d_negative_dimension PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_different_inputs PASSED [ 32%] dask/array/tests/test_rechunk.py::test_balance_split_into_n_chunks PASSED [ 32%] dask/array/tests/test_rechunk.py::test_rechunk_with_zero PASSED [ 32%] dask/array/tests/test_rechunk.py::test_intersect_chunks_with_nonzero PASSED [ 32%] dask/array/tests/test_rechunk.py::test_intersect_chunks_with_zero PASSED [ 32%] dask/array/tests/test_rechunk.py::test_old_to_new_with_zero PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[True-True-f4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[True-True-i4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[True-False-f4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[True-False-i4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[False-True-f4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[False-True-i4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[False-False-f4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_numel[False-False-i4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_reductions_0D PASSED [ 32%] dask/array/tests/test_reductions.py::test_reductions_1D[f4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_reductions_1D[i4] PASSED [ 32%] dask/array/tests/test_reductions.py::test_reduction_errors PASSED [ 32%] dask/array/tests/test_reductions.py::test_reductions_2D[f4] SKIPPED (need --runslow option to run) [ 32%] dask/array/tests/test_reductions.py::test_reductions_2D[i4] SKIPPED (need --runslow option to run) [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions[argmin-argmin] PASSED [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions[argmax-argmax] PASSED [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions[nanargmin-nanargmin] PASSED [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions[nanargmax-nanargmax] PASSED [ 32%] dask/array/tests/test_reductions.py::test_nanarg_reductions[nanargmin-nanargmin] PASSED [ 32%] dask/array/tests/test_reductions.py::test_nanarg_reductions[nanargmax-nanargmax] PASSED [ 32%] dask/array/tests/test_reductions.py::test_min_max_empty_chunks[min-amin] PASSED [ 32%] dask/array/tests/test_reductions.py::test_min_max_empty_chunks[max-amax] PASSED [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_chunksize[argmax] PASSED [ 32%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_chunksize[nanargmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_chunksize_2d[argmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_chunksize_2d[nanargmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_single_chunksize[argmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_arg_reductions_unknown_single_chunksize[nanargmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_reductions_2D_nans PASSED [ 33%] dask/array/tests/test_reductions.py::test_moment PASSED [ 33%] dask/array/tests/test_reductions.py::test_reductions_with_negative_axes PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[nansum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[sum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[nanmin] PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[min] PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[nanmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_nan_object[max] PASSED [ 33%] dask/array/tests/test_reductions.py::test_0d_array PASSED [ 33%] dask/array/tests/test_reductions.py::test_reduction_on_scalar PASSED [ 33%] dask/array/tests/test_reductions.py::test_reductions_with_empty_array PASSED [ 33%] dask/array/tests/test_reductions.py::test_tree_reduce_depth PASSED [ 33%] dask/array/tests/test_reductions.py::test_tree_reduce_set_options PASSED [ 33%] dask/array/tests/test_reductions.py::test_reduction_names PASSED [ 33%] dask/array/tests/test_reductions.py::test_general_reduction_names PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_reduction_out[sum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_reduction_out[argmax] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-None-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-0-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential-1-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[sequential--1-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-None-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-0-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch-1-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-False-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-False-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-False-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-False-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-True-cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-True-cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-True-nancumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_axis[blelloch--1-True-nancumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_out[cumsum] PASSED [ 33%] dask/array/tests/test_reductions.py::test_array_cumreduction_out[cumprod] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[None-sort-topk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[None-argsort-argtopk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[2-sort-topk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[2-argsort-argtopk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[4-sort-topk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[4-argsort-argtopk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[8-sort-topk] PASSED [ 33%] dask/array/tests/test_reductions.py::test_topk_argtopk1[8-argsort-argtopk] PASSED [ 33%] 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dask/array/tests/test_reductions.py::test_regres_3940[sequential-nansum] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[sequential-nanmax] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-cumsum] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-cumprod] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-argmin] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-argmax] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-min] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-max] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-nansum] PASSED [ 34%] dask/array/tests/test_reductions.py::test_regres_3940[blelloch-nanmax] PASSED [ 34%] dask/array/tests/test_reductions.py::test_trace PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-0-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-0-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-axis1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-axis1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True-1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True--1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[True--1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-0-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-0-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-axis1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-axis1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False-1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False--1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median[False--1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[0-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[0-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[axis1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[axis1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[1-median] PASSED [ 34%] dask/array/tests/test_reductions.py::test_median_does_not_rechunk_if_whole_axis_in_one_chunk[1-nanmedian] PASSED [ 34%] dask/array/tests/test_reductions.py::test_object_reduction[sum] PASSED [ 34%] dask/array/tests/test_reductions.py::test_object_reduction[mean] PASSED [ 34%] dask/array/tests/test_reductions.py::test_object_reduction[prod] PASSED [ 34%] dask/array/tests/test_reductions.py::test_empty_chunk_nanmin_nanmax[nanmin] PASSED [ 34%] dask/array/tests/test_reductions.py::test_empty_chunk_nanmin_nanmax[nanmax] PASSED [ 34%] dask/array/tests/test_reductions.py::test_empty_chunk_nanmin_nanmax_raise[nanmin] PASSED [ 34%] dask/array/tests/test_reductions.py::test_empty_chunk_nanmin_nanmax_raise[nanmax] PASSED [ 34%] dask/array/tests/test_reductions.py::test_mean_func_does_not_warn PASSED [ 34%] dask/array/tests/test_reductions.py::test_nan_func_does_not_warn[nanvar] PASSED [ 34%] dask/array/tests/test_reductions.py::test_nan_func_does_not_warn[nanstd] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks0] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks1] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks2] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks3] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks4] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-2-chunks5] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks0] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks1] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks2] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks3] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks4] PASSED [ 34%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes0-4-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-2-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes1-4-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-2-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes2-4-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-2-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes3-4-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks0] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks1] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks2] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks3] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks4] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-2-chunks5] PASSED [ 35%] dask/array/tests/test_reductions.py::test_chunk_structure_independence[axes4-4-chunks0] PASSED [ 35%] 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PASSED [ 38%] dask/array/tests/test_routines.py::test_vdot[shape0-chunks0] PASSED [ 38%] dask/array/tests/test_routines.py::test_vdot[shape1-chunks1] PASSED [ 38%] dask/array/tests/test_routines.py::test_outer[shape10-shape20] PASSED [ 38%] dask/array/tests/test_routines.py::test_outer[shape11-shape21] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-ndim--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-sum--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-range--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-range2--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape0-0-cumsum--True] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-ndim--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-sum--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-range--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-range2--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape1-1-cumsum--True] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-ndim--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-sum--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-range--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-range2--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape2-2-cumsum--True] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-ndim--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-sum--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-range--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-range2--False] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_along_axis[input_shape3--1-cumsum--True] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-sum0-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-sum1-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape0-axes0-range-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-sum0-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-sum1-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape1-0-range-] PASSED [ 38%] dask/array/tests/test_routines.py::test_apply_over_axes[shape2-axes2-sum0-] PASSED [ 38%] 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dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape3-elements_chunks3-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[True-test_shape3-test_chunks3-elements_shape3-elements_chunks3-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape0-elements_chunks0-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape0-elements_chunks0-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape1-elements_chunks1-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape1-elements_chunks1-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape2-elements_chunks2-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape2-elements_chunks2-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape3-elements_chunks3-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape0-test_chunks0-elements_shape3-elements_chunks3-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape0-elements_chunks0-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape0-elements_chunks0-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape1-elements_chunks1-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape1-elements_chunks1-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape2-elements_chunks2-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape2-elements_chunks2-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape3-elements_chunks3-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape1-test_chunks1-elements_shape3-elements_chunks3-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape0-elements_chunks0-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape0-elements_chunks0-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape1-elements_chunks1-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape1-elements_chunks1-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape2-elements_chunks2-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape2-elements_chunks2-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape3-elements_chunks3-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape2-test_chunks2-elements_shape3-elements_chunks3-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape0-elements_chunks0-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape0-elements_chunks0-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape1-elements_chunks1-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape1-elements_chunks1-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape2-elements_chunks2-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape2-elements_chunks2-0-10-796] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape3-elements_chunks3-0-10-23] PASSED [ 40%] dask/array/tests/test_routines.py::test_isin_rand[False-test_shape3-test_chunks3-elements_shape3-elements_chunks3-0-10-796] PASSED [ 41%] dask/array/tests/test_routines.py::test_isin_assume_unique[True] PASSED [ 41%] dask/array/tests/test_routines.py::test_isin_assume_unique[False] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[None-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[0-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[1-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[-1-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis4-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-7-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-7-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-9-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-9-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-shift3-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-shift3-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-shift4-chunks0] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll[axis5-shift4-chunks1] PASSED [ 41%] dask/array/tests/test_routines.py::test_roll_always_results_in_a_new_array PASSED [ 41%] dask/array/tests/test_routines.py::test_roll_works_even_if_shape_is_0 PASSED [ 41%] dask/array/tests/test_routines.py::test_shape_and_ndim[shape0] PASSED [ 41%] dask/array/tests/test_routines.py::test_shape_and_ndim[shape1] PASSED [ 41%] dask/array/tests/test_routines.py::test_shape_and_ndim[shape2] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[True-shape0] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[True-shape1] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[True-shape2] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[False-shape0] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[False-shape1] PASSED [ 41%] dask/array/tests/test_routines.py::test_union1d[False-shape2] PASSED [ 41%] dask/array/tests/test_routines.py::test_ravel PASSED [ 41%] dask/array/tests/test_routines.py::test_ravel_1D_no_op PASSED [ 41%] dask/array/tests/test_routines.py::test_ravel_with_array_like PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[None] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[0] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[1] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[-1] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[axis4] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[axis5] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[axis6] PASSED [ 41%] dask/array/tests/test_routines.py::test_expand_dims[2] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[None-True] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[None-False] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[0-True] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[0-False] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[-1-True] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[-1-False] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[axis3-True] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze[axis3-False] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze_1d_array[shape0] PASSED [ 41%] dask/array/tests/test_routines.py::test_squeeze_1d_array[shape1] PASSED [ 41%] dask/array/tests/test_routines.py::test_vstack PASSED [ 41%] dask/array/tests/test_routines.py::test_hstack PASSED [ 41%] dask/array/tests/test_routines.py::test_dstack PASSED [ 41%] dask/array/tests/test_routines.py::test_stack_unknown_chunk_sizes[hstack-hstack-0] PASSED [ 41%] dask/array/tests/test_routines.py::test_stack_unknown_chunk_sizes[dstack-dstack-1] PASSED [ 41%] dask/array/tests/test_routines.py::test_stack_unknown_chunk_sizes[vstack-vstack-2] PASSED [ 41%] dask/array/tests/test_routines.py::test_take PASSED [ 41%] dask/array/tests/test_routines.py::test_take_dask_from_numpy PASSED [ 41%] dask/array/tests/test_routines.py::test_compress PASSED [ 41%] dask/array/tests/test_routines.py::test_extract PASSED [ 42%] dask/array/tests/test_routines.py::test_isnull PASSED [ 42%] dask/array/tests/test_routines.py::test_isnull_result_is_an_array PASSED [ 42%] dask/array/tests/test_routines.py::test_isclose PASSED [ 42%] dask/array/tests/test_routines.py::test_allclose PASSED [ 42%] dask/array/tests/test_routines.py::test_choose PASSED [ 42%] dask/array/tests/test_routines.py::test_piecewise PASSED [ 42%] dask/array/tests/test_routines.py::test_piecewise_otherwise PASSED [ 42%] dask/array/tests/test_routines.py::test_select PASSED [ 42%] dask/array/tests/test_routines.py::test_select_multidimension PASSED [ 42%] dask/array/tests/test_routines.py::test_select_return_dtype PASSED [ 42%] dask/array/tests/test_routines.py::test_select_broadcasting XFAIL (broadcasting in da.select() not implemented yet) [ 42%] dask/array/tests/test_routines.py::test_argwhere PASSED [ 42%] dask/array/tests/test_routines.py::test_argwhere_obj PASSED [ 42%] dask/array/tests/test_routines.py::test_argwhere_str PASSED [ 42%] dask/array/tests/test_routines.py::test_where PASSED [ 42%] dask/array/tests/test_routines.py::test_where_scalar_dtype PASSED [ 42%] dask/array/tests/test_routines.py::test_where_bool_optimization PASSED [ 42%] dask/array/tests/test_routines.py::test_where_nonzero PASSED [ 42%] dask/array/tests/test_routines.py::test_where_incorrect_args PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_axis[None] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_axis[0] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_axis[axis2] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_axis[axis3] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_obj PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_obj_axis[None] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_obj_axis[0] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_obj_axis[axis2] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_obj_axis[axis3] PASSED [ 42%] dask/array/tests/test_routines.py::test_count_nonzero_str PASSED [ 42%] dask/array/tests/test_routines.py::test_flatnonzero PASSED [ 42%] dask/array/tests/test_routines.py::test_nonzero PASSED [ 42%] dask/array/tests/test_routines.py::test_nonzero_method PASSED [ 42%] dask/array/tests/test_routines.py::test_unravel_index_empty PASSED [ 42%] dask/array/tests/test_routines.py::test_unravel_index PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr0-chunks0-kwargs0-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr0-chunks0-kwargs0-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr0-chunks0-kwargs0-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr0-chunks0-kwargs0-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr0-chunks0-kwargs0-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr1-chunks1-kwargs1-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr1-chunks1-kwargs1-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr1-chunks1-kwargs1-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr1-chunks1-kwargs1-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr1-chunks1-kwargs1-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr2-1-kwargs2-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr2-1-kwargs2-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr2-1-kwargs2-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr2-1-kwargs2-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr2-1-kwargs2-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr3-chunks3-kwargs3-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr3-chunks3-kwargs3-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr3-chunks3-kwargs3-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr3-chunks3-kwargs3-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr3-chunks3-kwargs3-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr4-chunks4-kwargs4-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr4-chunks4-kwargs4-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr4-chunks4-kwargs4-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr4-chunks4-kwargs4-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr4-chunks4-kwargs4-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr5-chunks5-kwargs5-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr5-chunks5-kwargs5-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr5-chunks5-kwargs5-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr5-chunks5-kwargs5-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr5-chunks5-kwargs5-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr6-chunks6-kwargs6-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr6-chunks6-kwargs6-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr6-chunks6-kwargs6-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr6-chunks6-kwargs6-asarray] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr6-chunks6-kwargs6-from_array] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr7-None-kwargs7-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr7-None-kwargs7-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr7-None-kwargs7-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr7-None-kwargs7-asarray] SKIPPED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr7-None-kwargs7-from_array] SKIPPED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr8-None-kwargs8-0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr8-None-kwargs8-1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr8-None-kwargs8-2] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr8-None-kwargs8-asarray] SKIPPED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index[arr8-None-kwargs8-from_array] SKIPPED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_unknown_shape PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_unknown_shape_fails PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_delayed_dims[False-dims0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_delayed_dims[False-dims1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_delayed_dims[True-dims0] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_delayed_dims[True-dims1] PASSED [ 42%] dask/array/tests/test_routines.py::test_ravel_multi_index_non_int_dtype PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_with_excess PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks0] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks1] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks2] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks3] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks4] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks5] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks6] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks7] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks8] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks9] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks10] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks11] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks12] PASSED [ 42%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks13] PASSED [ 43%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks14] PASSED [ 43%] dask/array/tests/test_routines.py::test_coarsen_bad_chunks[chunks15] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks0-1] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks1-2] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks2-2] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks3-10] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks4-10] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks5-8] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks6-10] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks7-16] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks8-10] PASSED [ 43%] dask/array/tests/test_routines.py::test_aligned_coarsen_chunks[chunks9-4] PASSED [ 43%] dask/array/tests/test_routines.py::test_insert PASSED [ 43%] dask/array/tests/test_routines.py::test_append PASSED [ 43%] dask/array/tests/test_routines.py::test_multi_insert PASSED [ 43%] dask/array/tests/test_routines.py::test_delete PASSED [ 43%] dask/array/tests/test_routines.py::test_result_type PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[abc,bad->abcd] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[abcdef,bcdfg->abcdeg] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ea,fb,abcd,gc,hd->efgh] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ab,b] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[aa] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a,a->] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a,a->a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a,a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a,b] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a,b,c] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ba,b] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ba,b->] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[defab,fedbc->defac] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ab...,bc...->ac...] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a...a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[abc...->cba...] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[...ab->...a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[a...a->a...] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[...abc,...abcd->...d] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ab...,b->ab...] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[aa->a] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[ab,ab,c->c] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[aab,bc->ac] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[aab,bcc->ac] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[fdf,cdd,ccd,afe->ae] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum[fff,fae,bef,def->abd] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_optimize[optimize_opts0] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_optimize[optimize_opts1] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_optimize[optimize_opts2] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_order[C] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_order[F] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_order[A] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_order[K] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_casting[no] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_casting[equiv] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_casting[safe] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_casting[same_kind] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_casting[unsafe] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_split_every[None] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_split_every[2] PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_invalid_args PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_broadcasting_contraction PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_broadcasting_contraction2 PASSED [ 43%] dask/array/tests/test_routines.py::test_einsum_broadcasting_contraction3 PASSED [ 43%] dask/array/tests/test_routines.py::test_average[True-a0] PASSED [ 43%] dask/array/tests/test_routines.py::test_average[True-a1] PASSED [ 43%] dask/array/tests/test_routines.py::test_average[False-a0] PASSED [ 43%] dask/array/tests/test_routines.py::test_average[False-a1] PASSED [ 43%] dask/array/tests/test_routines.py::test_average_keepdims[a0] PASSED [ 43%] dask/array/tests/test_routines.py::test_average_keepdims[a1] PASSED [ 43%] dask/array/tests/test_routines.py::test_average_weights[False] PASSED [ 43%] dask/array/tests/test_routines.py::test_average_weights[True] PASSED [ 43%] dask/array/tests/test_routines.py::test_average_raises PASSED [ 43%] dask/array/tests/test_routines.py::test_iscomplexobj PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_ndims PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu_non_square_arrays PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu_indices[3-0-3-auto] PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu_indices[3-1-3-auto] PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu_indices[3--1-3-auto] PASSED [ 43%] dask/array/tests/test_routines.py::test_tril_triu_indices[5-0-5-1] PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_1d PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_singleton_value_on_boundary PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_array_1d PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_array_2d PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_optimizations PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_with_singleton_indices PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_with_newaxis PASSED [ 43%] dask/array/tests/test_slicing.py::test_take PASSED [ 43%] dask/array/tests/test_slicing.py::test_take_sorted PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_chunks PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_with_numpy_arrays PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_and_chunks PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_and_unknown_chunks PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_identities PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_stop_0 PASSED [ 43%] dask/array/tests/test_slicing.py::test_slice_list_then_None PASSED [ 43%] dask/array/tests/test_slicing.py::test_slicing_exhaustively SKIPPED (really long test) [ 43%] dask/array/tests/test_slicing.py::test_slicing_with_negative_step_flops_keys PASSED [ 43%] dask/array/tests/test_slicing.py::test_empty_slice PASSED [ 43%] dask/array/tests/test_slicing.py::test_multiple_list_slicing PASSED [ 43%] dask/array/tests/test_slicing.py::test_boolean_list_slicing PASSED [ 43%] dask/array/tests/test_slicing.py::test_boolean_numpy_array_slicing PASSED [ 43%] dask/array/tests/test_slicing.py::test_empty_list PASSED [ 43%] dask/array/tests/test_slicing.py::test_uneven_chunks PASSED [ 43%] dask/array/tests/test_slicing.py::test_new_blockdim PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_consistent_names PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_consistent_names_after_normalization PASSED [ 44%] dask/array/tests/test_slicing.py::test_sanitize_index_element PASSED [ 44%] dask/array/tests/test_slicing.py::test_sanitize_index PASSED [ 44%] dask/array/tests/test_slicing.py::test_uneven_blockdims PASSED [ 44%] dask/array/tests/test_slicing.py::test_oob_check PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[None-None] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[None-3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[None-2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[None-1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks1-None] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks1-3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks1-2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks1-1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks2-None] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks2-3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks2-2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks2-1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks3-None] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks3-3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks3-2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks3-1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks4-None] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks4-3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks4-2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array[x_chunks4-1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_0d[1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_0d[2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_0d[3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nanchunks[1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nanchunks[2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nanchunks[3] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nanchunks[4] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nanchunks[5] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_negindex[2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_negindex[4] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_indexerror[2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_indexerror[4] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[int8] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[int16] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[int32] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[int64] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[uint8] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[uint16] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[uint32] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_dtypes[uint64] PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_int_dask_array_nocompute PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_bool_dask_array PASSED [ 44%] dask/array/tests/test_slicing.py::test_index_with_bool_dask_array_2 PASSED [ 44%] dask/array/tests/test_slicing.py::test_cull XFAIL [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index0-shape0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index0-shape1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index0-shape2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index1-shape0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index1-shape1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index1-shape2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index2-shape0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index2-shape1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index2-shape2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index3-shape0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index3-shape1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_with_Nones[index3-shape2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_integer_no_warnings PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_none_int_ellipes SKIPPED (need --runslow option to run) [ 44%] dask/array/tests/test_slicing.py::test_None_overlap_int PASSED [ 44%] dask/array/tests/test_slicing.py::test_negative_n_slicing PASSED [ 44%] dask/array/tests/test_slicing.py::test_negative_list_slicing PASSED [ 44%] dask/array/tests/test_slicing.py::test_permit_oob_slices PASSED [ 44%] dask/array/tests/test_slicing.py::test_normalize_index PASSED [ 44%] dask/array/tests/test_slicing.py::test_take_semi_sorted PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_plan[chunks0-index0-expected0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_plan[chunks1-index1-expected1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slicing_plan[chunks2-index2-expected2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_getitem_avoids_large_chunks PASSED [ 44%] dask/array/tests/test_slicing.py::test_getitem_avoids_large_chunks_missing PASSED [ 44%] dask/array/tests/test_slicing.py::test_take_avoids_large_chunks PASSED [ 44%] dask/array/tests/test_slicing.py::test_take_uses_config PASSED [ 44%] dask/array/tests/test_slicing.py::test_pathological_unsorted_slicing PASSED [ 44%] dask/array/tests/test_slicing.py::test_setitem_with_different_chunks_preserves_shape[params0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_setitem_with_different_chunks_preserves_shape[params1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh3579 PASSED [ 44%] dask/array/tests/test_slicing.py::test_make_blockwise_sorted_slice PASSED [ 44%] dask/array/tests/test_slicing.py::test_shuffle_slice[size0-chunks0] PASSED [ 44%] dask/array/tests/test_slicing.py::test_shuffle_slice[size1-chunks1] PASSED [ 44%] dask/array/tests/test_slicing.py::test_shuffle_slice[size2-chunks2] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[True-True-True] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[True-True-False] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[True-False-True] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[True-False-False] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[False-True-True] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[False-True-False] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[False-False-True] PASSED [ 44%] dask/array/tests/test_slicing.py::test_gh4043[False-False-False] PASSED [ 44%] dask/array/tests/test_slicing.py::test_slice_array_3d_with_bool_numpy_array PASSED [ 44%] dask/array/tests/test_slicing.py::test_slice_array_null_dimension PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[True-skew-kwargs0] PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[True-kurtosis-kwargs1] PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[True-kurtosis-kwargs2] PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[False-skew-kwargs0] PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[False-kurtosis-kwargs1] PASSED [ 44%] dask/array/tests/test_stats.py::test_measures[False-kurtosis-kwargs2] PASSED [ 44%] dask/array/tests/test_stats.py::test_bias_raises PASSED [ 44%] dask/array/tests/test_stats.py::test_one[chisquare] PASSED [ 45%] dask/array/tests/test_stats.py::test_one[power_divergence] PASSED [ 45%] dask/array/tests/test_stats.py::test_one[normaltest] PASSED [ 45%] dask/array/tests/test_stats.py::test_one[skewtest] PASSED [ 45%] dask/array/tests/test_stats.py::test_one[kurtosistest] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[ttest_ind-kwargs0] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[ttest_ind-kwargs1] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[ttest_1samp-kwargs2] XFAIL (https://github.com/dask/dask/issues/9499) [ 45%] dask/array/tests/test_stats.py::test_two[ttest_rel-kwargs3] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[chisquare-kwargs4] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[power_divergence-kwargs5] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[power_divergence-kwargs6] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[power_divergence-kwargs7] PASSED [ 45%] dask/array/tests/test_stats.py::test_two[power_divergence-kwargs8] PASSED [ 45%] dask/array/tests/test_stats.py::test_moments[0] PASSED [ 45%] dask/array/tests/test_stats.py::test_moments[1] PASSED [ 45%] dask/array/tests/test_stats.py::test_moments[2] PASSED [ 45%] dask/array/tests/test_stats.py::test_moments[3] PASSED [ 45%] dask/array/tests/test_stats.py::test_moments[4] PASSED [ 45%] dask/array/tests/test_stats.py::test_anova PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-ttest_1samp-2] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-ttest_rel-2] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-skewtest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-kurtosis-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-kurtosistest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-normaltest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[omit-moment-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-ttest_1samp-2] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-ttest_rel-2] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-skewtest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-kurtosis-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-kurtosistest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-normaltest-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_nan_raises[raise-moment-1] PASSED [ 45%] dask/array/tests/test_stats.py::test_power_divergence_invalid PASSED [ 45%] dask/array/tests/test_stats.py::test_skew_raises PASSED [ 45%] dask/array/tests/test_stats.py::test_skew_single_return_type PASSED [ 45%] dask/array/tests/test_stats.py::test_kurtosis_single_return_type PASSED [ 45%] dask/array/tests/test_svg.py::test_basic PASSED [ 45%] dask/array/tests/test_svg.py::test_repr_html PASSED [ 45%] dask/array/tests/test_svg.py::test_errors PASSED [ 45%] dask/array/tests/test_svg.py::test_repr_html_size_units PASSED [ 45%] dask/array/tests/test_svg.py::test_draw_sizes PASSED [ 45%] dask/array/tests/test_svg.py::test_too_many_lines_fills_sides_darker PASSED [ 45%] dask/array/tests/test_svg.py::test_3d PASSED [ 45%] dask/array/tests/test_testing.py::test_assert_eq_checks_scalars PASSED [ 45%] dask/array/tests/test_ufunc.py::test_ufunc_meta[log] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_ufunc_meta[modf] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_ufunc_meta[frexp] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_ufunc PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[abs] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[absolute] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arccos] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arccosh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arcsin] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arcsinh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arctan] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[arctanh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[bitwise_not] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[cbrt] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[ceil] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[conj] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[cos] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[cosh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[deg2rad] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[degrees] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[exp] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[exp2] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[expm1] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[fabs] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[fix] SKIPPED (fix calls floor in a way that we do not yet support) [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[floor] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[invert] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[isfinite] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[isinf] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[isnan] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[log] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[log10] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[log1p] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[log2] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[logical_not] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[negative] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[positive] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[rad2deg] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[radians] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[reciprocal] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[rint] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[sign] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[signbit] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[sin] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[sinh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[spacing] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[sqrt] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[square] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[tan] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[tanh] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_unary_ufunc[trunc] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[add] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[arctan2] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[copysign] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[divide] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[equal] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[bitwise_and] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[bitwise_or] PASSED [ 45%] dask/array/tests/test_ufunc.py::test_binary_ufunc[bitwise_xor] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[floor_divide] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[fmax] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[fmin] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[fmod] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[greater] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[greater_equal] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[hypot] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[ldexp] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[left_shift] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[less] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[less_equal] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[logaddexp] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[logaddexp2] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[logical_and] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[logical_or] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[logical_xor] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[maximum] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[minimum] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[mod] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[multiply] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[nextafter] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[not_equal] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[power] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[remainder] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[right_shift] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[subtract] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[true_divide] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_binary_ufunc[float_power] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_outer PASSED [ 46%] dask/array/tests/test_ufunc.py::test_complex[isreal] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_complex[iscomplex] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_complex[real] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_complex[imag] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_2results[frexp] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_2results[modf] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_clip PASSED [ 46%] dask/array/tests/test_ufunc.py::test_angle PASSED [ 46%] dask/array/tests/test_ufunc.py::test_issignedinf PASSED [ 46%] dask/array/tests/test_ufunc.py::test_non_ufunc_others[i0] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_non_ufunc_others[sinc] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_non_ufunc_others[nan_to_num] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_frompyfunc PASSED [ 46%] dask/array/tests/test_ufunc.py::test_frompyfunc_wrapper PASSED [ 46%] dask/array/tests/test_ufunc.py::test_array_ufunc PASSED [ 46%] dask/array/tests/test_ufunc.py::test_array_ufunc_binop PASSED [ 46%] dask/array/tests/test_ufunc.py::test_array_ufunc_out PASSED [ 46%] dask/array/tests/test_ufunc.py::test_unsupported_ufunc_methods PASSED [ 46%] dask/array/tests/test_ufunc.py::test_out_numpy PASSED [ 46%] dask/array/tests/test_ufunc.py::test_out_shape_mismatch PASSED [ 46%] dask/array/tests/test_ufunc.py::test_divmod PASSED [ 46%] dask/array/tests/test_ufunc.py::test_dtype_kwarg[float64] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_dtype_kwarg[float32] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_dtype_kwarg[int32] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_dtype_kwarg[int64] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-False-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-False-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-False-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-False-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-True-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-True-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-True-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[True-True-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-False-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-False-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-False-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-False-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-True-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-True-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-True-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[False-True-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-False-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-False-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-False-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-False-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-True-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-True-False-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-True-True-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[numpy-True-True-f8] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[dask-False-False-None] PASSED [ 46%] dask/array/tests/test_ufunc.py::test_ufunc_where[dask-False-False-f8] PASSED [ 46%] 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dask/bag/tests/test_random.py::test_sample_with_more_bag_partitons PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_size_exactly_k PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_k_bigger_than_bag_size PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_empty_partition PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_size_k_bigger_than_smallest_partition_size PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_k_equal_bag_size_with_unbalanced_partitions PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_k_larger_than_partitions PASSED [ 48%] dask/bag/tests/test_random.py::test_weighted_sampling_without_replacement PASSED [ 48%] dask/bag/tests/test_random.py::test_sample_return_bag PASSED [ 48%] dask/bag/tests/test_random.py::test_partitions_are_coerced_to_lists PASSED [ 48%] dask/bag/tests/test_random.py::test_reservoir_sample_map_partitions_correctness PASSED [ 48%] dask/bag/tests/test_random.py::test_reservoir_sample_with_replacement_map_partitions_correctness PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[None-None-ascii-True] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[None-None-ascii-False] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[None-None-utf-8-True] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[None-None-utf-8-False] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[zip-None-ascii-True] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[zip-None-ascii-False] PASSED [ 48%] dask/bag/tests/test_text.py::test_read_text[zip-None-utf-8-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[zip-None-utf-8-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[bz2-None-ascii-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[bz2-None-ascii-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[bz2-None-utf-8-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[bz2-None-utf-8-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[gzip-None-ascii-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[gzip-None-ascii-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[gzip-None-utf-8-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[gzip-None-utf-8-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[lzma-None-ascii-True] SKIPPED (compress function not provided for lzma) [ 49%] dask/bag/tests/test_text.py::test_read_text[lzma-None-ascii-False] SKIPPED (compress function not provided for lzma) [ 49%] dask/bag/tests/test_text.py::test_read_text[lzma-None-utf-8-True] SKIPPED (compress function not provided for lzma) [ 49%] dask/bag/tests/test_text.py::test_read_text[lzma-None-utf-8-False] SKIPPED (compress function not provided for lzma) [ 49%] dask/bag/tests/test_text.py::test_read_text[xz-None-ascii-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[xz-None-ascii-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[xz-None-utf-8-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[xz-None-utf-8-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[snappy-None-ascii-True] SKIPPED (compress function not provided for snappy) [ 49%] dask/bag/tests/test_text.py::test_read_text[snappy-None-ascii-False] SKIPPED (compress function not provided for snappy) [ 49%] dask/bag/tests/test_text.py::test_read_text[snappy-None-utf-8-True] SKIPPED (compress function not provided for snappy) [ 49%] dask/bag/tests/test_text.py::test_read_text[snappy-None-utf-8-False] SKIPPED (compress function not provided for snappy) [ 49%] dask/bag/tests/test_text.py::test_read_text[lz4-None-ascii-True] SKIPPED (compress function not provided for lz4) [ 49%] dask/bag/tests/test_text.py::test_read_text[lz4-None-ascii-False] SKIPPED (compress function not provided for lz4) [ 49%] dask/bag/tests/test_text.py::test_read_text[lz4-None-utf-8-True] SKIPPED (compress function not provided for lz4) [ 49%] dask/bag/tests/test_text.py::test_read_text[lz4-None-utf-8-False] SKIPPED (compress function not provided for lz4) [ 49%] dask/bag/tests/test_text.py::test_read_text[None-10 B-ascii-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[None-10 B-ascii-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[None-10 B-utf-8-True] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text[None-10 B-utf-8-False] PASSED [ 49%] dask/bag/tests/test_text.py::test_read_text_unicode_no_collection PASSED [ 49%] dask/bag/tests/test_text.py::test_files_per_partition PASSED [ 49%] dask/bag/tests/test_text.py::test_errors PASSED [ 49%] dask/bag/tests/test_text.py::test_complex_delimiter PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_read_block PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_seek_delimiter_endline PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[c:\\foo\\bar-c:\\foo\\bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[C:\\\\foo\\bar-C:\\\\foo\\bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[c:/foo/bar-c:/foo/bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[file:///c|\\foo\\bar-c:\\foo\\bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[file:///C|/foo/bar-C:/foo/bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_infer_storage_options_c[file:///C:/foo/bar-C:/foo/bar] PASSED [ 49%] dask/bytes/tests/test_bytes_utils.py::test_stringify_path PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[None-noop_file] PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[zip-unzip] PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[bz2-BZ2File] PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[gzip-] PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[lzma-LZMAFile] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_compression.py::test_files[xz-LZMAFile] PASSED [ 49%] dask/bytes/tests/test_compression.py::test_files[snappy-SnappyFile] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_compression.py::test_files[lz4-open] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_http.py::test_simple PASSED [ 49%] dask/bytes/tests/test_http.py::test_loc PASSED [ 49%] dask/bytes/tests/test_http.py::test_fetch_range_with_headers PASSED [ 49%] dask/bytes/tests/test_http.py::test_ops[None] PASSED [ 49%] dask/bytes/tests/test_http.py::test_ops[99999] PASSED [ 49%] dask/bytes/tests/test_http.py::test_ops_blocksize PASSED [ 49%] dask/bytes/tests/test_http.py::test_errors PASSED [ 49%] dask/bytes/tests/test_http.py::test_files PASSED [ 49%] dask/bytes/tests/test_http.py::test_open_glob PASSED [ 49%] dask/bytes/tests/test_http.py::test_parquet[pyarrow] SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 49%] dask/bytes/tests/test_http.py::test_parquet[fastparquet] SKIPPED (could not import 'fastparquet': No module named 'fastparquet') [ 49%] dask/bytes/tests/test_http.py::test_bag PASSED [ 49%] dask/bytes/tests/test_http.py::test_read_csv PASSED [ 49%] dask/bytes/tests/test_local.py::test_unordered_urlpath_errors PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_sample_delimiter PASSED [ 49%] dask/bytes/tests/test_local.py::test_parse_sample_bytes PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_no_sample PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_blocksize_none PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_blocksize_types[5.0] PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_blocksize_types[5 B] PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_blocksize_float_errs PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_include_path PASSED [ 49%] dask/bytes/tests/test_local.py::test_with_urls PASSED [ 49%] dask/bytes/tests/test_local.py::test_with_paths PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_block PASSED [ 49%] dask/bytes/tests/test_local.py::test_read_bytes_delimited PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[None-None] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[zip-None] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[bz2-None] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[gzip-None] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[lzma-None] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_compression[xz-None] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[snappy-None] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_compression[lz4-None] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_compression[None-10] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[zip-10] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[bz2-10] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[gzip-10] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[lzma-10] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_compression[xz-10] PASSED [ 49%] dask/bytes/tests/test_local.py::test_compression[snappy-10] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_compression[lz4-10] SKIPPED (compression function not provided) [ 49%] dask/bytes/tests/test_local.py::test_open_files PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_text_mode[utf-8] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_text_mode[ascii] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[None-rt] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[None-rb] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[zip-rt] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[zip-rb] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[bz2-rt] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[bz2-rb] PASSED [ 49%] dask/bytes/tests/test_local.py::test_open_files_compression[gzip-rt] PASSED [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[gzip-rb] PASSED [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[lzma-rt] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[lzma-rb] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[xz-rt] PASSED [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[xz-rb] PASSED [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[snappy-rt] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[snappy-rb] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[lz4-rt] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_open_files_compression[lz4-rb] SKIPPED (compression function not provided) [ 50%] dask/bytes/tests/test_local.py::test_bad_compression PASSED [ 50%] dask/bytes/tests/test_local.py::test_not_found PASSED [ 50%] dask/bytes/tests/test_local.py::test_names SKIPPED (need --runslow option to run) [ 50%] dask/bytes/tests/test_local.py::test_open_files_write[compression_opener0] PASSED [ 50%] dask/bytes/tests/test_local.py::test_open_files_write[compression_opener1] PASSED [ 50%] dask/bytes/tests/test_local.py::test_pickability_of_lazy_files PASSED [ 50%] dask/bytes/tests/test_local.py::test_py2_local_bytes PASSED [ 50%] dask/bytes/tests/test_local.py::test_abs_paths PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_register[Series-register_series_accessor] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_register[DataFrame-register_dataframe_accessor] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_register[Index-register_index_accessor] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_accessor_works PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_dt_accessor PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_dt_accessor_not_available PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_not_available PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_getitem PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_extractall PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_removeprefix_removesuffix[removeprefix] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_removeprefix_removesuffix[removesuffix] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_cat PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_cat_none PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_split_noexpand[split] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_split_noexpand[rsplit] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_split_expand[split] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_split_expand[rsplit] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_accessor_split_expand_more_columns XFAIL (Need to pad columns) [ 50%] dask/dataframe/tests/test_accessors.py::test_str_split_no_warning[range_index] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_str_split_no_warning[other index] PASSED [ 50%] dask/dataframe/tests/test_accessors.py::test_string_nullable_types PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_arithmetics SKIPPED (need --runslow option to run) [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_deterministic_arithmetic_names PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_arithmetics_different_index SKIPPED (need --runslow option to run) [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_scalar_arithmetics PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_scalar_arithmetics_with_dask_instances PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_frame_series_arithmetic_methods PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_timedelta[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_timedelta[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[sum-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[sum-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[sum-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[prod-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[prod-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[prod-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[product-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[product-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[product-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[min-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[min-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[min-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[max-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[max-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[max-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[mean-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[mean-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[mean-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[var-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[var-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[var-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[std-frame0-0-out0] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[std-frame1-1-out1] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_out[std-frame2-None-None] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_allany[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_allany[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_deterministic_reduction_names[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_deterministic_reduction_names[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reduction_series_invalid_axis PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_non_numeric_dtypes PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame_dtypes PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame_dtypes_numeric_only PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame_nan[False] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_reductions_frame_nan[2] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[lt] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[gt] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[le] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[ge] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[ne] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_comparison_nan[eq] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_sum_intna PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_divmod PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_moment PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_empty_df_reductions[sum] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_empty_df_reductions[count] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_empty_df_reductions[mean] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_empty_df_reductions[var] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_empty_df_reductions[sem] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[0-sum] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[0-prod] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[0-product] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[9-sum] PASSED [ 50%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[9-prod] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_series_agg_with_min_count[9-product] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_creates_copy_cols[0] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_creates_copy_cols[1] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[False-0] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[False-1] FAILED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[True-0] PASSED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[True-1] FAILED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_across_axis1_null_results[False] FAILED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_across_axis1_null_results[True] FAILED [ 51%] dask/dataframe/tests/test_arithmetics_reduction.py::test_std_raises_on_index PASSED [ 51%] dask/dataframe/tests/test_boolean.py::test_meta PASSED [ 51%] dask/dataframe/tests/test_boolean.py::test_ops PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_concat_unions_categoricals PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_unknown_categoricals[disk] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_unknown_categoricals[tasks] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_is_categorical_dtype PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorize PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_dtype PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorize_index PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index[disk] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index[tasks] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[1-1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[1-3] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[1-6] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[3-1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[3-3] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[3-6] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[6-1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[6-3] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_set_index_npartitions_vs_ncategories[6-6] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_repartition_on_categoricals[1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_repartition_on_categoricals[4] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorical_accessor_presence PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_categorize_nan PASSED [ 51%] dask/dataframe/tests/test_categorical.py::test_return_type_known_categories PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[categories-assert_array_index_eq-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[categories-assert_array_index_eq-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[categories-assert_array_index_eq-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[ordered-assert_eq-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[ordered-assert_eq-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[ordered-assert_eq-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[codes-assert_array_index_eq-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[codes-assert_array_index_eq-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_properties[codes-assert_array_index_eq-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[add_categories-kwargs0-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[add_categories-kwargs0-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[add_categories-kwargs0-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs1-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs1-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs1-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_unordered-kwargs2-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_unordered-kwargs2-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_unordered-kwargs2-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs3-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs3-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[as_ordered-kwargs3-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_categories-kwargs4-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_categories-kwargs4-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_categories-kwargs4-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[rename_categories-kwargs5-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[rename_categories-kwargs5-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[rename_categories-kwargs5-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[reorder_categories-kwargs6-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[reorder_categories-kwargs6-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[reorder_categories-kwargs6-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[set_categories-kwargs7-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[set_categories-kwargs7-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[set_categories-kwargs7-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_unused_categories-kwargs8-series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_unused_categories-kwargs8-series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_callable[remove_unused_categories-kwargs8-series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_categorical_empty PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_unknown_categories[series0] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_unknown_categories[series1] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_unknown_categories[series2] PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_categorical_string_ops PASSED [ 51%] dask/dataframe/tests/test_categorical.py::TestCategoricalAccessor::test_categorical_non_string_raises PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_dataframe_doc PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_dataframe_doc_from_non_pandas PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_Dataframe PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_head_tail PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_head_npartitions PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_head_npartitions_warn PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_index_head PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_Series PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_Index PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_axes PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_series_axes PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_Scalar PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_scalar_raises PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_attributes PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_column_names PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_columns_named_divisions_and_meta PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_index_names PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_timezone_freq[1] SKIPPED (Freq no longer included in ts) [ 51%] dask/dataframe/tests/test_dataframe.py::test_timezone_freq[2] SKIPPED (Freq no longer included in ts) [ 51%] dask/dataframe/tests/test_dataframe.py::test_rename_columns PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_rename_series PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_rename_series_method PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_rename_series_method_2 PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_describe_numeric[tdigest-test_values0] SKIPPED (Requires crick) [ 51%] dask/dataframe/tests/test_dataframe.py::test_describe_numeric[dask-test_values1] PASSED [ 51%] dask/dataframe/tests/test_dataframe.py::test_describe[None-None-None-subset0] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[None-None-None-subset1] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[None-None-None-subset2] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[None-None-None-subset3] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[None-None-None-subset4] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[all-None-None-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[include6-None-percentiles6-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[include7-None-None-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[include8-None-percentiles8-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[None-exclude9-None-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe[include10-None-None-None] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe_without_datetime_is_numeric PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe_empty PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe_empty_tdigest SKIPPED (could not import 'crick': No module named 'crick') [ 52%] dask/dataframe/tests/test_dataframe.py::test_describe_for_possibly_unsorted_q PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_cumulative PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_cumulative_empty_partitions[func0] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_cumulative_empty_partitions[func1] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_cumulative_empty_partitions[func2] XFAIL (ValueError: Can only compare identically-labeled Series objects) [ 52%] dask/dataframe/tests/test_dataframe.py::test_cumulative_empty_partitions[func3] XFAIL (ValueError: Can only compare identically-labeled Series objects) [ 52%] dask/dataframe/tests/test_dataframe.py::test_dropna PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_clip[2-5] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_clip[2.5-3.5] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_squeeze PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_where_mask PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_multi_argument PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_type PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_partition_info PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_names PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_column_info PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_method_names PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_propagates_index_metadata PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_keeps_kwargs_readable XFAIL (now we use SubgraphCallables) [ 52%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_with_delayed_collection PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_metadata_inference_single_partition_aligned_args PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align_dataframes PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_drop_duplicates PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_drop_duplicates_subset PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_get_partition PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_ndim PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_dtype PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_value_counts PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_value_counts_not_sorted PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_value_counts_with_dropna PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_value_counts_with_normalize PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_value_counts_with_normalize_and_dropna PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_unique PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_isin PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_contains_frame PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_len PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_size PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_shape PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_nbytes PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile[tdigest-expected0] SKIPPED (Requires crick) [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile[dask-expected1] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile_missing[tdigest] SKIPPED (Requires crick) [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile_missing[dask] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_empty_quantile[tdigest] SKIPPED (Requires crick) [ 52%] dask/dataframe/tests/test_dataframe.py::test_empty_quantile[dask] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_dataframe_quantile[tdigest-expected0] SKIPPED (Requires crick) [ 52%] dask/dataframe/tests/test_dataframe.py::test_dataframe_quantile[dask-expected1] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile_for_possibly_unsorted_q PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile_tiny_partitions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_quantile_trivial_partitions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_index PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_assign PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_assign_callable PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_assign_dtypes PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_assign_pandas_series PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_map PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_concat PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_args PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_known_divisions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_unknown_divisions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_with_min_count PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align[inner] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align[outer] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align[left] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align[right] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align_axis[inner] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align_axis[outer] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align_axis[left] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_align_axis[right] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_combine PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_combine_first PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_dataframe_picklable PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_random_partitions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_series_round PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition SKIPPED (need --runslow option to run) [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_divisions PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_on_pandas_dataframe PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_npartitions[0-float-1-1-True] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_npartitions[0-float-1-1-False] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_npartitions[0-float-1-2-True] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_npartitions[0-float-1-2-False] PASSED [ 52%] dask/dataframe/tests/test_dataframe.py::test_repartition_npartitions[0-float-1-4-True] PASSED [ 52%] 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dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index6--2-3] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index7-None-None] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index8-left8-None] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index9-None-right9] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index10-left10-None] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_boundary_slice_same[index11-None-right11] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_better_errors_object_reductions PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_sample_empty_partitions PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_coerce PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_bool PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_cumulative_multiple_columns PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_partition_array[asarray] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_partition_array[func1] PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_partition_sparse SKIPPED (could not import 'sparse': No module named 'sparse') [ 57%] dask/dataframe/tests/test_dataframe.py::test_mixed_dask_array_operations PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_mixed_dask_array_operations_errors PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_mixed_dask_array_multi_dimensional PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_meta_raises PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_meta_nonempty_uses_meta_value_if_provided PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_dask_dataframe_holds_scipy_sparse_containers PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_delays_large_inputs PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_partitions_indexer PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_mod_eq PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_setitem PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_setitem_with_bool_dataframe_as_key PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_setitem_with_bool_series_as_key PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_setitem_with_numeric_column_name_raises_not_implemented PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_broadcast PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_scalar_with_array PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_has_parallel_type PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_meta_error_message PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_index PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_assign_index PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_index_divisions PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_replace PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_map_partitions_delays_lists PASSED [ 57%] dask/dataframe/tests/test_dataframe.py::test_dtype_cast PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-False-1-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-False-1-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-False-3-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-False-3-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-True-1-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-True-1-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-True-3-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[False-True-3-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-False-1-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-False-1-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-False-3-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-False-3-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-True-1-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-True-1-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-True-3-1] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_map[True-True-3-4] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dataframe_explode PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_series_explode PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_pop PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_nunique[0-True] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_nunique[0-False] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_nunique[1-True] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_nunique[1-False] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_view PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_simple_map_partitions PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_iter PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dataframe_groupby_cumsum_agg_empty_partitions PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dataframe_groupby_cumprod_agg_empty_partitions PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_fuse_roots PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_attrs_dataframe PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_attrs_series PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_attrs_series_in_dataframes XFAIL (df.iloc[:0] does not keep the series attrs) [ 58%] dask/dataframe/tests/test_dataframe.py::test_join_series PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dask_layers PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_repr_html_dataframe_highlevelgraph PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_assign_na_float_columns PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dot PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_dot_nan PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_use_of_weakref_proxy PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_is_monotonic_numeric PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_is_monotonic_dt64 PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_index_is_monotonic_numeric PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_index_is_monotonic_dt64 PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_is_monotonic_empty_partitions PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_custom_map_reduce PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[2-columns-int] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[2-columns-float] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[2-index-int] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[2-index-float] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[5-columns-int] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[5-columns-float] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[5-index-int] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict[5-index-float] PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_from_dict_raises PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_empty PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_repr_materialize PASSED [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_extension_dtype[int64[pyarrow]] SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_extension_dtype[int32[pyarrow]] SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_extension_dtype[float64[pyarrow]] SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_extension_dtype[float32[pyarrow]] SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_extension_dtype[uint8[pyarrow]] SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_dataframe.py::test_pyarrow_decimal_extension_dtype SKIPPED (Requires native PyArrow-backed ExtensionArrays) [ 58%] dask/dataframe/tests/test_extensions.py::test_register_extension_type PASSED [ 58%] dask/dataframe/tests/test_extensions.py::test_reduction PASSED [ 58%] dask/dataframe/tests/test_extensions.py::test_scalar PASSED [ 58%] dask/dataframe/tests/test_format.py::test_repr PASSED [ 58%] dask/dataframe/tests/test_format.py::test_repr_meta_mutation PASSED [ 58%] dask/dataframe/tests/test_format.py::test_dataframe_format PASSED [ 58%] dask/dataframe/tests/test_format.py::test_dataframe_format_with_index PASSED [ 58%] dask/dataframe/tests/test_format.py::test_dataframe_format_unknown_divisions PASSED [ 58%] dask/dataframe/tests/test_format.py::test_dataframe_format_long PASSED [ 58%] dask/dataframe/tests/test_format.py::test_series_format PASSED [ 58%] dask/dataframe/tests/test_format.py::test_series_format_long PASSED [ 58%] dask/dataframe/tests/test_format.py::test_index_format PASSED [ 58%] dask/dataframe/tests/test_format.py::test_categorical_format PASSED [ 58%] dask/dataframe/tests/test_format.py::test_duplicate_columns_repr PASSED [ 58%] dask/dataframe/tests/test_format.py::test_empty_repr PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_internal_repr_xfail[disk] XFAIL (uncertain how to handle. See issue #3481.) [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_internal_repr_xfail[tasks] XFAIL (uncertain how to handle. See issue #3481.) [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_internal_repr[disk] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_internal_repr[tasks] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_error[disk] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_groupby_error[tasks] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby[disk] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby[tasks] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_apply_multiarg[disk] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_apply_multiarg[tasks] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-True-0] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-True-1] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-True-2] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-True-3] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-True-4] XFAIL (not yet supported) [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-False-0] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-False-1] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-False-2] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-False-3] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[disk-False-4] XFAIL (not yet supported) [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-True-0] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-True-1] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-True-2] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-True-3] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-True-4] XFAIL (not yet supported) [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-False-0] PASSED [ 58%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-False-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-False-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-False-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_full_groupby_multilevel[tasks-False-4] XFAIL (not yet supported) [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_dir[disk] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_dir[tasks] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_on_index[disk-sync] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_on_index[disk-threads] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_on_index[tasks-sync] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_on_index[tasks-threads] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-disk-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[sum-tasks-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-disk-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[mean-tasks-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-disk-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[median-tasks-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-disk-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[min-tasks-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-disk-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[max-tasks-6] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-0] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-1] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-2] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-3] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-4] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-5] PASSED [ 59%] dask/dataframe/tests/test_groupby.py::test_groupby_multilevel_getitem[count-disk-6] PASSED [ 59%] 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dask/dataframe/tests/test_groupby.py::test_series_groupby_errors[disk] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_series_groupby_errors[tasks] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_index_array[disk] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_index_array[tasks] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_set_index[disk] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_set_index[tasks] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[disk-True] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[disk-False] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[tasks-True] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[tasks-False] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[disk-split_every] FAILED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[disk-split_out] FAILED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[tasks-split_every] FAILED [ 61%] dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[tasks-split_out] FAILED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-0] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-1] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-2] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-3] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-4] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-5] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-6] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-7] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-8] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-9] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-10] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-0-11] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-0] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-1] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-2] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-3] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-4] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-5] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-6] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-7] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-8] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-9] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-10] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[disk-1-11] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-0] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-1] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-2] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-3] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-4] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-5] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-6] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-7] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-8] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-9] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-10] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-0-11] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-0] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-1] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-2] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-3] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-4] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-5] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-6] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-7] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-8] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-9] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-10] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle[tasks-1-11] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-0] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-1] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-2] PASSED [ 61%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-3] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-4] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-5] XFAIL (condition: NotImplemented) [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-2] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-3] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-4] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-5] XFAIL (condition: NotImplemented) [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-2] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-3] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-4] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-5] XFAIL (condition: NotImplemented) [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-2] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-3] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-4] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-5] XFAIL (condition: NotImplemented) [ 62%] dask/dataframe/tests/test_groupby.py::test_numeric_column_names[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_numeric_column_names[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_apply_tasks[disk] SKIPPED (Tasks-only shuffle test) [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_apply_tasks[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_multiprocessing[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_multiprocessing[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_normalize_by[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_groupby_normalize_by[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[sum-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[sum-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[mean-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[mean-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[median-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[median-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[min-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[min-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[max-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[max-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[count-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[count-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[size-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[size-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[std-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[std-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[var-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[var-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[cov-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[cov-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[corr-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[corr-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[nunique-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[nunique-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[first-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[first-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[last-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[last-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[prod-disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate__single_element_groups[prod-tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_build_agg_args__reuse_of_intermediates[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_build_agg_args__reuse_of_intermediates[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_dask[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_dask[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[disk-2-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[disk-2-8] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[disk-32-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[disk-32-8] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[tasks-2-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[tasks-2-8] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[tasks-32-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate[tasks-32-8] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_sort[disk-True] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_sort[disk-False] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_sort[tasks-True] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_sort[tasks-False] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_defaults[disk] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_shuffle_aggregate_defaults[tasks] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[disk-a-spec0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[disk-a-spec1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[disk-keys1-spec0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[disk-keys1-spec1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[tasks-a-spec0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[tasks-a-spec1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[tasks-keys1-spec0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_aggregate_median[tasks-keys1-spec1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-True-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-True-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-False-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-False-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-None-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-ffill-None-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-True-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-True-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-False-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-False-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-None-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-None-bfill-None-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-True-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-True-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-False-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-False-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-None-0] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-ffill-None-1] PASSED [ 62%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-None-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-1-bfill-None-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-None-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-ffill-None-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-None-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[disk-4-bfill-None-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-None-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-ffill-None-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-None-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-None-bfill-None-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-1-ffill-True-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-1-ffill-True-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-1-ffill-False-0] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-1-ffill-False-1] PASSED [ 63%] dask/dataframe/tests/test_groupby.py::test_fillna[tasks-1-ffill-None-0] PASSED [ 63%] 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dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-2-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-2-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-2-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-2-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[std-tasks-2-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-disk-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-disk-1-1] PASSED [ 65%] 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dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-2-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-2-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-2-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-2-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[var-tasks-2-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-2-0] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-2-1] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-2-2] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-2-3] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-disk-2-4] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-2-0] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-2-1] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-2-2] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-2-3] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[cov-tasks-2-4] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-2-0] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-2-1] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-2-2] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-2-3] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-disk-2-4] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-2-0] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-2-1] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-2-2] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-2-3] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[corr-tasks-2-4] SKIPPED (https://github.com/dask/dask/issues/9509) [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-2-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-2-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-2-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-2-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-disk-2-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-2-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-2-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-2-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-2-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[nunique-tasks-2-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-1-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-1-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-2-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-2-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-2-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-2-3] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-disk-2-4] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-1-0] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-1-1] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-1-2] PASSED [ 65%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-1-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-1-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-2-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[first-tasks-2-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-1-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-1-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-2-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-disk-2-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-1-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-1-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-2-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[last-tasks-2-4] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-4] FAILED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-4] FAILED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-4] FAILED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-3] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-4] FAILED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[sum-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[mean-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[median-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[min-tasks-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-1-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-2-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-2-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-disk-2-2] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-1-0] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-1-1] PASSED [ 66%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[max-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[count-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[size-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[std-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[var-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[cov-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[corr-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[nunique-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-disk-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-2-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[first-tasks-2-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-1-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-1-1] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-1-2] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-2-0] PASSED [ 67%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-disk-2-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-1-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-1-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-1-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-2-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[last-tasks-2-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-1-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-1-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-1-2] FAILED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-2-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-2-2] FAILED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-1-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-1-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-1-2] FAILED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-2-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-2-2] FAILED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-0-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-0-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-0-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-0-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-0-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-1-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-1-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-1-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-1-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-1-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-2-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-2-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-2-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[disk-2-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-0-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-0-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-0-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-0-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-0-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-1-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-1-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-1-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-1-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-1-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-2-0] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-2-2] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-2-3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_meta_content[tasks-2-4] XFAIL (index dtype does not coincide: boolean != empty) [ 68%] dask/dataframe/tests/test_groupby.py::test_groupy_non_aligned_index[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupy_non_aligned_index[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupy_series_wrong_grouper[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupy_series_wrong_grouper[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-1-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-5-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[disk-20-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-1-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-5-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-2-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-2-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-2-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-5-1] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-5-4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_hash_groupby_aggregate[tasks-20-5-20] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_split_out_multi_column_groupby[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_split_out_multi_column_groupby[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_num[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_num[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_not_supported[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_not_supported[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_numeric_column[disk] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_groupby_numeric_column[tasks] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-a-a] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-a-c] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-a-d] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-a-sel3] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-a-sel4] PASSED [ 68%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumsum-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-a-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-a-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-a-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-a-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-a-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumprod-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-a-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-a-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-a-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-a-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-a-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[disk-cumcount-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-a-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-a-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-a-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-a-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-a-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumsum-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-a-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-a-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-a-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-a-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-a-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumprod-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-a-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-a-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-a-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-a-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-a-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-key1-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-key1-c] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-key1-d] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-key1-sel3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative[tasks-cumcount-key1-sel4] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_series_groupby_multi_character_column_name[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_series_groupby_multi_character_column_name[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative_axis1[disk-cumsum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative_axis1[disk-cumprod] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative_axis1[tasks-cumsum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_cumulative_axis1[tasks-cumprod] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_unaligned_index[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_unaligned_index[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_string_label[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_string_label[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_dataframe_cum_caching[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_dataframe_cum_caching[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_series_cum_caching[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_series_cum_caching[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_agg_reduces[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_agg_reduces[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_single[disk] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_single[tasks] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[disk-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[disk-slice_1] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[disk-slice_2] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[disk-slice_3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[tasks-a] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[tasks-slice_1] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[tasks-slice_2] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_agg_grouper_multiple[tasks-slice_3] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-cumprod] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-cumcount] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-cumsum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-var] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-sum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-mean] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-count] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-size] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-std] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-min] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-max] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-first] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-last] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[disk-prod] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-cumprod] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-cumcount] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-cumsum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-var] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-sum] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-mean] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-count] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-size] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-std] PASSED [ 69%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-min] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-max] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-first] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-last] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_agg_funcs[tasks-prod] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-amin-group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-amin-group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-amin-group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-amin-idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-mean-group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-mean-group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-mean-group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk-mean-idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk--group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk--group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk--group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[disk--idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-amin-group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-amin-group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-amin-group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-amin-idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-mean-group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-mean-group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-mean-group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks-mean-idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks--group_args0] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks--group_args1] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks--group_args2] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_groupby_column_and_index_apply[tasks--idx] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_dataframe_groupby_agg_custom_sum[disk-pandas_spec0-dask_spec0-False] PASSED [ 70%] dask/dataframe/tests/test_groupby.py::test_dataframe_groupby_agg_custom_sum[disk-pandas_spec1-dask_spec1-True] PASSED [ 70%] 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dask/dataframe/tests/test_groupby.py::test_groupby_shift_series[disk] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_series[tasks] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_lazy_input[disk] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_lazy_input[tasks] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_within_partition_sorting[disk] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_within_partition_sorting[tasks] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_with_freq[disk] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_shift_with_freq[tasks] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_funcs[disk-] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_funcs[disk-sum0] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_funcs[disk-sum1] PASSED [ 71%] 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dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-True-6] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-True-7] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-True-8] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-True-9] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-1] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-2] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-3] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-4] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-5] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-6] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-7] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-8] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[disk-False-9] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[tasks-True-1] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[tasks-True-2] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[tasks-True-3] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[tasks-True-4] PASSED [ 71%] dask/dataframe/tests/test_groupby.py::test_groupby_transform_ufunc_partitioning[tasks-True-5] PASSED [ 71%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_partial_function_unexpected_args[tasks-1] PASSED [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_pandas[disk-False] PASSED [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_pandas[disk-True] PASSED [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_pandas[tasks-False] PASSED [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_pandas[tasks-True] PASSED [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-True-a-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-True-a-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-True-a-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] 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'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by4-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by4-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by4-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by5-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by5-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[disk-False-by5-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 72%] 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(could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-False-by5-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-a-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-a-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-a-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-c-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-c-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] 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'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by4-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by4-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by4-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by5-False] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by5-True] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_cudf[tasks-None-by5-None] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_grouper_dispatch[disk-a] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_grouper_dispatch[disk-b] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_grouper_dispatch[tasks-a] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_grouper_dispatch[tasks-b] SKIPPED (could not import 'cudf': No module named 'cudf') [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_with_agg[disk] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_dropna_with_agg[tasks] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_observed_with_agg[disk] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_observed_with_agg[tasks] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_rounding_negative_var[disk] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_rounding_negative_var[tasks] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column0-2] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column0-3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column1-2] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column1-3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column2-2] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[disk-column2-3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[tasks-column0-2] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[tasks-column0-3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_split_out_multiindex[tasks-column1-2] 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PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-count-c] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-count-by3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-count-by4] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-mean-a] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-mean-b] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-mean-c] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-mean-by3] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-mean-by4] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-std-a] PASSED [ 73%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[disk-True-std-b] PASSED [ 73%] 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dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-mean-c] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-mean-by3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-mean-by4] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-std-a] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-std-b] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-std-c] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-std-by3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument[tasks-False-std-by4] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-True-agg0] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-True-agg1] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-True-agg2] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-True-agg3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-False-agg0] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-False-agg1] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-False-agg2] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[disk-False-agg3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-True-agg0] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-True-agg1] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-True-agg2] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-True-agg3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-False-agg0] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-False-agg1] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-False-agg2] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_argument_agg[tasks-False-agg3] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_true_split_out[disk] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_sort_true_split_out[tasks] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-disk-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[sum-tasks-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-groupby1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-groupby1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-groupby1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-observed-groupby1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-cat_1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-cat_1-ordered-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-cat_1-unordererd-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-groupby1-ordered-known] PASSED [ 74%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[mean-disk-unobserved-groupby1-ordered-unknown] PASSED [ 74%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-cat_1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-cat_1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-cat_1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-groupby1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-groupby1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-disk-unobserved-groupby1-unordererd-known] PASSED [ 75%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-observed-groupby1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-observed-groupby1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-cat_1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-cat_1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-cat_1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-cat_1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-groupby1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-groupby1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-groupby1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[max-tasks-unobserved-groupby1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-cat_1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-cat_1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-cat_1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-cat_1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-cat_1-ordered-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-cat_1-ordered-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-cat_1-unordererd-known] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 75%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-disk-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-cat_1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-cat_1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-cat_1-unordererd-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-cat_1-unordererd-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-cat_1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-cat_1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-cat_1-unordererd-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-cat_1-unordererd-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[count-tasks-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-cat_1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-cat_1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-cat_1-unordererd-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-cat_1-unordererd-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-groupby1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-groupby1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-disk-observed-groupby1-unordererd-known] PASSED [ 76%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-tasks-unobserved-groupby1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-tasks-unobserved-groupby1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-tasks-unobserved-groupby1-unordererd-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[size-tasks-unobserved-groupby1-unordererd-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-observed-cat_1-ordered-known] SKIPPED (Can't calculate observed with all nans) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-observed-cat_1-ordered-unknown] SKIPPED (Can't calculate observed with all nans) [ 76%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-observed-groupby1-unordererd-unknown] SKIPPED (Can't calculate observed with all nans) [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-unobserved-cat_1-ordered-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-unobserved-cat_1-ordered-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-unobserved-cat_1-unordererd-known] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 76%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[std-disk-unobserved-groupby1-ordered-known] PASSED [ 76%] 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[var-tasks-unobserved-groupby1-ordered-known] PASSED [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[var-tasks-unobserved-groupby1-ordered-unknown] PASSED [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[var-tasks-unobserved-groupby1-unordererd-known] PASSED [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[var-tasks-unobserved-groupby1-unordererd-unknown] PASSED [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-cat_1-ordered-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-cat_1-ordered-unknown] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-cat_1-unordererd-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-cat_1-unordererd-unknown] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-groupby1-ordered-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-groupby1-ordered-unknown] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-groupby1-unordererd-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-observed-groupby1-unordererd-unknown] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-unobserved-cat_1-ordered-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-unobserved-cat_1-ordered-unknown] SKIPPED (Not implemented for DataFrameGroupBy yet.) [ 77%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[cov-disk-unobserved-cat_1-unordererd-known] SKIPPED (Not implemented for DataFrameGroupBy yet.) 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dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-groupby1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-groupby1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-groupby1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-observed-groupby1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-cat_1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-groupby1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-groupby1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-groupby1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[last-tasks-unobserved-groupby1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-cat_1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-cat_1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-disk-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-cat_1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-observed-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-cat_1-ordered-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-cat_1-ordered-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-cat_1-unordererd-known] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-cat_1-unordererd-unknown] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-groupby1-ordered-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-groupby1-ordered-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-groupby1-unordererd-known] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[prod-tasks-unobserved-groupby1-unordererd-unknown] SKIPPED (Gives zeros rather than nans.) [ 78%] dask/dataframe/tests/test_groupby.py::test_dataframe_named_agg[disk-True] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_dataframe_named_agg[disk-False] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_dataframe_named_agg[tasks-True] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_dataframe_named_agg[tasks-False] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-count-True] PASSED [ 78%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-count-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-mean-True] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-mean-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-agg2-True] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[disk-agg2-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-count-True] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-count-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-mean-True] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-mean-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-agg2-True] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_series_named_agg[tasks-agg2-False] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_empty_partitions_with_value_counts[disk] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_empty_partitions_with_value_counts[tasks] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_pd_grouper[disk] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_pd_grouper[tasks] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_empty_partitions_with_rows_operation[disk-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_empty_partitions_with_rows_operation[disk-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_empty_partitions_with_rows_operation[tasks-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_empty_partitions_with_rows_operation[tasks-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_row_operations[disk-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_row_operations[disk-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_row_operations[tasks-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_with_row_operations[tasks-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_multi_index_with_row_operations[disk-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_multi_index_with_row_operations[disk-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_multi_index_with_row_operations[tasks-head] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_multi_index_with_row_operations[tasks-tail] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_iter_fails[disk] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_iter_fails[tasks] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_None_split_out_warns[disk] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_None_split_out_warns[tasks] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-3-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-3-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-value-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-value-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key2-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key2-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key3-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key3-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key4-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key4-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key5-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[disk-slice_key5-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-3-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-3-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-value-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-value-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key2-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key2-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key3-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key3-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key4-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key4-by1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key5-key1] PASSED [ 79%] dask/dataframe/tests/test_groupby.py::test_groupby_slice_getitem[tasks-slice_key5-by1] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj0] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj1] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj2] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj3] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj4] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj5] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj6] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj7] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj8] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj9] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj10] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj11] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_pandas_object[obj12] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_categorical_consistency PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_object_missing_values PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj0] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj1] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj2] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj3] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj4] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj5] PASSED [ 79%] dask/dataframe/tests/test_hashing.py::test_hash_object_dispatch[obj6] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df0] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df1] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df2] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df3] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df4] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df5] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df6] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df7] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df8] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df9] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df10] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df11] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[2-df12] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df0] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df1] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df2] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df3] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df4] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df5] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df6] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df7] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df8] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df9] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df10] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df11] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_basic[20-df12] PASSED [ 79%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[2-None] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[2-2] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[2-10] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[20-None] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[20-2] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_split_every[20-10] PASSED [ 80%] dask/dataframe/tests/test_hyperloglog.py::test_larger_data PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_non_informative_index PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_text_dates PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_series PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_array PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_function PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_array_different_partition PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_series_different_partition PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_with_non_boolean_series PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc2d PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc2d_with_known_divisions PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc2d_with_unknown_divisions PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc2d_duplicated_columns PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_getitem PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_getitem_slice PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_getitem_integer_slice PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_on_numpy_datetimes PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_on_pandas_datetimes PASSED [ 80%] dask/dataframe/tests/test_indexing.py::test_loc_datetime_no_freq PASSED [ 80%] 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dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on2-outer-tasks] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-inner-disk] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-inner-tasks] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-left-disk] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-left-tasks] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-right-disk] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-right-tasks] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-outer-disk] PASSED [ 81%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_unknown_to_unknown[on3-outer-tasks] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[idx-disk-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[idx-disk-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[idx-tasks-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[idx-tasks-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on1-disk-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on1-disk-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on1-tasks-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on1-tasks-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on2-disk-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on2-disk-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on2-tasks-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on2-tasks-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on3-disk-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on3-disk-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on3-tasks-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_right[on3-tasks-left] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-disk-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-disk-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-disk-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-disk-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-tasks-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-tasks-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-tasks-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[idx-tasks-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-disk-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-disk-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-disk-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-disk-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-tasks-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-tasks-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-tasks-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on1-tasks-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-disk-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-disk-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-disk-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-disk-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-tasks-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-tasks-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-tasks-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on2-tasks-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-disk-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-disk-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-disk-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-disk-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-tasks-True-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-tasks-True-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-tasks-0.75-inner] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_known_to_double_bcast_left[on3-tasks-0.75-right] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_column_with_nulls[None] PASSED [ 82%] dask/dataframe/tests/test_merge_column_and_index.py::test_merge_column_with_nulls[4] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_align_partitions PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_align_partitions_unknown_divisions PASSED [ 82%] dask/dataframe/tests/test_multi.py::test__maybe_align_partitions PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_indexed_dataframe_to_indexed_dataframe PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[disk-inner] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[disk-left] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[disk-right] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[disk-outer] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[tasks-inner] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[tasks-left] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[tasks-right] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_hash_join[tasks-outer] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_sequential_joins PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_indexed PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_basic PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_lefton_righton_error PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_by_leftby_rightby_error PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[backward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[backward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[forward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[forward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[nearest-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on[nearest-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-backward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-backward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-forward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-forward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-nearest-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[False-nearest-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-backward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-backward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-forward-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-forward-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-nearest-True] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_left_on_right_index[True-nearest-False] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_indexed_two_partitions PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_by PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_by_tolerance PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_by_tolerance_no_exact_matches PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_unsorted_raises PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_with_empty PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_left_right[endofweek-timestamp] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_on_left_right[endofweek-endofweek] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_merge_asof_with_various_npartitions PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_indexed_concat[inner] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_indexed_concat[outer] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat[inner] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat[outer] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat_series[inner] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat_series[outer] PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat_with_operation_remains_hlg PASSED [ 82%] dask/dataframe/tests/test_multi.py::test_concat_dataframe_empty FAILED [ 82%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[1.0-1] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[1.0-one] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[1.0-value_22] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[1-one] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[1-value_24] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_different_dtypes[one-value_25] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[True-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[True-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[True-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[True-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[False-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[False-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[False-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_columns_dtypes[False-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[disk-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[disk-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[disk-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[disk-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[tasks-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[tasks-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[tasks-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge[tasks-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_empty_left_df[disk-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_empty_left_df[disk-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_empty_left_df[tasks-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_empty_left_df[tasks-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_how_raises PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftsemi-parts0] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftsemi-parts1] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftsemi-parts2] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftanti-parts0] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftanti-parts1] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[pandas-leftanti-parts2] XFAIL (Pandas does not support leftsemi or leftanti) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftsemi-parts0] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftsemi-parts1] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftsemi-parts2] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftanti-parts0] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftanti-parts1] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_semi_anti_cudf[cudf-leftanti-parts2] SKIPPED (could not import 'cudf': No module named 'cudf') [ 83%] dask/dataframe/tests/test_multi.py::test_merge_tasks_passes_through PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[disk-inner] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[disk-outer] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[disk-left] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[disk-right] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[tasks-inner] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[tasks-outer] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[tasks-left] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_index_patterns[tasks-right] SKIPPED (need --runslow option to run) [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[disk-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[disk-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[disk-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[disk-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[tasks-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[tasks-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[tasks-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_by_index_patterns[tasks-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_join_gives_proper_divisions PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[tasks-inner] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[tasks-outer] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[tasks-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[tasks-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_melt PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_inner_merge_with_pandas_object PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_partition_merge[False] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_partition_merge[True] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_partition_merge_divisions PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_parition_merge_left_right[False-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_parition_merge_left_right[False-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_parition_merge_left_right[True-left] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_parition_merge_left_right[True-right] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_cheap_single_partition_merge_on_index PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_maintains_columns PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_index_without_divisions[disk] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_merge_index_without_divisions[tasks] PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_half_indexed_dataframe_avoids_shuffle PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_errors_for_merge_on_frame_columns PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_one_series PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_unknown_divisions PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat_unknown_divisions_errors PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat2 PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat3 PASSED [ 83%] dask/dataframe/tests/test_multi.py::test_concat4_interleave_partitions PASSED [ 83%] 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dask/dataframe/tests/test_shuffle.py::test_shuffle_empty_partitions[disk] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_shuffle_empty_partitions[tasks] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_partitioning_index PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_partitioning_index_categorical_on_values PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[disk-1] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[disk-4] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[disk-7] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[disk-23] SKIPPED (need --runslow option to run) [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[tasks-1] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[tasks-4] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[tasks-7] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_general[tasks-23] SKIPPED (need --runslow option to run) [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[disk-string[python]] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[disk-string[pyarrow]] SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[disk-object] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[tasks-string[python]] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[tasks-string[pyarrow]] SKIPPED (could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory) [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_string[tasks-object] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_self_index[disk] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_self_index[tasks] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_names[disk] XFAIL (dsk names in disk shuffle are not deterministic) [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_names[tasks] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_2[disk] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_2[tasks] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_3[disk] PASSED [ 88%] dask/dataframe/tests/test_shuffle.py::test_set_index_3[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_shuffle_sort[disk] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_shuffle_sort[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange[disk-threads] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange[disk-processes] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange[tasks-threads] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange[tasks-processes] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange_cleanup PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange_disk_cleanup_with_exception PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_rearrange_by_column_with_narrow_divisions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_maybe_buffered_partd PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_with_explicit_divisions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_with_empty_divisions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_divisions_2 PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_divisions_compute PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_divisions_sorted PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_consistent_divisions SKIPPED (need --runslow option to run) [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_reduces_partitions_small[disk] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_reduces_partitions_small[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_reduces_partitions_large[disk] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_reduces_partitions_large[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_doesnt_increase_partitions[disk] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_doesnt_increase_partitions[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_detects_sorted_data[disk] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_detects_sorted_data[tasks] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_sorts PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index[pandas] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index[cudf] SKIPPED (could not import 'dask_cudf': No module named 'dask_cudf') [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate[pandas] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate[cudf] SKIPPED (could not import 'cudf': No module named 'cudf') [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate_int[pandas] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate_int[cudf] SKIPPED (could not import 'cudf': No module named 'cudf') [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate_large_uint[pandas] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_interpolate_large_uint[cudf] SKIPPED (could not import 'cudf': No module named 'cudf') [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_timezone PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_npartitions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_datetime_precision[ns] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_datetime_precision[us] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_drop[True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_drop[False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_raises_error_on_bad_input PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_sorted_true PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_sorted_single_partition PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_sorted_min_max_same PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_empty_partition PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_on_empty PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_categorical PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_with_empty_and_overlap PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_compute_divisions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_empty_partitions PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_remove_nans PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_gh_2730 SKIPPED (need --runslow option to run) [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_does_not_repeat_work_due_to_optimizations[None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_does_not_repeat_work_due_to_optimizations[auto] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_errors_with_inplace_kwarg PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_set_index_timestamp PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_disk_shuffle_with_compression_option[None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_disk_shuffle_with_compression_option[ZLib] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_disk_shuffle_with_unknown_compression[UNKOWN_COMPRESSION_ALGO] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_disk_shuffle_check_actual_compression PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-id-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-id-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-id-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-name-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-name-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-name-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on2-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on2-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on2-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on3-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on3-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-None-on3-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-id-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-id-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-id-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-name-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-name-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-name-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on2-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on2-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on2-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on3-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on3-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[disk-4-on3-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-id-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-id-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-id-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-name-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-name-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-name-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on2-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on2-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on2-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on3-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on3-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-None-on3-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-id-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-id-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-id-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-name-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-name-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-name-False] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on2-None] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on2-True] PASSED [ 89%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on2-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on3-None] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on3-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_dataframe_shuffle_on_arg[tasks-4-on3-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_overlap PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_overlap_2 PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_overlap_does_not_drop_rows_when_divisions_overlap PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_compute_current_divisions_nan_partition PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_compute_current_divisions_overlap PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_compute_current_divisions_overlap_2 PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_shuffle_hlg_layer PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_shuffle_hlg_layer_serialize[10] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_shuffle_hlg_layer_serialize[1] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_nan_partition PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_with_dask_dt_index PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_set_index_with_series_uses_fastpath PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[10-a-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[10-a-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[10-b-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[10-b-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[500-a-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[500-a-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[500-b-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values[500-b-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by0-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by0-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by0-ascending2] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by0-ascending3] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by1-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by1-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by1-ascending2] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[10-by1-ascending3] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by0-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by0-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by0-ascending2] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by0-ascending3] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by1-True] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by1-False] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by1-ascending2] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_single_partition[500-by1-ascending3] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-a-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-a-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-a-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-a-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-b-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-b-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-b-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-1-b-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-a-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-a-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-a-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-a-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-b-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-b-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-b-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data0-5-b-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-a-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-a-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-a-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-a-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-b-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-b-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-b-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-1-b-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-a-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-a-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-a-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-a-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-b-True-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-b-True-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-b-False-first] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_with_nulls[data1-5-b-False-last] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_shuffle_values_raises PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_shuffle_by_as_list PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_noop PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_custom_function[1-by0] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_custom_function[1-by1] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_custom_function[10-by0] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_custom_function[10-by1] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_bool_ascending PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_timestamp[1] PASSED [ 90%] dask/dataframe/tests/test_shuffle.py::test_sort_values_timestamp[3] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input0] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input1] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input2] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input3] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input4] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[conj-pandas_input5] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input0] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input1] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input2] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input3] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input4] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp-pandas_input5] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input0] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input1] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input2] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input3] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input4] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log-pandas_input5] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input0] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input1] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input2] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input3] PASSED [ 90%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log2-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log10-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[log1p-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[expm1-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sqrt-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[square-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sin-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cos-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tan-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsin-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccos-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctan-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sinh-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cosh-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[tanh-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arcsinh-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arccosh-pandas_input5] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input0] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input1] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input2] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input3] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input4] PASSED [ 91%] dask/dataframe/tests/test_ufunc.py::test_ufunc[arctanh-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[deg2rad-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rad2deg-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isfinite-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isinf-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[isnan-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[signbit-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[degrees-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[radians-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[rint-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[fabs-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[sign-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[absolute-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[floor-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[ceil-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[trunc-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[logical_not-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input1] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input2] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input3] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input4] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[cbrt-pandas_input5] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input0] PASSED [ 92%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input3] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input4] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[exp2-pandas_input5] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input3] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input4] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[negative-pandas_input5] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input3] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input4] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[reciprocal-pandas_input5] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input3] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input4] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc[spacing-pandas_input5] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[isreal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[iscomplex] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[real] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[imag] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[angle] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[fix] SKIPPED (fix calls floor in a way that we do not yet support) [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[i0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[sinc] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped[nan_to_num] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_wrapped_not_implemented PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logaddexp] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logaddexp2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-arctan2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-hypot] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-copysign] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-nextafter] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-ldexp] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-fmod] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_and0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_or0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_xor0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-maximum] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-minimum] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-fmax] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-fmin] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-greater] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-greater_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-less] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-less_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-not_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_or1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_and1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[0-logical_xor1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logaddexp] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logaddexp2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-arctan2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-hypot] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-copysign] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-nextafter] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-ldexp] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-fmod] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_and0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_or0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_xor0] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-maximum] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-minimum] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-fmax] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-fmin] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-greater] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-greater_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-less] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-less_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-not_equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-equal] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_or1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_and1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_2args[1-logical_xor1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_clip[pandas0-5-50] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_clip[pandas1-5.5-40.5] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[conj] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[exp] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[log] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[log2] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[log10] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[log1p] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[expm1] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[sqrt] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[square] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[sin] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[cos] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[tan] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arcsin] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arccos] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arctan] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[sinh] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[cosh] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[tanh] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arcsinh] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arccosh] PASSED [ 93%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[arctanh] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[deg2rad] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[rad2deg] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[isfinite] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[isinf] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[isnan] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[signbit] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[degrees] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[radians] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[rint] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[fabs] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[sign] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[absolute] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[floor] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[ceil] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[trunc] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[logical_not] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[cbrt] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[exp2] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[negative] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[reciprocal] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_ufunc_out[spacing] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_frame_2ufunc_out PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp2-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp2-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp2-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logaddexp2-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[arctan2-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[arctan2-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[arctan2-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[arctan2-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[hypot-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[hypot-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[hypot-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[hypot-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[copysign-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[copysign-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[copysign-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[copysign-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[nextafter-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[nextafter-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[nextafter-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[nextafter-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[ldexp-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[ldexp-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[ldexp-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[ldexp-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmod-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmod-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmod-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmod-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and0-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and0-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and0-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and0-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or0-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or0-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or0-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or0-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor0-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor0-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor0-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor0-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[maximum-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[maximum-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[maximum-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[maximum-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[minimum-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[minimum-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[minimum-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[minimum-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmax-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmax-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmax-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmax-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmin-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmin-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmin-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[fmin-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater_equal-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater_equal-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater_equal-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[greater_equal-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less_equal-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less_equal-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less_equal-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[less_equal-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[not_equal-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[not_equal-2-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[not_equal-arg21-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[not_equal-arg21-arg11] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[equal-2-arg10] PASSED [ 94%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[equal-2-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[equal-arg21-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[equal-arg21-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or1-2-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or1-2-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or1-arg21-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_or1-arg21-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and1-2-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and1-2-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and1-arg21-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_and1-arg21-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor1-2-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor1-2-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor1-arg21-arg10] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_mixed_types[logical_xor1-arg21-arg11] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logaddexp] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logaddexp2] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-arctan2] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-hypot] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-copysign] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-nextafter] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-ldexp] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-fmod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_and0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_or0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_xor0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-maximum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-minimum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-fmax] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-fmin] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-greater] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-greater_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-less] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-less_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-not_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_or1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_and1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas0-darray0-logical_xor1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logaddexp] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logaddexp2] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-arctan2] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-hypot] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-copysign] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-nextafter] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-ldexp] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-fmod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_and0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_or0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_xor0] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-maximum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-minimum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-fmax] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-fmin] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-greater] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-greater_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-less] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-less_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-not_equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-equal] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_or1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_and1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_2args_with_array[pandas1-darray1-logical_xor1] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-conj-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-conj-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-conj-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-conj-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-conj-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log2-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log2-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log2-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log2-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log2-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log10-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log10-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log10-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log10-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log10-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log1p-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log1p-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log1p-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log1p-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-log1p-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-expm1-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-expm1-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-expm1-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-expm1-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-expm1-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sqrt-sum] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sqrt-prod] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sqrt-min] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sqrt-max] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sqrt-mean] PASSED [ 95%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-square-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-square-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-square-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-square-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-square-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sin-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sin-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sin-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sin-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sin-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cos-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cos-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cos-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cos-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cos-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tan-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tan-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tan-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tan-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tan-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsin-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsin-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsin-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsin-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsin-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccos-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccos-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccos-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccos-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccos-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctan-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctan-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctan-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctan-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctan-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sinh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sinh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sinh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sinh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sinh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cosh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cosh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cosh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cosh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cosh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tanh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tanh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tanh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tanh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-tanh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsinh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsinh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsinh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsinh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arcsinh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccosh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccosh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccosh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccosh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arccosh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctanh-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctanh-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctanh-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctanh-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-arctanh-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-deg2rad-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-deg2rad-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-deg2rad-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-deg2rad-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-deg2rad-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rad2deg-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rad2deg-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rad2deg-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rad2deg-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rad2deg-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isfinite-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isfinite-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isfinite-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isfinite-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isfinite-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isinf-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isinf-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isinf-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isinf-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isinf-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isnan-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isnan-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isnan-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isnan-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-isnan-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-signbit-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-signbit-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-signbit-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-signbit-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-signbit-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-degrees-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-degrees-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-degrees-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-degrees-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-degrees-mean] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-radians-sum] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-radians-prod] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-radians-min] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-radians-max] PASSED [ 96%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-radians-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rint-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rint-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rint-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rint-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-rint-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-fabs-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-fabs-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-fabs-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-fabs-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-fabs-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sign-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sign-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sign-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sign-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-sign-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-absolute-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-absolute-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-absolute-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-absolute-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-absolute-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-floor-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-floor-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-floor-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-floor-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-floor-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-ceil-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-ceil-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-ceil-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-ceil-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-ceil-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-trunc-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-trunc-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-trunc-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-trunc-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-trunc-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-logical_not-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-logical_not-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-logical_not-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-logical_not-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-logical_not-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cbrt-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cbrt-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cbrt-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cbrt-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-cbrt-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp2-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp2-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp2-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp2-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-exp2-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-negative-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-negative-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-negative-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-negative-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-negative-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-reciprocal-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-reciprocal-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-reciprocal-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-reciprocal-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-reciprocal-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-spacing-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-spacing-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-spacing-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-spacing-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas0-spacing-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-conj-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-conj-prod] XFAIL ('prod' overflowing with integer columns in pandas 1.2.0) [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-conj-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-conj-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-conj-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log2-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log2-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log2-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log2-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log2-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log10-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log10-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log10-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log10-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log10-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log1p-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log1p-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log1p-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log1p-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-log1p-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-expm1-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-expm1-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-expm1-min] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-expm1-max] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-expm1-mean] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sqrt-sum] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sqrt-prod] PASSED [ 97%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sqrt-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sqrt-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sqrt-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-square-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-square-prod] XFAIL ('prod' overflowing with integer columns in pandas 1.2.0) [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-square-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-square-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-square-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sin-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sin-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sin-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sin-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sin-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cos-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cos-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cos-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cos-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cos-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tan-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tan-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tan-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tan-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tan-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsin-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsin-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsin-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsin-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsin-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccos-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccos-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccos-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccos-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccos-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctan-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctan-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctan-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctan-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctan-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sinh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sinh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sinh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sinh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sinh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cosh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cosh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cosh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cosh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cosh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tanh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tanh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tanh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tanh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-tanh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsinh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsinh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsinh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsinh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arcsinh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccosh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccosh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccosh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccosh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arccosh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctanh-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctanh-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctanh-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctanh-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-arctanh-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-deg2rad-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-deg2rad-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-deg2rad-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-deg2rad-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-deg2rad-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rad2deg-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rad2deg-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rad2deg-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rad2deg-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rad2deg-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isfinite-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isfinite-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isfinite-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isfinite-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isfinite-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isinf-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isinf-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isinf-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isinf-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isinf-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isnan-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isnan-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isnan-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isnan-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-isnan-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-signbit-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-signbit-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-signbit-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-signbit-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-signbit-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-degrees-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-degrees-prod] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-degrees-min] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-degrees-max] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-degrees-mean] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-radians-sum] PASSED [ 98%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-radians-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-radians-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-radians-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-radians-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rint-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rint-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rint-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rint-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-rint-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-fabs-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-fabs-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-fabs-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-fabs-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-fabs-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sign-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sign-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sign-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sign-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-sign-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-absolute-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-absolute-prod] XFAIL ('prod' overflowing with integer columns in pandas 1.2.0) [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-absolute-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-absolute-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-absolute-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-floor-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-floor-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-floor-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-floor-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-floor-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-ceil-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-ceil-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-ceil-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-ceil-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-ceil-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-trunc-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-trunc-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-trunc-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-trunc-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-trunc-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-logical_not-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-logical_not-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-logical_not-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-logical_not-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-logical_not-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cbrt-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cbrt-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cbrt-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cbrt-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-cbrt-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp2-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp2-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp2-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp2-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-exp2-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-negative-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-negative-prod] XFAIL ('prod' overflowing with integer columns in pandas 1.2.0) [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-negative-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-negative-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-negative-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-reciprocal-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-reciprocal-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-reciprocal-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-reciprocal-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-reciprocal-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-spacing-sum] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-spacing-prod] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-spacing-min] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-spacing-max] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_with_reduction[pandas1-spacing-mean] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[15-pandas0] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[15-pandas1] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[16.40-pandas0] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[16.40-pandas1] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[scalar2-pandas0] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[scalar2-pandas1] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[16.41-pandas0] PASSED [ 99%] dask/dataframe/tests/test_ufunc.py::test_ufunc_numpy_scalar_comparison[16.41-pandas1] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_shard_df_on_index PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_make_meta PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_nonempty PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_duplicated PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_nonempty_empty_categories PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_nonempty_index PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_nonempty_uint64index PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_nonempty_scalar PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_raise_on_meta_error PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_check_meta PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_check_matching_columns_raises_appropriate_errors PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_check_meta_typename PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_is_dataframe_like[True] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_is_dataframe_like[False] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_apply_and_enforce_message PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_nonempty_series_sparse PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_nonempty_series_nullable_float PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_assert_eq_sorts PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_assert_eq_scheduler PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data0] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data1] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data2] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data3] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data4] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities[data5] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities_raise[data0] PASSED [ 99%] dask/dataframe/tests/test_utils_dataframe.py::test_meta_constructor_utilities_raise[data1] PASSED [100%] =================================== FAILURES =================================== ________________ test_datetime_std_with_larger_dataset[False-1] ________________ axis = 1, skipna = False @pytest.mark.skipif( not PANDAS_GT_120, reason="std() for datetime only added in pandas>=1.2" ) @pytest.mark.parametrize("axis", [0, 1]) @pytest.mark.parametrize("skipna", [False, True]) def test_datetime_std_with_larger_dataset(axis, skipna): num_rows = 250  dt1 = pd.concat( [ pd.Series([pd.NaT] * 15, index=range(15)), pd.to_datetime( pd.Series( [ datetime.fromtimestamp(1636426704 + (i * 250000)) for i in range(num_rows - 15) ], index=range(15, 250), ) ), ], ignore_index=False, )  base_numbers = [ (1638290040706793300 + (i * 69527182702409)) for i in range(num_rows) ]  pdf = pd.DataFrame( {"dt1": dt1, "dt2": pd.to_datetime(pd.Series(base_numbers))}, index=range(250) )  for i in range(3, 8): pdf[f"dt{i}"] = pd.to_datetime( pd.Series([int(x + (0.12 * i)) for x in base_numbers]) )  ddf = dd.from_pandas(pdf, 8)  assert_near_timedeltas( > ddf[["dt1"]].std(axis=axis, skipna=skipna).compute(), pdf[["dt1"]].std(axis=axis, skipna=skipna), ) dask/dataframe/tests/test_arithmetics_reduction.py:1566: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/threaded.py:89: in get results = get_async( dask/local.py:511: in get_async raise_exception(exc, tb) dask/local.py:319: in reraise raise exc dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:8143: in _sqrt_and_convert_to_timedelta return pd.to_timedelta(M.std(partition, axis=axis, *args, **kwargs)) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:130: in to_timedelta values = _convert_listlike(arg._values, unit=unit, errors=errors) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:179: in _convert_listlike td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ data = array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]) copy = False, unit = None, errors = 'raise' def sequence_to_td64ns( data, copy: bool = False, unit=None, errors="raise" ) -> tuple[np.ndarray, Tick | None]:  """  Parameters  ----------  data : list-like  copy : bool, default False  unit : str, optional  The timedelta unit to treat integers as multiples of. For numeric  data this defaults to ``'ns'``.  Must be un-specified if the data contains a str and ``errors=="raise"``.  errors : {"raise", "coerce", "ignore"}, default "raise"  How to handle elements that cannot be converted to timedelta64[ns].  See ``pandas.to_timedelta`` for details.   Returns  -------  converted : numpy.ndarray  The sequence converted to a numpy array with dtype ``timedelta64[ns]``.  inferred_freq : Tick or None  The inferred frequency of the sequence.   Raises  ------  ValueError : Data cannot be converted to timedelta64[ns].   Notes  -----  Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause  errors to be ignored; they are caught and subsequently ignored at a  higher level.  """ inferred_freq = None if unit is not None: unit = parse_timedelta_unit(unit)  # Unwrap whatever we have into a np.ndarray if not hasattr(data, "dtype"): # e.g. list, tuple if np.ndim(data) == 0: # i.e. generator data = list(data) data = np.array(data, copy=False) elif isinstance(data, ABCMultiIndex): raise TypeError("Cannot create a DatetimeArray from a MultiIndex.") else: data = extract_array(data, extract_numpy=True)  if isinstance(data, IntegerArray): data = data.to_numpy("int64", na_value=iNaT) elif not isinstance(data, (np.ndarray, ExtensionArray)): # GH#24539 e.g. xarray, dask object data = np.asarray(data) elif isinstance(data, ABCCategorical): data = data.categories.take(data.codes, fill_value=NaT)._values copy = False  if isinstance(data, TimedeltaArray): inferred_freq = data.freq  # Convert whatever we have into timedelta64[ns] dtype if is_object_dtype(data.dtype) or is_string_dtype(data.dtype): # no need to make a copy, need to convert if string-dtyped data = objects_to_td64ns(data, unit=unit, errors=errors) copy = False  elif is_integer_dtype(data.dtype): # treat as multiples of the given unit data, copy_made = ints_to_td64ns(data, unit=unit) copy = copy and not copy_made  elif is_float_dtype(data.dtype): # cast the unit, multiply base/frac separately # to avoid precision issues from float -> int mask = np.isnan(data) m, p = precision_from_unit(unit or "ns") > base = data.astype(np.int64) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1014: RuntimeWarning ________________ test_datetime_std_with_larger_dataset[True-1] _________________ axis = 1, skipna = True @pytest.mark.skipif( not PANDAS_GT_120, reason="std() for datetime only added in pandas>=1.2" ) @pytest.mark.parametrize("axis", [0, 1]) @pytest.mark.parametrize("skipna", [False, True]) def test_datetime_std_with_larger_dataset(axis, skipna): num_rows = 250  dt1 = pd.concat( [ pd.Series([pd.NaT] * 15, index=range(15)), pd.to_datetime( pd.Series( [ datetime.fromtimestamp(1636426704 + (i * 250000)) for i in range(num_rows - 15) ], index=range(15, 250), ) ), ], ignore_index=False, )  base_numbers = [ (1638290040706793300 + (i * 69527182702409)) for i in range(num_rows) ]  pdf = pd.DataFrame( {"dt1": dt1, "dt2": pd.to_datetime(pd.Series(base_numbers))}, index=range(250) )  for i in range(3, 8): pdf[f"dt{i}"] = pd.to_datetime( pd.Series([int(x + (0.12 * i)) for x in base_numbers]) )  ddf = dd.from_pandas(pdf, 8)  assert_near_timedeltas( > ddf[["dt1"]].std(axis=axis, skipna=skipna).compute(), pdf[["dt1"]].std(axis=axis, skipna=skipna), ) dask/dataframe/tests/test_arithmetics_reduction.py:1566: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/threaded.py:89: in get results = get_async( dask/local.py:511: in get_async raise_exception(exc, tb) dask/local.py:319: in reraise raise exc dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:8143: in _sqrt_and_convert_to_timedelta return pd.to_timedelta(M.std(partition, axis=axis, *args, **kwargs)) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:130: in to_timedelta values = _convert_listlike(arg._values, unit=unit, errors=errors) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:179: in _convert_listlike td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ data = array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]) copy = False, unit = None, errors = 'raise' def sequence_to_td64ns( data, copy: bool = False, unit=None, errors="raise" ) -> tuple[np.ndarray, Tick | None]:  """  Parameters  ----------  data : list-like  copy : bool, default False  unit : str, optional  The timedelta unit to treat integers as multiples of. For numeric  data this defaults to ``'ns'``.  Must be un-specified if the data contains a str and ``errors=="raise"``.  errors : {"raise", "coerce", "ignore"}, default "raise"  How to handle elements that cannot be converted to timedelta64[ns].  See ``pandas.to_timedelta`` for details.   Returns  -------  converted : numpy.ndarray  The sequence converted to a numpy array with dtype ``timedelta64[ns]``.  inferred_freq : Tick or None  The inferred frequency of the sequence.   Raises  ------  ValueError : Data cannot be converted to timedelta64[ns].   Notes  -----  Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause  errors to be ignored; they are caught and subsequently ignored at a  higher level.  """ inferred_freq = None if unit is not None: unit = parse_timedelta_unit(unit)  # Unwrap whatever we have into a np.ndarray if not hasattr(data, "dtype"): # e.g. list, tuple if np.ndim(data) == 0: # i.e. generator data = list(data) data = np.array(data, copy=False) elif isinstance(data, ABCMultiIndex): raise TypeError("Cannot create a DatetimeArray from a MultiIndex.") else: data = extract_array(data, extract_numpy=True)  if isinstance(data, IntegerArray): data = data.to_numpy("int64", na_value=iNaT) elif not isinstance(data, (np.ndarray, ExtensionArray)): # GH#24539 e.g. xarray, dask object data = np.asarray(data) elif isinstance(data, ABCCategorical): data = data.categories.take(data.codes, fill_value=NaT)._values copy = False  if isinstance(data, TimedeltaArray): inferred_freq = data.freq  # Convert whatever we have into timedelta64[ns] dtype if is_object_dtype(data.dtype) or is_string_dtype(data.dtype): # no need to make a copy, need to convert if string-dtyped data = objects_to_td64ns(data, unit=unit, errors=errors) copy = False  elif is_integer_dtype(data.dtype): # treat as multiples of the given unit data, copy_made = ints_to_td64ns(data, unit=unit) copy = copy and not copy_made  elif is_float_dtype(data.dtype): # cast the unit, multiply base/frac separately # to avoid precision issues from float -> int mask = np.isnan(data) m, p = precision_from_unit(unit or "ns") > base = data.astype(np.int64) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1014: RuntimeWarning ______________ test_datetime_std_across_axis1_null_results[False] ______________ skipna = False @pytest.mark.skipif( not PANDAS_GT_120, reason="std() for datetime only added in pandas>=1.2" ) @pytest.mark.filterwarnings( "ignore:Dropping of nuisance columns:FutureWarning" ) # https://github.com/dask/dask/issues/7714 @pytest.mark.parametrize("skipna", [False, True]) def test_datetime_std_across_axis1_null_results(skipna): pdf = pd.DataFrame( { "dt1": [ datetime.fromtimestamp(1636426704 + (i * 250000)) for i in range(10) ], "dt2": [ datetime.fromtimestamp(1636426704 + (i * 217790)) for i in range(10) ], "nums": [i for i in range(10)], } )  ddf = dd.from_pandas(pdf, 3)  # Single column always results in NaT > assert_eq( ddf[["dt1"]].std(axis=1, skipna=skipna), pdf[["dt1"]].std(axis=1, skipna=skipna) ) dask/dataframe/tests/test_arithmetics_reduction.py:1604: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:545: in assert_eq assert_divisions(a, scheduler=scheduler) dask/dataframe/utils.py:620: in assert_divisions results = get(ddf.dask, ddf.__dask_keys__()) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:8143: in _sqrt_and_convert_to_timedelta return pd.to_timedelta(M.std(partition, axis=axis, *args, **kwargs)) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:130: in to_timedelta values = _convert_listlike(arg._values, unit=unit, errors=errors) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:179: in _convert_listlike td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ data = array([nan, nan, nan, nan]), copy = False, unit = None, errors = 'raise' def sequence_to_td64ns( data, copy: bool = False, unit=None, errors="raise" ) -> tuple[np.ndarray, Tick | None]:  """  Parameters  ----------  data : list-like  copy : bool, default False  unit : str, optional  The timedelta unit to treat integers as multiples of. For numeric  data this defaults to ``'ns'``.  Must be un-specified if the data contains a str and ``errors=="raise"``.  errors : {"raise", "coerce", "ignore"}, default "raise"  How to handle elements that cannot be converted to timedelta64[ns].  See ``pandas.to_timedelta`` for details.   Returns  -------  converted : numpy.ndarray  The sequence converted to a numpy array with dtype ``timedelta64[ns]``.  inferred_freq : Tick or None  The inferred frequency of the sequence.   Raises  ------  ValueError : Data cannot be converted to timedelta64[ns].   Notes  -----  Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause  errors to be ignored; they are caught and subsequently ignored at a  higher level.  """ inferred_freq = None if unit is not None: unit = parse_timedelta_unit(unit)  # Unwrap whatever we have into a np.ndarray if not hasattr(data, "dtype"): # e.g. list, tuple if np.ndim(data) == 0: # i.e. generator data = list(data) data = np.array(data, copy=False) elif isinstance(data, ABCMultiIndex): raise TypeError("Cannot create a DatetimeArray from a MultiIndex.") else: data = extract_array(data, extract_numpy=True)  if isinstance(data, IntegerArray): data = data.to_numpy("int64", na_value=iNaT) elif not isinstance(data, (np.ndarray, ExtensionArray)): # GH#24539 e.g. xarray, dask object data = np.asarray(data) elif isinstance(data, ABCCategorical): data = data.categories.take(data.codes, fill_value=NaT)._values copy = False  if isinstance(data, TimedeltaArray): inferred_freq = data.freq  # Convert whatever we have into timedelta64[ns] dtype if is_object_dtype(data.dtype) or is_string_dtype(data.dtype): # no need to make a copy, need to convert if string-dtyped data = objects_to_td64ns(data, unit=unit, errors=errors) copy = False  elif is_integer_dtype(data.dtype): # treat as multiples of the given unit data, copy_made = ints_to_td64ns(data, unit=unit) copy = copy and not copy_made  elif is_float_dtype(data.dtype): # cast the unit, multiply base/frac separately # to avoid precision issues from float -> int mask = np.isnan(data) m, p = precision_from_unit(unit or "ns") > base = data.astype(np.int64) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1014: RuntimeWarning ______________ test_datetime_std_across_axis1_null_results[True] _______________ skipna = True @pytest.mark.skipif( not PANDAS_GT_120, reason="std() for datetime only added in pandas>=1.2" ) @pytest.mark.filterwarnings( "ignore:Dropping of nuisance columns:FutureWarning" ) # https://github.com/dask/dask/issues/7714 @pytest.mark.parametrize("skipna", [False, True]) def test_datetime_std_across_axis1_null_results(skipna): pdf = pd.DataFrame( { "dt1": [ datetime.fromtimestamp(1636426704 + (i * 250000)) for i in range(10) ], "dt2": [ datetime.fromtimestamp(1636426704 + (i * 217790)) for i in range(10) ], "nums": [i for i in range(10)], } )  ddf = dd.from_pandas(pdf, 3)  # Single column always results in NaT > assert_eq( ddf[["dt1"]].std(axis=1, skipna=skipna), pdf[["dt1"]].std(axis=1, skipna=skipna) ) dask/dataframe/tests/test_arithmetics_reduction.py:1604: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:545: in assert_eq assert_divisions(a, scheduler=scheduler) dask/dataframe/utils.py:620: in assert_divisions results = get(ddf.dask, ddf.__dask_keys__()) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:8143: in _sqrt_and_convert_to_timedelta return pd.to_timedelta(M.std(partition, axis=axis, *args, **kwargs)) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:130: in to_timedelta values = _convert_listlike(arg._values, unit=unit, errors=errors) /usr/lib/python3.10/site-packages/pandas/core/tools/timedeltas.py:179: in _convert_listlike td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ data = array([nan, nan, nan, nan]), copy = False, unit = None, errors = 'raise' def sequence_to_td64ns( data, copy: bool = False, unit=None, errors="raise" ) -> tuple[np.ndarray, Tick | None]:  """  Parameters  ----------  data : list-like  copy : bool, default False  unit : str, optional  The timedelta unit to treat integers as multiples of. For numeric  data this defaults to ``'ns'``.  Must be un-specified if the data contains a str and ``errors=="raise"``.  errors : {"raise", "coerce", "ignore"}, default "raise"  How to handle elements that cannot be converted to timedelta64[ns].  See ``pandas.to_timedelta`` for details.   Returns  -------  converted : numpy.ndarray  The sequence converted to a numpy array with dtype ``timedelta64[ns]``.  inferred_freq : Tick or None  The inferred frequency of the sequence.   Raises  ------  ValueError : Data cannot be converted to timedelta64[ns].   Notes  -----  Unlike `pandas.to_timedelta`, if setting ``errors=ignore`` will not cause  errors to be ignored; they are caught and subsequently ignored at a  higher level.  """ inferred_freq = None if unit is not None: unit = parse_timedelta_unit(unit)  # Unwrap whatever we have into a np.ndarray if not hasattr(data, "dtype"): # e.g. list, tuple if np.ndim(data) == 0: # i.e. generator data = list(data) data = np.array(data, copy=False) elif isinstance(data, ABCMultiIndex): raise TypeError("Cannot create a DatetimeArray from a MultiIndex.") else: data = extract_array(data, extract_numpy=True)  if isinstance(data, IntegerArray): data = data.to_numpy("int64", na_value=iNaT) elif not isinstance(data, (np.ndarray, ExtensionArray)): # GH#24539 e.g. xarray, dask object data = np.asarray(data) elif isinstance(data, ABCCategorical): data = data.categories.take(data.codes, fill_value=NaT)._values copy = False  if isinstance(data, TimedeltaArray): inferred_freq = data.freq  # Convert whatever we have into timedelta64[ns] dtype if is_object_dtype(data.dtype) or is_string_dtype(data.dtype): # no need to make a copy, need to convert if string-dtyped data = objects_to_td64ns(data, unit=unit, errors=errors) copy = False  elif is_integer_dtype(data.dtype): # treat as multiples of the given unit data, copy_made = ints_to_td64ns(data, unit=unit) copy = copy and not copy_made  elif is_float_dtype(data.dtype): # cast the unit, multiply base/frac separately # to avoid precision issues from float -> int mask = np.isnan(data) m, p = precision_from_unit(unit or "ns") > base = data.astype(np.int64) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1014: RuntimeWarning ________________ test_groupby_reduction_split[disk-split_every] ________________ keyword = 'split_every' @pytest.mark.parametrize("keyword", ["split_every", "split_out"]) def test_groupby_reduction_split(keyword): pdf = pd.DataFrame( {"a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 100, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 100} ) ddf = dd.from_pandas(pdf, npartitions=15)  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # DataFrame for m in AGG_FUNCS: # nunique is not implemented for DataFrameGroupBy # covariance/correlation is not a series aggregation if m in ("nunique", "cov", "corr"): continue res = call(ddf.groupby("b", sort=False), m, **{keyword: 2}) > sol = call(pdf.groupby("b"), m) dask/dataframe/tests/test_groupby.py:796: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:787: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1347: in grouped_reduce applied = blk.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: in _cython_op_ndim_compat return self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[5.41065251e+185, 4.10018609e+114, 2.58224988e+120, 1.00000000e+000, 6.53318624e+077]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning _________________ test_groupby_reduction_split[disk-split_out] _________________ keyword = 'split_out' @pytest.mark.parametrize("keyword", ["split_every", "split_out"]) def test_groupby_reduction_split(keyword): pdf = pd.DataFrame( {"a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 100, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 100} ) ddf = dd.from_pandas(pdf, npartitions=15)  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # DataFrame for m in AGG_FUNCS: # nunique is not implemented for DataFrameGroupBy # covariance/correlation is not a series aggregation if m in ("nunique", "cov", "corr"): continue res = call(ddf.groupby("b", sort=False), m, **{keyword: 2}) > sol = call(pdf.groupby("b"), m) dask/dataframe/tests/test_groupby.py:796: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:787: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1347: in grouped_reduce applied = blk.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: in _cython_op_ndim_compat return self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[5.41065251e+185, 4.10018609e+114, 2.58224988e+120, 1.00000000e+000, 6.53318624e+077]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning _______________ test_groupby_reduction_split[tasks-split_every] ________________ keyword = 'split_every' @pytest.mark.parametrize("keyword", ["split_every", "split_out"]) def test_groupby_reduction_split(keyword): pdf = pd.DataFrame( {"a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 100, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 100} ) ddf = dd.from_pandas(pdf, npartitions=15)  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # DataFrame for m in AGG_FUNCS: # nunique is not implemented for DataFrameGroupBy # covariance/correlation is not a series aggregation if m in ("nunique", "cov", "corr"): continue res = call(ddf.groupby("b", sort=False), m, **{keyword: 2}) > sol = call(pdf.groupby("b"), m) dask/dataframe/tests/test_groupby.py:796: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:787: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1347: in grouped_reduce applied = blk.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: in _cython_op_ndim_compat return self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[5.41065251e+185, 4.10018609e+114, 2.58224988e+120, 1.00000000e+000, 6.53318624e+077]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning ________________ test_groupby_reduction_split[tasks-split_out] _________________ keyword = 'split_out' @pytest.mark.parametrize("keyword", ["split_every", "split_out"]) def test_groupby_reduction_split(keyword): pdf = pd.DataFrame( {"a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 100, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 100} ) ddf = dd.from_pandas(pdf, npartitions=15)  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # DataFrame for m in AGG_FUNCS: # nunique is not implemented for DataFrameGroupBy # covariance/correlation is not a series aggregation if m in ("nunique", "cov", "corr"): continue res = call(ddf.groupby("b", sort=False), m, **{keyword: 2}) > sol = call(pdf.groupby("b"), m) dask/dataframe/tests/test_groupby.py:796: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:787: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1347: in grouped_reduce applied = blk.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: in _cython_op_ndim_compat return self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[5.41065251e+185, 4.10018609e+114, 2.58224988e+120, 1.00000000e+000, 6.53318624e+077]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning ________ test_dataframe_aggregations_multilevel[prod-disk-1-4] _________ grouper = at 0x4014eecf70>, split_out = 1, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: ["a"], lambda df: ["a", "b"], lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_dataframe_aggregations_multilevel(grouper, split_out, agg_func): sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "d": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a", "d"], )  ddf = dd.from_pandas(pdf, npartitions=10)  # covariance only works with N+1 columns if agg_func not in ("cov", "corr"): assert_eq( > call(pdf.groupby(grouper(pdf), sort=sort)["c"], agg_func), call( ddf.groupby(grouper(ddf), sort=sort)["c"], agg_func, split_out=split_out, split_every=2, ), ) dask/dataframe/tests/test_groupby.py:1378: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1361: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 1.66798810e+23, 6.80788619e+22]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning ________ test_dataframe_aggregations_multilevel[prod-disk-2-4] _________ grouper = at 0x4014eecf70>, split_out = 2, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: ["a"], lambda df: ["a", "b"], lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_dataframe_aggregations_multilevel(grouper, split_out, agg_func): sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "d": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a", "d"], )  ddf = dd.from_pandas(pdf, npartitions=10)  # covariance only works with N+1 columns if agg_func not in ("cov", "corr"): assert_eq( > call(pdf.groupby(grouper(pdf), sort=sort)["c"], agg_func), call( ddf.groupby(grouper(ddf), sort=sort)["c"], agg_func, split_out=split_out, split_every=2, ), ) dask/dataframe/tests/test_groupby.py:1378: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1361: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 6.80788619e+22, 1.66798810e+23]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning ________ test_dataframe_aggregations_multilevel[prod-tasks-1-4] ________ grouper = at 0x4014eecf70>, split_out = 1, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: ["a"], lambda df: ["a", "b"], lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_dataframe_aggregations_multilevel(grouper, split_out, agg_func): sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "d": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a", "d"], )  ddf = dd.from_pandas(pdf, npartitions=10)  # covariance only works with N+1 columns if agg_func not in ("cov", "corr"): assert_eq( > call(pdf.groupby(grouper(pdf), sort=sort)["c"], agg_func), call( ddf.groupby(grouper(ddf), sort=sort)["c"], agg_func, split_out=split_out, split_every=2, ), ) dask/dataframe/tests/test_groupby.py:1378: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1361: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 1.66798810e+23, 6.80788619e+22]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning ________ test_dataframe_aggregations_multilevel[prod-tasks-2-4] ________ grouper = at 0x4014eecf70>, split_out = 2, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: ["a"], lambda df: ["a", "b"], lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_dataframe_aggregations_multilevel(grouper, split_out, agg_func): sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "d": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a", "d"], )  ddf = dd.from_pandas(pdf, npartitions=10)  # covariance only works with N+1 columns if agg_func not in ("cov", "corr"): assert_eq( > call(pdf.groupby(grouper(pdf), sort=sort)["c"], agg_func), call( ddf.groupby(grouper(ddf), sort=sort)["c"], agg_func, split_out=split_out, split_every=2, ), ) dask/dataframe/tests/test_groupby.py:1378: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1361: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 6.80788619e+22, 1.66798810e+23]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning __________ test_series_aggregations_multilevel[prod-disk-1-2] __________ grouper = at 0x4014eed1b0>, split_out = 1, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_series_aggregations_multilevel(grouper, split_out, agg_func):  """  similar to ``test_dataframe_aggregations_multilevel``, but series do not  support all groupby args.  """ sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # covariance/correlation is not a series aggregation if agg_func in ("cov", "corr"): return  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a"], )  ddf = dd.from_pandas(pdf, npartitions=10)  assert_eq( > call(pdf["c"].groupby(grouper(pdf), sort=sort), agg_func), call( ddf["c"].groupby(grouper(ddf), sort=sort), agg_func, split_out=split_out, split_every=2, ), # for pandas ~ 0.18, the name is not not properly propagated for # the mean aggregation check_names=(agg_func not in {"mean", "nunique"}), ) dask/dataframe/tests/test_groupby.py:1463: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1445: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 1.66798810e+23, 6.80788619e+22]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning __________ test_series_aggregations_multilevel[prod-disk-2-2] __________ grouper = at 0x4014eed1b0>, split_out = 2, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_series_aggregations_multilevel(grouper, split_out, agg_func):  """  similar to ``test_dataframe_aggregations_multilevel``, but series do not  support all groupby args.  """ sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # covariance/correlation is not a series aggregation if agg_func in ("cov", "corr"): return  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a"], )  ddf = dd.from_pandas(pdf, npartitions=10)  assert_eq( > call(pdf["c"].groupby(grouper(pdf), sort=sort), agg_func), call( ddf["c"].groupby(grouper(ddf), sort=sort), agg_func, split_out=split_out, split_every=2, ), # for pandas ~ 0.18, the name is not not properly propagated for # the mean aggregation check_names=(agg_func not in {"mean", "nunique"}), ) dask/dataframe/tests/test_groupby.py:1463: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1445: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 6.80788619e+22, 1.66798810e+23]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning _________ test_series_aggregations_multilevel[prod-tasks-1-2] __________ grouper = at 0x4014eed1b0>, split_out = 1, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_series_aggregations_multilevel(grouper, split_out, agg_func):  """  similar to ``test_dataframe_aggregations_multilevel``, but series do not  support all groupby args.  """ sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # covariance/correlation is not a series aggregation if agg_func in ("cov", "corr"): return  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a"], )  ddf = dd.from_pandas(pdf, npartitions=10)  assert_eq( > call(pdf["c"].groupby(grouper(pdf), sort=sort), agg_func), call( ddf["c"].groupby(grouper(ddf), sort=sort), agg_func, split_out=split_out, split_every=2, ), # for pandas ~ 0.18, the name is not not properly propagated for # the mean aggregation check_names=(agg_func not in {"mean", "nunique"}), ) dask/dataframe/tests/test_groupby.py:1463: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1445: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 1.66798810e+23, 6.80788619e+22]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning _________ test_series_aggregations_multilevel[prod-tasks-2-2] __________ grouper = at 0x4014eed1b0>, split_out = 2, agg_func = 'prod' @pytest.mark.parametrize( "grouper", [ lambda df: df["a"], lambda df: [df["a"], df["b"]], lambda df: [df["a"] > 2, df["b"] > 1], ], ) @pytest.mark.parametrize("split_out", [1, 2]) def test_series_aggregations_multilevel(grouper, split_out, agg_func):  """  similar to ``test_dataframe_aggregations_multilevel``, but series do not  support all groupby args.  """ sort = split_out == 1 # Don't sort for split_out > 1  def call(g, m, **kwargs): return getattr(g, m)(**kwargs)  # covariance/correlation is not a series aggregation if agg_func in ("cov", "corr"): return  pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6, 4, 3, 7] * 10, "b": [4, 2, 7, 3, 3, 1, 1, 1, 2] * 10, "c": [0, 1, 2, 3, 4, 5, 6, 7, 8] * 10, }, columns=["c", "b", "a"], )  ddf = dd.from_pandas(pdf, npartitions=10)  assert_eq( > call(pdf["c"].groupby(grouper(pdf), sort=sort), agg_func), call( ddf["c"].groupby(grouper(ddf), sort=sort), agg_func, split_out=split_out, split_every=2, ), # for pandas ~ 0.18, the name is not not properly propagated for # the mean aggregation check_names=(agg_func not in {"mean", "nunique"}), ) dask/dataframe/tests/test_groupby.py:1463: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:1445: in call return getattr(g, m)(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:2205: in prod return self._agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1506: in _agg_general result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/base.py:199: in grouped_reduce res = func(arr) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: in array_func result = self.grouper._cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: in _cython_operation return cy_op.cython_operation( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: in cython_operation return self._cython_op_ndim_compat( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:451: in _cython_op_ndim_compat res = self._call_cython_op( /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:578: in _call_cython_op op_result = maybe_downcast_to_dtype(result, res_dtype) /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:279: in maybe_downcast_to_dtype converted = maybe_downcast_numeric(result, dtype, do_round) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ result = array([[0.00000000e+00, 6.80788619e+22, 1.66798810e+23]]) dtype = dtype('int64'), do_round = False def maybe_downcast_numeric( result: ArrayLike, dtype: DtypeObj, do_round: bool = False ) -> ArrayLike:  """  Subset of maybe_downcast_to_dtype restricted to numeric dtypes.   Parameters  ----------  result : ndarray or ExtensionArray  dtype : np.dtype or ExtensionDtype  do_round : bool   Returns  -------  ndarray or ExtensionArray  """ if not isinstance(dtype, np.dtype) or not isinstance(result.dtype, np.dtype): # e.g. SparseDtype has no itemsize attr return result  def trans(x): if do_round: return x.round() return x  if dtype.kind == result.dtype.kind: # don't allow upcasts here (except if empty) if result.dtype.itemsize <= dtype.itemsize and result.size: return result  if is_bool_dtype(dtype) or is_integer_dtype(dtype):  if not result.size: # if we don't have any elements, just astype it return trans(result).astype(dtype)  # do a test on the first element, if it fails then we are done r = result.ravel() arr = np.array([r[0]])  if isna(arr).any(): # if we have any nulls, then we are done return result  elif not isinstance(r[0], (np.integer, np.floating, int, float, bool)): # a comparable, e.g. a Decimal may slip in here return result  if ( issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all() ): > new_result = trans(result).astype(dtype) E RuntimeWarning: invalid value encountered in cast /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:343: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-ordered-known] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 9 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo A foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x4355444d30> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = True, ordered_cats = True, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-ordered-unknown] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 13 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo __UNKNOWN_CATEGORIES__ foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x4355445900> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = False, ordered_cats = True, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-unordererd-known] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 9 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo A foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x43554463b0> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = True, ordered_cats = False, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-unordererd-unknown] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 13 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo __UNKNOWN_CATEGORIES__ foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x43554475b0> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = False, ordered_cats = False, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-ordered-known] _ values = array([[0.6669807950453606, , , , , , , , , , , , , , ...85, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.6669807950453606, , , , , , , , , , , , , , ...85, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6669807950453606, , , , , , , , , , , , , , ...85, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6669807950453606, , , , , , , , , , , , , , ...85, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6669807950453606], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.6669807950453606, , , , , , , , , , , , , , ...85, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6669807950453606], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = True, ordered_cats = True, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-ordered-unknown] _ values = array([[0.3980046708910494, , , , , , , , , , , , , , ...82, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.3980046708910494, , , , , , , , , , , , , , ...82, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.3980046708910494, , , , , , , , , , , , , , ...82, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.3980046708910494, , , , , , , , , , , , , , ...82, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.3980046708910494], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.3980046708910494, , , , , , , , , , , , , , ...82, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.3980046708910494], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = False, ordered_cats = True, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-unordererd-known] _ values = array([[0.06154259327397371, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.06154259327397371, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.06154259327397371, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.06154259327397371, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.06154259327397371], [], [], [], [], [], []... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.06154259327397371, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.06154259327397371], [], [], [], [], [], []... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = True, ordered_cats = False, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-unordererd-unknown] _ values = array([[0.6537832897505481, , , , , , , , , , , , , , ...38, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.6537832897505481, , , , , , , , , , , , , , ...38, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6537832897505481, , , , , , , , , , , , , , ...38, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6537832897505481, , , , , , , , , , , , , , ...38, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6537832897505481], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.6537832897505481, , , , , , , , , , , , , , ...38, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.6537832897505481], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = False, ordered_cats = False, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-ordered-known] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 9 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo A foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x428cc59e10> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = True, ordered_cats = True, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-ordered-unknown] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 13 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo __UNKNOWN_CATEGORIES__ foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x428cc5a830> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = False, ordered_cats = True, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-unordererd-known] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 9 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo A foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x428cc5ac20> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = True, ordered_cats = False, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-unordererd-unknown] _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: > yield dask/dataframe/utils.py:195: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = , udf = True args = (Dask DataFrame Structure: value_1 npartitions=1 object ... Dask Name: drop_by_shallow_copy, 13 graph layers,) kwargs = {'aggfunc': , 'levels': 0, 'observed': False} def _emulate(func, *args, udf=False, **kwargs):  """  Apply a function using args / kwargs. If arguments contain dd.DataFrame /  dd.Series, using internal cache (``_meta``) for calculation  """ with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): > return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) dask/dataframe/core.py:6560: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ df = value_1 cat_1 NaN foo __UNKNOWN_CATEGORIES__ foo aggfunc = , levels = 0, dropna = {} sort = False, observed = {'observed': False}, kwargs = {} grouped = def _groupby_aggregate( df, aggfunc=None, levels=None, dropna=None, sort=False, observed=None, **kwargs ): dropna = {"dropna": dropna} if dropna is not None else {} observed = {"observed": observed} if observed is not None else {}  grouped = df.groupby(level=levels, sort=sort, **observed, **dropna) > return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:350: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ series_gb = kwargs = {} def _median_aggregate(series_gb, **kwargs): with check_numeric_only_deprecation(): > return series_gb.median(**kwargs) dask/dataframe/groupby.py:2842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = numeric_only = @final @Substitution(name="groupby") @Appender(_common_see_also) def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):  """  Compute median of groups, excluding missing values.   For multiple groupings, the result index will be a MultiIndex   Parameters  ----------  numeric_only : bool, default True  Include only float, int, boolean columns. If None, will attempt to use  everything, then use only numeric data.   Returns  -------  Series or DataFrame  Median of values within each group.  """ numeric_only_bool = self._resolve_numeric_only(numeric_only)  > result = self._cython_agg_general( "median", alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), numeric_only=numeric_only_bool, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = how = 'median' alt = . at 0x428cc5b490> numeric_only = False, min_count = -1 @final def _cython_agg_general( self, how: str, alt: Callable, numeric_only: bool, min_count: int = -1 ): # Note: we never get here with how="ohlc" for DataFrameGroupBy; # that goes through SeriesGroupBy  data = self._get_data_to_aggregate() is_ser = data.ndim == 1  if numeric_only: if is_ser and not is_numeric_dtype(self._selected_obj.dtype): # GH#41291 match Series behavior kwd_name = "numeric_only" if how in ["any", "all"]: kwd_name = "bool_only" raise NotImplementedError( f"{type(self).__name__}.{how} does not implement {kwd_name}." ) elif not is_ser: data = data.get_numeric_data(copy=False)  def array_func(values: ArrayLike) -> ArrayLike: try: result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) except NotImplementedError: # generally if we have numeric_only=False # and non-applicable functions # try to python agg # TODO: shouldn't min_count matter? result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt)  return result  # TypeError -> we may have an exception in trying to aggregate # continue and exclude the block new_mgr = data.grouped_reduce(array_func, ignore_failures=True)  if not is_ser and len(new_mgr) < len(data): > warn_dropping_nuisance_columns_deprecated(type(self), how) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1595: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cls = , how = 'median' def warn_dropping_nuisance_columns_deprecated(cls, how: str) -> None: > warnings.warn( "Dropping invalid columns in " f"{cls.__name__}.{how} is deprecated. " "In a future version, a TypeError will be raised. " f"Before calling .{how}, select only columns which " "should be valid for the function.", FutureWarning, stacklevel=find_stack_level(), ) E FutureWarning: Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function. /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:3893: FutureWarning The above exception was the direct cause of the following exception: known_cats = False, ordered_cats = False, agg_func = 'median', groupby = 'cat_1' observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  assert_eq( agg(pdf.groupby(groupby, observed=observed)), > agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2987: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_groupby.py:2977: in agg return getattr(grp, agg_func)(**kwargs) dask/dataframe/groupby.py:1807: in median return _shuffle_aggregate( dask/dataframe/groupby.py:2979: in _shuffle_aggregate result = chunked.shuffle( dask/dataframe/core.py:874: in map_partitions return map_partitions(func, self, *args, **kwargs) dask/dataframe/core.py:6630: in map_partitions meta = _get_meta_map_partitions(args, dfs, func, kwargs, meta, parent_meta) dask/dataframe/core.py:6741: in _get_meta_map_partitions meta = _emulate(func, *args, udf=True, **kwargs) dask/dataframe/core.py:6559: in _emulate with raise_on_meta_error(funcname(func), udf=udf), check_numeric_only_deprecation(): /usr/lib/python3.10/contextlib.py:153: in __exit__ self.gen.throw(typ, value, traceback) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ funcname = '_groupby_aggregate', udf = True @contextmanager def raise_on_meta_error(funcname=None, udf=False):  """Reraise errors in this block to show metadata inference failure.   Parameters  ----------  funcname : str, optional  If provided, will be added to the error message to indicate the  name of the method that failed.  """ try: yield except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) msg = "Metadata inference failed{0}.\n\n" if udf: msg += ( "You have supplied a custom function and Dask is unable to \n" "determine the type of output that that function returns. \n\n" "To resolve this please provide a meta= keyword.\n" "The docstring of the Dask function you ran should have more information.\n\n" ) msg += ( "Original error is below:\n" "------------------------\n" "{1}\n\n" "Traceback:\n" "---------\n" "{2}" ) msg = msg.format(f" in `{funcname}`" if funcname else "", repr(e), tb) > raise ValueError(msg) from e E ValueError: Metadata inference failed in `_groupby_aggregate`. E  E You have supplied a custom function and Dask is unable to  E determine the type of output that that function returns.  E  E To resolve this please provide a meta= keyword. E The docstring of the Dask function you ran should have more information. E  E Original error is below: E ------------------------ E FutureWarning('Dropping invalid columns in DataFrameGroupBy.median is deprecated. In a future version, a TypeError will be raised. Before calling .median, select only columns which should be valid for the function.') E  E Traceback: E --------- E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/utils.py", line 195, in raise_on_meta_error E yield E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/core.py", line 6560, in _emulate E return func(*_extract_meta(args, True), **_extract_meta(kwargs, True)) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 350, in _groupby_aggregate E return aggfunc(grouped, **kwargs) E File "/build/python-dask/src/dask-2022.12.1/dask/dataframe/groupby.py", line 2842, in _median_aggregate E return series_gb.median(**kwargs) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1985, in median E result = self._cython_agg_general( E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 1595, in _cython_agg_general E warn_dropping_nuisance_columns_deprecated(type(self), how) E File "/usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py", line 3893, in warn_dropping_nuisance_columns_deprecated E warnings.warn( dask/dataframe/utils.py:216: ValueError _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-ordered-known] _ values = array([[0.28526191113577404, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.28526191113577404, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.28526191113577404, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.28526191113577404, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.28526191113577404], [], [], [], [], [], []... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.28526191113577404, , , , , , , , , , , , , , , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.28526191113577404], [], [], [], [], [], []... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = True, ordered_cats = True, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-ordered-unknown] _ values = array([[0.965248730380497, , , , , , , , , , , , , , ,...77, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.965248730380497, , , , , , , , , , , , , , ,...77, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.965248730380497, , , , , , , , , , , , , , ,...77, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.965248730380497, , , , , , , , , , , , , , ,...77, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.965248730380497], [], [], [], [], [], [], ... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.965248730380497, , , , , , , , , , , , , , ,...77, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.965248730380497], [], [], [], [], [], [], ... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = False, ordered_cats = True, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-unordererd-known] _ values = array([[0.5279300342243215, , , , , , , , , , , , , , ...79, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.5279300342243215, , , , , , , , , , , , , , ...79, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.5279300342243215, , , , , , , , , , , , , , ...79, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.5279300342243215, , , , , , , , , , , , , , ...79, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.5279300342243215], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.5279300342243215, , , , , , , , , , , , , , ...79, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.5279300342243215], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = True, ordered_cats = False, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _ test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-unordererd-unknown] _ values = array([[0.4417626030844213, , , , , , , , , , , , , , ...09, , , , , , , , , , , , , , ]], dtype=object) def array_func(values: ArrayLike) -> ArrayLike: try: > result = self.grouper._cython_operation( "aggregate", values, how, axis=data.ndim - 1, min_count=min_count ) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1578: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = kind = 'aggregate' values = array([[0.4417626030844213, , , , , , , , , , , , , , ...09, , , , , , , , , , , , , , ]], dtype=object) how = 'median', axis = 1, min_count = -1, kwargs = {} cy_op = ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) _ = 15, ngroups = 15 @final def _cython_operation( self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs, ) -> ArrayLike:  """  Returns the values of a cython operation.  """ assert kind in ["transform", "aggregate"]  cy_op = WrappedCythonOp(kind=kind, how=how)  ids, _, _ = self.group_info ngroups = self.ngroups > return cy_op.cython_operation( values=values, axis=axis, min_count=min_count, comp_ids=ids, ngroups=ngroups, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:939: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.4417626030844213, , , , , , , , , , , , , , ...09, , , , , , , , , , , , , , ]], dtype=object) axis = 1, min_count = -1 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) ngroups = 15, kwargs = {}, dtype = dtype('O'), is_numeric = False @final def cython_operation( self, *, values: ArrayLike, axis: int, min_count: int = -1, comp_ids: np.ndarray, ngroups: int, **kwargs, ) -> ArrayLike:  """  Call our cython function, with appropriate pre- and post- processing.  """ if values.ndim > 2: raise NotImplementedError("number of dimensions is currently limited to 2") elif values.ndim == 2: assert axis == 1, axis elif not is_1d_only_ea_obj(values): # Note: it is *not* the case that axis is always 0 for 1-dim values, # as we can have 1D ExtensionArrays that we need to treat as 2D assert axis == 0  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  # can we do this operation with our cython functions # if not raise NotImplementedError self._disallow_invalid_ops(dtype, is_numeric)  if not isinstance(values, np.ndarray): # i.e. ExtensionArray return self._ea_wrap_cython_operation( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, **kwargs, )  > return self._cython_op_ndim_compat( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=None, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:626: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.4417626030844213, , , , , , , , , , , , , , ...09, , , , , , , , , , , , , , ]], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} @final def _cython_op_ndim_compat( self, values: np.ndarray, *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None = None, result_mask: np.ndarray | None = None, **kwargs, ) -> np.ndarray: if values.ndim == 1: # expand to 2d, dispatch, then squeeze if appropriate values2d = values[None, :] if mask is not None: mask = mask[None, :] if result_mask is not None: result_mask = result_mask[None, :] res = self._call_cython_op( values2d, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) if res.shape[0] == 1: return res[0]  # otherwise we have OHLC return res.T  > return self._call_cython_op( values, min_count=min_count, ngroups=ngroups, comp_ids=comp_ids, mask=mask, result_mask=result_mask, **kwargs, ) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:466: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.4417626030844213], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) min_count = -1, ngroups = 15 comp_ids = array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 4, 0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14]) mask = None, result_mask = None, kwargs = {} orig_values = array([[0.4417626030844213, , , , , , , , , , , , , , ...09, , , , , , , , , , , , , , ]], dtype=object) dtype = dtype('O') @final def _call_cython_op( self, values: np.ndarray, # np.ndarray[ndim=2] *, min_count: int, ngroups: int, comp_ids: np.ndarray, mask: np.ndarray | None, result_mask: np.ndarray | None, **kwargs, ) -> np.ndarray: # np.ndarray[ndim=2] orig_values = values  dtype = values.dtype is_numeric = is_numeric_dtype(dtype)  is_datetimelike = needs_i8_conversion(dtype)  if is_datetimelike: values = values.view("int64") is_numeric = True elif is_bool_dtype(dtype): values = values.astype("int64") elif is_integer_dtype(dtype): # GH#43329 If the dtype is explicitly of type uint64 the type is not # changed to prevent overflow. if dtype != np.uint64: values = values.astype(np.int64, copy=False) elif is_numeric: if not is_complex_dtype(dtype): values = ensure_float64(values)  values = values.T if mask is not None: mask = mask.T if result_mask is not None: result_mask = result_mask.T  out_shape = self._get_output_shape(ngroups, values) > func, values = self.get_cython_func_and_vals(values, is_numeric) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:516: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = values = array([[0.4417626030844213], [], [], [], [], [], [],... [], [], [], [], [], [], []], dtype=object) is_numeric = False def get_cython_func_and_vals(self, values: np.ndarray, is_numeric: bool):  """  Find the appropriate cython function, casting if necessary.   Parameters  ----------  values : np.ndarray  is_numeric : bool   Returns  -------  func : callable  values : np.ndarray  """ how = self.how kind = self.kind  if how in ["median", "cumprod"]: # these two only have float64 implementations if is_numeric: values = ensure_float64(values) else: > raise NotImplementedError( f"function is not implemented for this dtype: " f"[how->{how},dtype->{values.dtype.name}]" ) E NotImplementedError: function is not implemented for this dtype: [how->median,dtype->object] /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:192: NotImplementedError During handling of the above exception, another exception occurred: known_cats = False, ordered_cats = False, agg_func = 'median' groupby = ['cat_1', 'cat_2'], observed = False @pytest.mark.skipif( not PANDAS_GT_110, reason="observed only supported for newer pandas" ) @pytest.mark.parametrize("known_cats", [True, False], ids=["known", "unknown"]) @pytest.mark.parametrize("ordered_cats", [True, False], ids=["ordered", "unordererd"]) @pytest.mark.parametrize("groupby", ["cat_1", ["cat_1", "cat_2"]]) @pytest.mark.parametrize("observed", [True, False], ids=["observed", "unobserved"]) def test_groupby_aggregate_categorical_observed( known_cats, ordered_cats, agg_func, groupby, observed ): if agg_func in ["cov", "corr", "nunique"]: pytest.skip("Not implemented for DataFrameGroupBy yet.") if agg_func in ["sum", "count", "prod"] and groupby != "cat_1": pytest.skip("Gives zeros rather than nans.") if agg_func in ["std", "var"] and observed: pytest.skip("Can't calculate observed with all nans")  pdf = pd.DataFrame( { "cat_1": pd.Categorical( list("AB"), categories=list("ABCDE"), ordered=ordered_cats ), "cat_2": pd.Categorical([1, 2], categories=[1, 2, 3], ordered=ordered_cats), "value_1": np.random.uniform(size=2), } ) ddf = dd.from_pandas(pdf, 2)  if not known_cats: ddf["cat_1"] = ddf["cat_1"].cat.as_unknown() ddf["cat_2"] = ddf["cat_2"].cat.as_unknown()  def agg(grp, **kwargs): if isinstance(grp, pd.core.groupby.DataFrameGroupBy): ctx = check_numeric_only_deprecation else: ctx = contextlib.nullcontext with ctx(): return getattr(grp, agg_func)(**kwargs)  # only include numeric columns when passing to "min" or "max" # pandas default is numeric_only=False if ordered_cats is False and agg_func in ["min", "max"] and groupby == "cat_1": pdf = pdf[["cat_1", "value_1"]] ddf = ddf[["cat_1", "value_1"]]  > assert_eq( agg(pdf.groupby(groupby, observed=observed)), agg(ddf.groupby(groupby, observed=observed)), ) dask/dataframe/tests/test_groupby.py:2985: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/utils.py:556: in assert_eq b = _check_dask( dask/dataframe/utils.py:464: in _check_dask result = dsk.compute(scheduler=scheduler) dask/base.py:315: in compute (result,) = compute(self, traverse=False, **kwargs) dask/base.py:600: in compute results = schedule(dsk, keys, **kwargs) dask/local.py:557: in get_sync return get_async( dask/local.py:500: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.10/concurrent/futures/_base.py:451: in result return self.__get_result() /usr/lib/python3.10/concurrent/futures/_base.py:403: in __get_result raise self._exception dask/local.py:542: in submit fut.set_result(fn(*args, **kwargs)) dask/local.py:238: in batch_execute_tasks return [execute_task(*a) for a in it] dask/local.py:238: in return [execute_task(*a) for a in it] dask/local.py:229: in execute_task result = pack_exception(e, dumps) dask/local.py:224: in execute_task result = _execute_task(task, data) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/optimization.py:990: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) dask/core.py:149: in get result = _execute_task(task, cache) dask/core.py:119: in _execute_task return func(*(_execute_task(a, cache) for a in args)) dask/utils.py:71: in apply return func(*args, **kwargs) dask/dataframe/core.py:6773: in apply_and_enforce df = func(*args, **kwargs) dask/dataframe/groupby.py:350: in _groupby_aggregate return aggfunc(grouped, **kwargs) dask/dataframe/groupby.py:2842: in _median_aggregate return series_gb.median(**kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1985: in median result = self._cython_agg_general( /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1592: in _cython_agg_general new_mgr = data.grouped_reduce(array_func, ignore_failures=True) /usr/lib/python3.10/site-packages/pandas/core/internals/managers.py:1338: in grouped_reduce applied = sb.apply(func) /usr/lib/python3.10/site-packages/pandas/core/internals/blocks.py:402: in apply result = func(self.values, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1586: in array_func result = self._agg_py_fallback(values, ndim=data.ndim, alt=alt) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1540: in _agg_py_fallback res_values = self.grouper.agg_series(ser, alt, preserve_dtype=True) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:981: in agg_series result = self._aggregate_series_pure_python(obj, func) /usr/lib/python3.10/site-packages/pandas/core/groupby/ops.py:1005: in _aggregate_series_pure_python res = func(group) /usr/lib/python3.10/site-packages/pandas/core/groupby/groupby.py:1987: in alt=lambda x: Series(x).median(numeric_only=numeric_only_bool), /usr/lib/python3.10/site-packages/pandas/core/generic.py:11197: in median return NDFrame.median(self, axis, skipna, level, numeric_only, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/generic.py:10709: in median return self._stat_function( /usr/lib/python3.10/site-packages/pandas/core/generic.py:10649: in _stat_function return self._reduce( /usr/lib/python3.10/site-packages/pandas/core/series.py:4471: in _reduce return op(delegate, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:155: in f result = alt(values, axis=axis, skipna=skipna, **kwds) /usr/lib/python3.10/site-packages/pandas/core/nanops.py:785: in nanmedian res = get_median(values) if notempty else np.nan /usr/lib/python3.10/site-packages/pandas/core/nanops.py:746: in get_median res = np.nanmedian(x[mask]) <__array_function__ internals>:200: in nanmedian ??? /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1215: in nanmedian return np.nanmean(a, axis, out=out, keepdims=keepdims) <__array_function__ internals>:200: in nanmean ??? _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ a = array([], dtype=float64), axis = None, dtype = None, out = None keepdims = @array_function_dispatch(_nanmean_dispatcher) def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, *, where=np._NoValue):  """  Compute the arithmetic mean along the specified axis, ignoring NaNs.   Returns the average of the array elements. The average is taken over  the flattened array by default, otherwise over the specified axis.  `float64` intermediate and return values are used for integer inputs.   For all-NaN slices, NaN is returned and a `RuntimeWarning` is raised.   .. versionadded:: 1.8.0   Parameters  ----------  a : array_like  Array containing numbers whose mean is desired. If `a` is not an  array, a conversion is attempted.  axis : {int, tuple of int, None}, optional  Axis or axes along which the means are computed. The default is to compute  the mean of the flattened array.  dtype : data-type, optional  Type to use in computing the mean. For integer inputs, the default  is `float64`; for inexact inputs, it is the same as the input  dtype.  out : ndarray, optional  Alternate output array in which to place the result. The default  is ``None``; if provided, it must have the same shape as the  expected output, but the type will be cast if necessary. See  :ref:`ufuncs-output-type` for more details.  keepdims : bool, optional  If this is set to True, the axes which are reduced are left  in the result as dimensions with size one. With this option,  the result will broadcast correctly against the original `a`.   If the value is anything but the default, then  `keepdims` will be passed through to the `mean` or `sum` methods  of sub-classes of `ndarray`. If the sub-classes methods  does not implement `keepdims` any exceptions will be raised.  where : array_like of bool, optional  Elements to include in the mean. See `~numpy.ufunc.reduce` for details.   .. versionadded:: 1.22.0   Returns  -------  m : ndarray, see dtype parameter above  If `out=None`, returns a new array containing the mean values,  otherwise a reference to the output array is returned. Nan is  returned for slices that contain only NaNs.   See Also  --------  average : Weighted average  mean : Arithmetic mean taken while not ignoring NaNs  var, nanvar   Notes  -----  The arithmetic mean is the sum of the non-NaN elements along the axis  divided by the number of non-NaN elements.   Note that for floating-point input, the mean is computed using the same  precision the input has. Depending on the input data, this can cause  the results to be inaccurate, especially for `float32`. Specifying a  higher-precision accumulator using the `dtype` keyword can alleviate  this issue.   Examples  --------  >>> a = np.array([[1, np.nan], [3, 4]])  >>> np.nanmean(a)  2.6666666666666665  >>> np.nanmean(a, axis=0)  array([2., 4.])  >>> np.nanmean(a, axis=1)  array([1., 3.5]) # may vary   """ arr, mask = _replace_nan(a, 0) if mask is None: return np.mean(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where)  if dtype is not None: dtype = np.dtype(dtype) if dtype is not None and not issubclass(dtype.type, np.inexact): raise TypeError("If a is inexact, then dtype must be inexact") if out is not None and not issubclass(out.dtype.type, np.inexact): raise TypeError("If a is inexact, then out must be inexact")  cnt = np.sum(~mask, axis=axis, dtype=np.intp, keepdims=keepdims, where=where) tot = np.sum(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims, where=where) avg = _divide_by_count(tot, cnt, out=out)  isbad = (cnt == 0) if isbad.any(): > warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=3) E RuntimeWarning: Mean of empty slice /usr/lib/python3.10/site-packages/numpy/lib/nanfunctions.py:1052: RuntimeWarning _________________________ test_concat_dataframe_empty __________________________ def test_concat_dataframe_empty(): df = pd.DataFrame({"a": [100, 200, 300]}, dtype="int64") empty_df = pd.DataFrame([], dtype="int64") df_concat = pd.concat([df, empty_df])  ddf = dd.from_pandas(df, npartitions=1) empty_ddf = dd.from_pandas(empty_df, npartitions=1) ddf_concat = dd.concat([ddf, empty_ddf]) assert_eq(df_concat, ddf_concat)  > empty_df_with_col = pd.DataFrame([], columns=["x"], dtype="int64") dask/dataframe/tests/test_multi.py:842: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3.10/site-packages/pandas/core/frame.py:746: in __init__ mgr = dict_to_mgr( /usr/lib/python3.10/site-packages/pandas/core/internals/construction.py:502: in dict_to_mgr return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy) /usr/lib/python3.10/site-packages/pandas/core/internals/construction.py:125: in arrays_to_mgr arrays = _homogenize(arrays, index, dtype) /usr/lib/python3.10/site-packages/pandas/core/internals/construction.py:625: in _homogenize val = sanitize_array( /usr/lib/python3.10/site-packages/pandas/core/construction.py:525: in sanitize_array data = construct_1d_arraylike_from_scalar(data, len(index), dtype) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ value = nan, length = 0, dtype = dtype('int64') def construct_1d_arraylike_from_scalar( value: Scalar, length: int, dtype: DtypeObj | None ) -> ArrayLike:  """  create a np.ndarray / pandas type of specified shape and dtype  filled with values   Parameters  ----------  value : scalar value  length : int  dtype : pandas_dtype or np.dtype   Returns  -------  np.ndarray / pandas type of length, filled with value   """  if dtype is None: try: dtype, value = infer_dtype_from_scalar(value, pandas_dtype=True) except OutOfBoundsDatetime: dtype = _dtype_obj  if isinstance(dtype, ExtensionDtype): cls = dtype.construct_array_type() subarr = cls._from_sequence([value] * length, dtype=dtype)  else:  if length and is_integer_dtype(dtype) and isna(value): # coerce if we have nan for an integer dtype dtype = np.dtype("float64") elif isinstance(dtype, np.dtype) and dtype.kind in ("U", "S"): # we need to coerce to object dtype to avoid # to allow numpy to take our string as a scalar value dtype = np.dtype("object") if not isna(value): value = ensure_str(value) elif dtype.kind in ["M", "m"]: value = maybe_unbox_datetimelike_tz_deprecation(value, dtype)  subarr = np.empty(length, dtype=dtype) > subarr.fill(value) E ValueError: cannot convert float NaN to integer /usr/lib/python3.10/site-packages/pandas/core/dtypes/cast.py:1917: ValueError ___________________________ test_get_dummies_sparse ____________________________ def decorator(): with warnings.catch_warnings(record=True) as record: > test_func() dask/dataframe/tests/test_reshape.py:100: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_reshape.py:119: in test_get_dummies_sparse assert_eq(exp, res) dask/dataframe/utils.py:564: in assert_eq a = _maybe_sort(a, check_index) dask/dataframe/utils.py:525: in _maybe_sort a = a.sort_values(by=methods.tolist(a.columns)) /usr/lib/python3.10/site-packages/pandas/util/_decorators.py:311: in wrapper return func(*args, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/frame.py:6300: in sort_values indexer = lexsort_indexer( /usr/lib/python3.10/site-packages/pandas/core/sorting.py:329: in lexsort_indexer cat = Categorical(k, ordered=True) /usr/lib/python3.10/site-packages/pandas/core/arrays/categorical.py:438: in __init__ codes, categories = factorize(values, sort=True) /usr/lib/python3.10/site-packages/pandas/core/algorithms.py:768: in factorize uniques, codes = safe_sort( /usr/lib/python3.10/site-packages/pandas/core/algorithms.py:1735: in safe_sort sorter = values.argsort() /usr/lib/python3.10/site-packages/pandas/core/arrays/base.py:678: in argsort mask=np.asarray(self.isna()), /usr/lib/python3.10/site-packages/pandas/core/arrays/sparse/array.py:725: in isna mask = np.full(len(self), False, dtype=np.bool8) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool8' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2)  def _expired(*args, **kwds): raise RuntimeError(msg)  return _expired  # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: > warnings.warn(msg, DeprecationWarning, stacklevel=2) E DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`. (Deprecated NumPy 1.24) /usr/lib/python3.10/site-packages/numpy/__init__.py:294: DeprecationWarning _________________________ test_get_dummies_sparse_mix __________________________ def decorator(): with warnings.catch_warnings(record=True) as record: > test_func() dask/dataframe/tests/test_reshape.py:100: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ dask/dataframe/tests/test_reshape.py:142: in test_get_dummies_sparse_mix assert_eq(exp, res) dask/dataframe/utils.py:564: in assert_eq a = _maybe_sort(a, check_index) dask/dataframe/utils.py:525: in _maybe_sort a = a.sort_values(by=methods.tolist(a.columns)) /usr/lib/python3.10/site-packages/pandas/util/_decorators.py:311: in wrapper return func(*args, **kwargs) /usr/lib/python3.10/site-packages/pandas/core/frame.py:6300: in sort_values indexer = lexsort_indexer( /usr/lib/python3.10/site-packages/pandas/core/sorting.py:329: in lexsort_indexer cat = Categorical(k, ordered=True) /usr/lib/python3.10/site-packages/pandas/core/arrays/categorical.py:438: in __init__ codes, categories = factorize(values, sort=True) /usr/lib/python3.10/site-packages/pandas/core/algorithms.py:768: in factorize uniques, codes = safe_sort( /usr/lib/python3.10/site-packages/pandas/core/algorithms.py:1735: in safe_sort sorter = values.argsort() /usr/lib/python3.10/site-packages/pandas/core/arrays/base.py:678: in argsort mask=np.asarray(self.isna()), /usr/lib/python3.10/site-packages/pandas/core/arrays/sparse/array.py:725: in isna mask = np.full(len(self), False, dtype=np.bool8) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool8' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2)  def _expired(*args, **kwds): raise RuntimeError(msg)  return _expired  # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: > warnings.warn(msg, DeprecationWarning, stacklevel=2) E DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`. (Deprecated NumPy 1.24) /usr/lib/python3.10/site-packages/numpy/__init__.py:294: DeprecationWarning =============================== warnings summary =============================== dask/tests/test_base.py::test_tokenize_dense_sparse_array[dia] /usr/lib/python3.10/site-packages/scipy/sparse/_coo.py:428: SparseEfficiencyWarning: Constructing a DIA matrix with 960 diagonals is inefficient warn("Constructing a DIA matrix with %d diagonals " dask/tests/test_base.py::test_tokenize_dense_sparse_array[dia] /usr/lib/python3.10/site-packages/scipy/sparse/_coo.py:428: SparseEfficiencyWarning: Constructing a DIA matrix with 959 diagonals is inefficient warn("Constructing a DIA matrix with %d diagonals " dask/array/tests/test_reductions.py::test_nan_object[min] dask/array/tests/test_reductions.py::test_nan_object[min] dask/array/tests/test_reductions.py::test_nan_object[min] dask/array/tests/test_reductions.py::test_nan_object[max] dask/array/tests/test_reductions.py::test_nan_object[max] dask/array/tests/test_reductions.py::test_nan_object[max] /usr/lib/python3.10/site-packages/numpy/core/fromnumeric.py:86: RuntimeWarning: invalid value encountered in reduce return ufunc.reduce(obj, axis, dtype, out, **passkwargs) dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-0-5] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[disk-1-5] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-0-5] dask/dataframe/tests/test_groupby.py::test_apply_or_transform_shuffle_multilevel[tasks-1-5] /usr/lib/python3.10/site-packages/_pytest/skipping.py:225: DeprecationWarning: NotImplemented should not be used in a boolean context if result: -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ============================= slowest 10 durations ============================= 26.94s call dask/dataframe/tests/test_arithmetics_reduction.py::test_frame_series_arithmetic_methods 26.08s call dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[disk-False] 23.76s call dask/dataframe/tests/test_groupby.py::test_split_apply_combine_on_series[tasks-False] 15.57s call dask/array/tests/test_routines.py::test_rot90[shape4-kwargs1] 15.20s call dask/bag/tests/test_bag.py::test_starmap 14.57s call dask/array/tests/test_routines.py::test_rot90[shape4-kwargs0] 13.75s call dask/array/tests/test_routines.py::test_rot90[shape4-kwargs2] 12.88s call dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-inner] 12.86s call dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-outer] 12.75s call dask/dataframe/tests/test_multi.py::test_merge_by_multiple_columns[disk-left] =========================== short test summary info ============================ SKIPPED [1] dask/tests/test_cache.py:11: could not import 'cachey': No module named 'cachey' SKIPPED [1] dask/tests/test_distributed.py:3: could not import 'distributed': cannot import name 'factors' from 'dask.utils' (/build/python-dask/src/dask-2022.12.1/dask/utils.py) SKIPPED [1] dask/tests/test_dot.py:10: could not import 'ipycytoscape': No module named 'ipycytoscape' SKIPPED [1] dask/tests/test_layers.py:5: could not import 'distributed': cannot import name 'factors' from 'dask.utils' (/build/python-dask/src/dask-2022.12.1/dask/utils.py) SKIPPED [1] dask/tests/test_spark_compat.py:12: could not import 'pyspark': No module named 'pyspark' SKIPPED [1] dask/array/tests/test_cupy_core.py:13: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_creation.py:10: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_gufunc.py:10: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_linalg.py:11: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_overlap.py:10: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_percentile.py:10: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_random.py:8: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_reductions.py:13: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_routines.py:11: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_slicing.py:10: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_cupy_sparse.py:8: could not import 'cupy': No module named 'cupy' SKIPPED [1] dask/array/tests/test_image.py:6: could not import 'skimage': No module named 'skimage' SKIPPED [1] dask/array/tests/test_sparse.py:10: could not import 'sparse': No module named 'sparse' SKIPPED [1] dask/bag/tests/test_avro.py:8: could not import 'fastavro': No module named 'fastavro' SKIPPED [1] dask/bytes/tests/test_s3.py:13: could not import 's3fs': No module named 's3fs' SKIPPED [1] dask/dataframe/tests/test_pyarrow_compat.py:8: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/tests/test_backends.py:11: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/tests/test_base.py:1132: could not import 'ipycytoscape': No module named 'ipycytoscape' SKIPPED [189] conftest.py:59: need --runslow option to run SKIPPED [1] dask/tests/test_ci.py:8: Only check for dev packages in `upstream` CI build SKIPPED [1] dask/tests/test_datasets.py:7: could not import 'mimesis': No module named 'mimesis' SKIPPED [1] dask/tests/test_datasets.py:16: could not import 'mimesis': No module named 'mimesis' SKIPPED [1] dask/tests/test_datasets.py:22: could not import 'mimesis': No module named 'mimesis' SKIPPED [1] dask/tests/test_datasets.py:41: could not import 'mimesis': No module named 'mimesis' SKIPPED [1] dask/tests/test_multiprocessing.py:285: POSIX supports different contexts SKIPPED [1] dask/tests/test_multiprocessing.py:298: POSIX supports different contexts SKIPPED [1] dask/tests/test_order.py:858: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/tests/test_sizeof.py:122: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/tests/test_utils.py:66: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/tests/test_utils.py:89: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/tests/test_utils.py:463: could not import 'multipledispatch': No module named 'multipledispatch' SKIPPED [1] dask/array/tests/test_array_core.py:1715: could not import 'sparse': No module named 'sparse' SKIPPED [1] dask/array/tests/test_array_core.py:3615: could not import 'distributed': cannot import name 'factors' from 'dask.utils' (/build/python-dask/src/dask-2022.12.1/dask/utils.py) SKIPPED [1] dask/array/tests/test_array_core.py:4546: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4554: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4560: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4570: could not import 'zarr': No module named 'zarr' SKIPPED [2] dask/array/tests/test_array_core.py:4582: could not import 'zarr': No module named 'zarr' SKIPPED [2] dask/array/tests/test_array_core.py:4593: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4601: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4612: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4620: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4629: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4642: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4681: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4693: could not import 'zarr': No module named 'zarr' SKIPPED [1] dask/array/tests/test_array_core.py:4722: could not import 'tiledb': No module named 'tiledb' SKIPPED [1] dask/array/tests/test_array_core.py:4755: could not import 'tiledb': No module named 'tiledb' SKIPPED [1] dask/array/tests/test_array_core.py:5071: could not import 'sparse': No module named 'sparse' SKIPPED [1] dask/array/tests/test_array_core.py:5152: could not import 'zarr': No module named 'zarr' SKIPPED [3] dask/array/tests/test_array_function.py:100: could not import 'sparse': No module named 'sparse' SKIPPED [1] dask/array/tests/test_array_function.py:110: could not import 'sparse': No module named 'sparse' SKIPPED [2] dask/array/tests/test_array_function.py:126: could not import 'cupy': No module named 'cupy' SKIPPED [288] dask/array/tests/test_creation.py:41: could not import 'cupy': No module named 'cupy' SKIPPED [60] dask/array/tests/test_creation.py:799: Bug when pad_width is larger than dimension: https://github.com/dask/dask/issues/5303 SKIPPED [20] dask/array/tests/test_creation.py:799: Not implemented SKIPPED [20] dask/array/tests/test_creation.py:799: Empty leads to undefined values, which may be different SKIPPED [2] dask/array/tests/test_fft.py:124: `scipy.fftpack` missing function `hfft`. SKIPPED [2] dask/array/tests/test_fft.py:124: `scipy.fftpack` missing function `ihfft`. SKIPPED [2] dask/array/tests/test_fft.py:159: `scipy.fftpack` missing function `rfft2`. SKIPPED [2] dask/array/tests/test_fft.py:159: `scipy.fftpack` missing function `irfft2`. SKIPPED [2] dask/array/tests/test_fft.py:159: `scipy.fftpack` missing function `rfftn`. SKIPPED [2] dask/array/tests/test_fft.py:159: `scipy.fftpack` missing function `irfftn`. SKIPPED [1] dask/array/tests/test_gufunc.py:612: could not import 'numba': No module named 'numba' SKIPPED [1] dask/array/tests/test_gufunc.py:631: could not import 'numba': No module named 'numba' SKIPPED [1] dask/array/tests/test_gufunc.py:647: could not import 'sparse': No module named 'sparse' SKIPPED [1] dask/array/tests/test_percentiles.py:27: Requires crick SKIPPED [1] dask/array/tests/test_percentiles.py:60: unconditional skip SKIPPED [1] dask/array/tests/test_percentiles.py:79: Requires crick SKIPPED [1] dask/array/tests/test_percentiles.py:88: Requires crick SKIPPED [4] dask/array/tests/test_percentiles.py:97: Requires crick SKIPPED [1] dask/array/tests/test_percentiles.py:109: Requires crick SKIPPED [1] dask/array/tests/test_random.py:326: could not import 'randomgen': No module named 'randomgen' SKIPPED [1] dask/array/tests/test_random.py:369: could not import 'cupy': No module named 'cupy' SKIPPED [4] dask/array/tests/test_routines.py:2071: Skipped SKIPPED [1] dask/array/tests/test_slicing.py:465: really long test SKIPPED [1] dask/array/tests/test_ufunc.py:141: fix calls floor in a way that we do not yet support SKIPPED [1] dask/bag/tests/test_bag.py:634: Hangs SKIPPED [4] dask/bag/tests/test_text.py:47: compress function not provided for lzma SKIPPED [4] dask/bag/tests/test_text.py:47: compress function not provided for snappy SKIPPED [4] dask/bag/tests/test_text.py:47: compress function not provided for lz4 SKIPPED [3] dask/bytes/tests/test_compression.py:12: compression function not provided SKIPPED [1] dask/bytes/tests/test_http.py:178: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/bytes/tests/test_http.py:178: could not import 'fastparquet': No module named 'fastparquet' SKIPPED [6] dask/bytes/tests/test_local.py:197: compression function not provided SKIPPED [6] dask/bytes/tests/test_local.py:248: compression function not provided SKIPPED [2] dask/dataframe/tests/test_dataframe.py:291: Freq no longer included in ts SKIPPED [1] dask/dataframe/tests/test_dataframe.py:403: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:605: could not import 'crick': No module named 'crick' SKIPPED [1] dask/dataframe/tests/test_dataframe.py:1404: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:1454: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:1477: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:1497: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:3247: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_dataframe.py:3311: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_dataframe.py:4475: Requires crick SKIPPED [1] dask/dataframe/tests/test_dataframe.py:4738: could not import 'sparse': No module named 'sparse' SKIPPED [5] dask/dataframe/tests/test_dataframe.py:5484: Requires native PyArrow-backed ExtensionArrays SKIPPED [1] dask/dataframe/tests/test_dataframe.py:5507: Requires native PyArrow-backed ExtensionArrays SKIPPED [1] dask/dataframe/tests/test_groupby.py:945: Tasks-only shuffle test SKIPPED [20] dask/dataframe/tests/test_groupby.py:1390: https://github.com/dask/dask/issues/9509 SKIPPED [108] dask/dataframe/tests/test_groupby.py:2713: could not import 'cudf': No module named 'cudf' SKIPPED [4] dask/dataframe/tests/test_groupby.py:2744: could not import 'cudf': No module named 'cudf' SKIPPED [2] dask/dataframe/tests/test_groupby.py:2841: could not import 'cudf': No module named 'cudf' SKIPPED [48] dask/dataframe/tests/test_groupby.py:2952: Gives zeros rather than nans. SKIPPED [32] dask/dataframe/tests/test_groupby.py:2954: Can't calculate observed with all nans SKIPPED [96] dask/dataframe/tests/test_groupby.py:2950: Not implemented for DataFrameGroupBy yet. SKIPPED [1] dask/dataframe/tests/test_indexing.py:731: could not import 'cudf': No module named 'cudf' SKIPPED [6] dask/dataframe/tests/test_multi.py:1063: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_multi.py:2401: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_rolling.py:531: could not import 'numba': No module named 'numba' SKIPPED [2] dask/dataframe/tests/test_shuffle.py:222: could not import 'pyarrow': libarrow.so.800: cannot open shared object file: No such file or directory SKIPPED [1] dask/dataframe/tests/test_shuffle.py:651: could not import 'dask_cudf': No module named 'dask_cudf' SKIPPED [1] dask/dataframe/tests/test_shuffle.py:692: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_shuffle.py:721: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_shuffle.py:745: could not import 'cudf': No module named 'cudf' SKIPPED [1] dask/dataframe/tests/test_ufunc.py:175: fix calls floor in a way that we do not yet support FAILED dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[False-1] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_with_larger_dataset[True-1] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_across_axis1_null_results[False] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_arithmetics_reduction.py::test_datetime_std_across_axis1_null_results[True] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[disk-split_every] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[disk-split_out] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[tasks-split_every] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_groupby_reduction_split[tasks-split_out] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-1-4] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-disk-2-4] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-1-4] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_dataframe_aggregations_multilevel[prod-tasks-2-4] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-1-2] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-disk-2-2] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-1-2] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_series_aggregations_multilevel[prod-tasks-2-2] - RuntimeWarning: invalid value encountered in cast FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-ordered-known] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-ordered-unknown] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-unordererd-known] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-cat_1-unordererd-unknown] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-ordered-known] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-ordered-unknown] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-unordererd-known] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-disk-unobserved-groupby1-unordererd-unknown] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-ordered-known] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-ordered-unknown] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-unordererd-known] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-cat_1-unordererd-unknown] - ValueError: Metadata inference failed in `_groupby_aggregate`. FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-ordered-known] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-ordered-unknown] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-unordererd-known] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_groupby.py::test_groupby_aggregate_categorical_observed[median-tasks-unobserved-groupby1-unordererd-unknown] - RuntimeWarning: Mean of empty slice FAILED dask/dataframe/tests/test_multi.py::test_concat_dataframe_empty - ValueError: cannot convert float NaN to integer FAILED dask/dataframe/tests/test_reshape.py::test_get_dummies_sparse - DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`. (Depr... FAILED dask/dataframe/tests/test_reshape.py::test_get_dummies_sparse_mix - DeprecationWarning: `np.bool8` is a deprecated alias for `np.bool_`. (Depr... = 35 failed, 9248 passed, 1046 skipped, 47 xfailed, 12 warnings in 2607.42s (0:43:27) = ==> ERROR: A failure occurred in check().  Aborting... ==> ERROR: Build failed, check /var/lib/archbuild/extra-riscv64/root2/build receiving incremental file list python-dask-2022.12.1-1-riscv64-build.log python-dask-2022.12.1-1-riscv64-check.log sent 62 bytes received 130,680 bytes 87,161.33 bytes/sec total size is 1,943,477 speedup is 14.86