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  • markelg 6

issue 1

  • Xarray does not support full range of netcdf-python compression options · 6 ✖

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  • CONTRIBUTOR · 6 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1519536791 https://github.com/pydata/xarray/issues/7388#issuecomment-1519536791 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85akkqX markelg 6883049 2023-04-24T07:32:26Z 2023-04-24T07:32:26Z CONTRIBUTOR

Good question. Right now ci/requirements/environment.yml is resolving libnetcdf 4.9.1, so fixing 4.9.2 would not work. I am not sure why or how to change this, as few package versions are pinned.

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  Xarray does not support full range of netcdf-python compression options 1503046820
1517820737 https://github.com/pydata/xarray/issues/7388#issuecomment-1517820737 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aeBtB markelg 6883049 2023-04-21T13:15:03Z 2023-04-21T13:15:03Z CONTRIBUTOR

I think it is about these two issues only, so backporting the fixes it should work.

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  Xarray does not support full range of netcdf-python compression options 1503046820
1511596653 https://github.com/pydata/xarray/issues/7388#issuecomment-1511596653 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85aGSJt markelg 6883049 2023-04-17T15:28:21Z 2023-04-17T15:29:43Z CONTRIBUTOR

Thanks. It looks like the errors are related to this bug https://github.com/Unidata/netcdf-c/issues/2674 The fix has been merged so I hope they include it in the next netcdf-c release. For the moment I prefer not to merge this as netcdf 4.9.2 and dask do not seem to play well together.

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  Xarray does not support full range of netcdf-python compression options 1503046820
1503827455 https://github.com/pydata/xarray/issues/7388#issuecomment-1503827455 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85ZopX_ markelg 6883049 2023-04-11T17:38:51Z 2023-04-11T17:38:51Z CONTRIBUTOR

Hi. I updated the branch and created a fresh python environment with the idea of writing another, final test for this. However before doing it I run the test suite, and got some bad HDF5 errors in test_backends.py::test_open_mfdataset_manyfiles[netcdf4-20-True-None-5]

#000: H5A.c line 528 in H5Aopen_by_name(): can't open attribute major: Attribute minor: Can't open object #001: H5VLcallback.c line 1091 in H5VL_attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #002: H5VLcallback.c line 1058 in H5VL__attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #003: H5VLnative_attr.c line 130 in H5VL__native_attr_open(): can't open attribute major: Attribute minor: Can't open object #004: H5Aint.c line 545 in H5A__open_by_name(): unable to load attribute info from object header major: Attribute minor: Unable to initialize object #005: H5Oattribute.c line 494 in H5O__attr_open_by_name(): can't locate attribute: '_QuantizeBitGroomNumberOfSignificantDigits' major: Attribute minor: Object not found HDF5-DIAG: Error detected in HDF5 (1.12.2) thread 1: #000: H5A.c line 528 in H5Aopen_by_name(): can't open attribute major: Attribute minor: Can't open object #001: H5VLcallback.c line 1091 in H5VL_attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #002: H5VLcallback.c line 1058 in H5VL__attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #003: H5VLnative_attr.c line 130 in H5VL__native_attr_open(): can't open attribute major: Attribute minor: Can't open object #004: H5Aint.c line 545 in H5A__open_by_name(): unable to load attribute info from object header major: Attribute minor: Unable to initialize object #005: H5Oattribute.c line 494 in H5O__attr_open_by_name(): can't locate attribute: '_QuantizeGranularBitRoundNumberOfSignificantDigits' major: Attribute minor: Object not found HDF5-DIAG: Error detected in HDF5 (1.12.2) thread 1: #000: H5A.c line 528 in H5Aopen_by_name(): can't open attribute major: Attribute minor: Can't open object #001: H5VLcallback.c line 1091 in H5VL_attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #002: H5VLcallback.c line 1058 in H5VL__attr_open(): attribute open failed major: Virtual Object Layer minor: Can't open object #003: H5VLnative_attr.c line 130 in H5VL__native_attr_open(): can't open attribute major: Attribute minor: Can't open object #004: H5Aint.c line 545 in H5A__open_by_name(): unable to load attribute info from object header major: Attribute minor: Unable to initialize object #005: H5Oattribute.c line 494 in H5O__attr_open_by_name(): can't locate attribute: '_QuantizeBitRoundNumberOfSignificantBits' major: Attribute minor: Object not found

I am not sure what is going on. It seems that the currently resolved netcdf4-hdf5 versions do not like the default parameters we are supplying. My environment is

```

Name Version Build Channel

_libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_gnu conda-forge affine 2.4.0 pyhd8ed1ab_0 conda-forge aiobotocore 2.5.0 pyhd8ed1ab_0 conda-forge aiohttp 3.8.4 py310h1fa729e_0 conda-forge aioitertools 0.11.0 pyhd8ed1ab_0 conda-forge aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge antlr-python-runtime 4.7.2 py310hff52083_1003 conda-forge asciitree 0.3.3 py_2 conda-forge async-timeout 4.0.2 pyhd8ed1ab_0 conda-forge attrs 22.2.0 pyh71513ae_0 conda-forge backports.zoneinfo 0.2.1 py310hff52083_7 conda-forge beautifulsoup4 4.12.2 pyha770c72_0 conda-forge blosc 1.21.3 hafa529b_0 conda-forge boost-cpp 1.78.0 h5adbc97_2 conda-forge boto3 1.26.76 pyhd8ed1ab_0 conda-forge botocore 1.29.76 pyhd8ed1ab_0 conda-forge bottleneck 1.3.7 py310h0a54255_0 conda-forge brotli 1.0.9 h166bdaf_8 conda-forge brotli-bin 1.0.9 h166bdaf_8 conda-forge brotlipy 0.7.0 py310h5764c6d_1005 conda-forge bzip2 1.0.8 h7f98852_4 conda-forge c-ares 1.18.1 h7f98852_0 conda-forge ca-certificates 2022.12.7 ha878542_0 conda-forge cached-property 1.5.2 hd8ed1ab_1 conda-forge cached_property 1.5.2 pyha770c72_1 conda-forge cairo 1.16.0 ha61ee94_1014 conda-forge cartopy 0.21.1 py310hcb7e713_0 conda-forge cdat_info 8.2.1 pyhd8ed1ab_2 conda-forge cdms2 3.1.5 py310hb9168da_16 conda-forge cdtime 3.1.4 py310h87e304a_8 conda-forge certifi 2022.12.7 pyhd8ed1ab_0 conda-forge cf-units 3.1.1 py310hde88566_2 conda-forge cffi 1.15.1 py310h255011f_3 conda-forge cfgrib 0.9.10.3 pyhd8ed1ab_0 conda-forge cfgv 3.3.1 pyhd8ed1ab_0 conda-forge cfitsio 4.2.0 hd9d235c_0 conda-forge cftime 1.6.2 py310hde88566_1 conda-forge charset-normalizer 2.1.1 pyhd8ed1ab_0 conda-forge click 8.1.3 unix_pyhd8ed1ab_2 conda-forge click-plugins 1.1.1 py_0 conda-forge cligj 0.7.2 pyhd8ed1ab_1 conda-forge cloudpickle 2.2.1 pyhd8ed1ab_0 conda-forge colorama 0.4.6 pyhd8ed1ab_0 conda-forge contourpy 1.0.7 py310hdf3cbec_0 conda-forge coverage 7.2.3 py310h1fa729e_0 conda-forge cryptography 40.0.1 py310h34c0648_0 conda-forge curl 7.88.1 hdc1c0ab_1 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0 conda-forge fonts-conda-forge 1 0 conda-forge fonttools 4.39.3 py310h1fa729e_0 conda-forge freeglut 3.2.2 h9c3ff4c_1 conda-forge freetype 2.12.1 hca18f0e_1 conda-forge freexl 1.0.6 h166bdaf_1 conda-forge frozenlist 1.3.3 py310h5764c6d_0 conda-forge fsspec 2023.4.0 pyh1a96a4e_0 conda-forge future 0.18.3 pyhd8ed1ab_0 conda-forge g2clib 1.6.3 hbecde78_1 conda-forge geos 3.11.1 h27087fc_0 conda-forge geotiff 1.7.1 h7a142b4_6 conda-forge gettext 0.21.1 h27087fc_0 conda-forge giflib 5.2.1 h0b41bf4_3 conda-forge h5netcdf 1.1.0 pyhd8ed1ab_1 conda-forge h5py 3.8.0 nompi_py310h0311031_100 conda-forge hdf4 4.2.15 h9772cbc_5 conda-forge hdf5 1.12.2 nompi_h4df4325_101 conda-forge heapdict 1.0.1 py_0 conda-forge hypothesis 6.71.0 pyha770c72_0 conda-forge icu 70.1 h27087fc_0 conda-forge identify 2.5.22 pyhd8ed1ab_0 conda-forge idna 3.4 pyhd8ed1ab_0 conda-forge importlib-metadata 6.3.0 pyha770c72_0 conda-forge importlib_metadata 6.3.0 hd8ed1ab_0 conda-forge importlib_resources 5.12.0 pyhd8ed1ab_0 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libpq 15.2 hb675445_0 conda-forge librttopo 1.1.0 ha49c73b_12 conda-forge libspatialite 5.0.1 h221c8f1_23 conda-forge libsqlite 3.40.0 h753d276_0 conda-forge libssh2 1.10.0 hf14f497_3 conda-forge libstdcxx-ng 12.2.0 h46fd767_19 conda-forge libtiff 4.5.0 h6adf6a1_2 conda-forge libuuid 2.38.1 h0b41bf4_0 conda-forge libwebp-base 1.3.0 h0b41bf4_0 conda-forge libxcb 1.13 h7f98852_1004 conda-forge libxml2 2.10.3 hca2bb57_4 conda-forge libxslt 1.1.37 h873f0b0_0 conda-forge libzip 1.9.2 hc929e4a_1 conda-forge libzlib 1.2.13 h166bdaf_4 conda-forge llvmlite 0.39.1 py310h58363a5_1 conda-forge locket 1.0.0 pyhd8ed1ab_0 conda-forge lxml 4.9.2 py310hbdc0903_0 conda-forge lz4-c 1.9.4 hcb278e6_0 conda-forge markupsafe 2.1.2 py310h1fa729e_0 conda-forge matplotlib-base 3.7.1 py310he60537e_0 conda-forge msgpack-python 1.0.5 py310hdf3cbec_0 conda-forge multidict 6.0.4 py310h1fa729e_0 conda-forge munkres 1.1.4 pyh9f0ad1d_0 conda-forge nbformat 5.8.0 pyhd8ed1ab_0 conda-forge nc-time-axis 1.4.1 pyhd8ed1ab_0 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conda-forge pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge platformdirs 3.2.0 pyhd8ed1ab_0 conda-forge pluggy 1.0.0 pyhd8ed1ab_5 conda-forge pooch 1.7.0 pyha770c72_3 conda-forge poppler 23.03.0 h091648b_0 conda-forge poppler-data 0.4.12 hd8ed1ab_0 conda-forge postgresql 15.2 h3248436_0 conda-forge pre-commit 3.2.2 pyha770c72_0 conda-forge proj 9.1.1 h8ffa02c_2 conda-forge pseudonetcdf 3.2.2 pyhd8ed1ab_0 conda-forge psutil 5.9.4 py310h5764c6d_0 conda-forge pthread-stubs 0.4 h36c2ea0_1001 conda-forge pycparser 2.21 pyhd8ed1ab_0 conda-forge pydap 3.4.0 pyhd8ed1ab_0 conda-forge pyopenssl 23.1.1 pyhd8ed1ab_0 conda-forge pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge pyproj 3.5.0 py310h15e2413_0 conda-forge pyrsistent 0.19.3 py310h1fa729e_0 conda-forge pyshp 2.3.1 pyhd8ed1ab_0 conda-forge pysocks 1.7.1 pyha2e5f31_6 conda-forge pytest 7.3.0 pyhd8ed1ab_0 conda-forge pytest-cov 4.0.0 pyhd8ed1ab_0 conda-forge pytest-env 0.8.1 pyhd8ed1ab_0 conda-forge pytest-xdist 3.2.1 pyhd8ed1ab_0 conda-forge python 3.10.10 he550d4f_0_cpython conda-forge python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge python-eccodes 1.5.1 py310h0a54255_0 conda-forge python-fastjsonschema 2.16.3 pyhd8ed1ab_0 conda-forge python-xxhash 3.2.0 py310h1fa729e_0 conda-forge python_abi 3.10 3_cp310 conda-forge pytz 2023.3 pyhd8ed1ab_0 conda-forge pyyaml 6.0 py310h5764c6d_5 conda-forge rasterio 1.3.6 py310h3e853a9_0 conda-forge readline 8.2 h8228510_1 conda-forge requests 2.28.2 pyhd8ed1ab_1 conda-forge s3transfer 0.6.0 pyhd8ed1ab_0 conda-forge scipy 1.10.1 py310h8deb116_0 conda-forge seaborn 0.12.2 hd8ed1ab_0 conda-forge seaborn-base 0.12.2 pyhd8ed1ab_0 conda-forge setuptools 67.6.1 pyhd8ed1ab_0 conda-forge shapely 2.0.1 py310h8b84c32_0 conda-forge six 1.16.0 pyh6c4a22f_0 conda-forge snappy 1.1.10 h9fff704_0 conda-forge snuggs 1.4.7 py_0 conda-forge sortedcontainers 2.4.0 pyhd8ed1ab_0 conda-forge soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge sparse 0.14.0 pyhd8ed1ab_0 conda-forge sqlite 3.40.0 h4ff8645_0 conda-forge 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h7f98852_1002 conda-forge xorg-kbproto 1.0.7 h7f98852_1002 conda-forge xorg-libice 1.0.10 h7f98852_0 conda-forge xorg-libsm 1.2.3 hd9c2040_1000 conda-forge xorg-libx11 1.8.4 h0b41bf4_0 conda-forge xorg-libxau 1.0.9 h7f98852_0 conda-forge xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge xorg-libxext 1.3.4 h0b41bf4_2 conda-forge xorg-libxfixes 5.0.3 h7f98852_1004 conda-forge xorg-libxi 1.7.10 h7f98852_0 conda-forge xorg-libxrender 0.9.10 h7f98852_1003 conda-forge xorg-renderproto 0.11.1 h7f98852_1002 conda-forge xorg-xextproto 7.3.0 h0b41bf4_1003 conda-forge xorg-xproto 7.0.31 h7f98852_1007 conda-forge xxhash 0.8.1 h0b41bf4_0 conda-forge xz 5.2.6 h166bdaf_0 conda-forge yaml 0.2.5 h7f98852_2 conda-forge yarl 1.8.2 py310h5764c6d_0 conda-forge zarr 2.14.2 pyhd8ed1ab_0 conda-forge zict 2.2.0 pyhd8ed1ab_0 conda-forge zipp 3.15.0 pyhd8ed1ab_0 conda-forge zlib 1.2.13 h166bdaf_4 conda-forge zstd 1.5.2 h3eb15da_6 conda-forge ```

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  Xarray does not support full range of netcdf-python compression options 1503046820
1441513675 https://github.com/pydata/xarray/issues/7388#issuecomment-1441513675 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85V68DL markelg 6883049 2023-02-23T10:23:21Z 2023-02-23T10:23:21Z CONTRIBUTOR

With the PR the test above works, and also bzip2. I can't get it to apply blosc filters for some reason, it works but it does not really apply them. This is the full snippet I am using:

``` import xarray as xr import numpy as np

shape = (10, 20) chunksizes = (1, 10)

encoding = { 'compression': 'bzip2', 'shuffle': True, 'complevel': 8, 'fletcher32': False, 'contiguous': False, 'chunksizes': chunksizes }

da = xr.DataArray( data=np.random.rand(*shape), dims=['y', 'x'], name="foo", attrs={"bar": "baz"} ) da.encoding = encoding ds = da.to_dataset()

fname = "test.nc" ds.to_netcdf(fname, engine="netcdf4", mode="w")

with xr.open_dataset(fname, engine="netcdf4") as ds1: print(ds1.foo.encoding) ```

Also, I was not able to make the conda environment in ci/environment.yml to resolve libnetcdf 4.9.1. I had to build an environment on my own. I also added the hdf5 filters

name: xarray-tests channels: - conda-forge dependencies: - _libgcc_mutex=0.1=conda_forge - _openmp_mutex=4.5=2_gnu - blosc=1.21.3=hafa529b_0 - blosc-hdf5-plugin=1.0.0=h8b9aba8_4 - bzip2=1.0.8=h7f98852_4 - c-ares=1.18.1=h7f98852_0 - ca-certificates=2022.12.7=ha878542_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - cftime=1.6.2=py311h4c7f6c3_1 - curl=7.88.1=hdc1c0ab_0 - h5py=3.8.0=nompi_py311h1db17ec_100 - hdf4=4.2.15=h9772cbc_5 - hdf5=1.12.2=nompi_h4df4325_101 - hdf5-external-filter-plugins=0.1.0=ha770c72_9 - hdf5-external-filter-plugins-bitshuffle=0.1.0=h6ca952b_9 - hdf5-external-filter-plugins-bzip2=0.1.0=hd13e76c_9 - hdf5-external-filter-plugins-lz4=0.1.0=h6ca952b_9 - hdf5plugin=4.1.1=py311hc7375e3_0 - icu=70.1=h27087fc_0 - jpeg=9e=h0b41bf4_3 - keyutils=1.6.1=h166bdaf_0 - krb5=1.20.1=h81ceb04_0 - ld_impl_linux-64=2.40=h41732ed_0 - libaec=1.0.6=hcb278e6_1 - libblas=3.9.0=16_linux64_openblas - libcblas=3.9.0=16_linux64_openblas - libcurl=7.88.1=hdc1c0ab_0 - libedit=3.1.20191231=he28a2e2_2 - libev=4.33=h516909a_1 - libffi=3.4.2=h7f98852_5 - libgcc-ng=12.2.0=h65d4601_19 - libgfortran-ng=12.2.0=h69a702a_19 - libgfortran5=12.2.0=h337968e_19 - libgomp=12.2.0=h65d4601_19 - libiconv=1.17=h166bdaf_0 - liblapack=3.9.0=16_linux64_openblas - libnetcdf=4.9.1=nompi_h34a3ff0_100 - libnghttp2=1.51.0=hff17c54_0 - libnsl=2.0.0=h7f98852_0 - libopenblas=0.3.21=pthreads_h78a6416_3 - libsqlite=3.40.0=h753d276_0 - libssh2=1.10.0=hf14f497_3 - libstdcxx-ng=12.2.0=h46fd767_19 - libuuid=2.32.1=h7f98852_1000 - libxml2=2.10.3=h7463322_0 - libzip=1.9.2=hc929e4a_1 - libzlib=1.2.13=h166bdaf_4 - lz4-c=1.9.4=hcb278e6_0 - ncurses=6.3=h27087fc_1 - netcdf4=1.6.2=nompi_py311ha396515_101 - numpy=1.24.2=py311h8e6699e_0 - openssl=3.0.8=h0b41bf4_0 - pip=23.0.1=pyhd8ed1ab_0 - python=3.11.0=he550d4f_1_cpython - python_abi=3.11=3_cp311 - readline=8.1.2=h0f457ee_0 - setuptools=67.4.0=pyhd8ed1ab_0 - snappy=1.1.9=hbd366e4_2 - tk=8.6.12=h27826a3_0 - tzdata=2022g=h191b570_0 - wheel=0.38.4=pyhd8ed1ab_0 - xz=5.2.6=h166bdaf_0 - zlib=1.2.13=h166bdaf_4 - zstd=1.5.2=h3eb15da_6 - pip: - packaging==23.0 - pandas==1.5.3 - python-dateutil==2.8.2 - pytz==2022.7.1 - six==1.16.0 - xarray==0.1.dev4485+gf8a0014

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  Xarray does not support full range of netcdf-python compression options 1503046820
1383643668 https://github.com/pydata/xarray/issues/7388#issuecomment-1383643668 https://api.github.com/repos/pydata/xarray/issues/7388 IC_kwDOAMm_X85SeLoU markelg 6883049 2023-01-16T08:15:41Z 2023-01-16T08:15:41Z CONTRIBUTOR

I'll have a look. Sorry about that, I guess we assumed that encoding was passed with "**kwargs". I did not try it with netcdf-c 4.9.x since is it not yet available in conda-forge and I did not find the time to compile it.

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  Xarray does not support full range of netcdf-python compression options 1503046820

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