html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/6854#issuecomment-1538068408,https://api.github.com/repos/pydata/xarray/issues/6854,1538068408,IC_kwDOAMm_X85brQ-4,302469,2023-05-08T09:42:08Z,2023-05-08T09:42:08Z,CONTRIBUTOR,I think this was fixed by https://github.com/Unidata/netcdf-c/issues/2573,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180
https://github.com/pydata/xarray/issues/6854#issuecomment-1382625582,https://api.github.com/repos/pydata/xarray/issues/6854,1382625582,IC_kwDOAMm_X85SaTEu,302469,2023-01-14T01:33:08Z,2023-01-14T01:33:08Z,CONTRIBUTOR,"Building against netcdf with the patch backported by @opoplawski, I now get a single failure:
```
_________________________ TestNCZarr.test_open_nczarr __________________________
[gw3] linux -- Python 3.11.1 /usr/bin/python3
zarr_obj = <zarr.core.Array '/dim2' (9,) float64 read-only>
dimension_key = '_ARRAY_DIMENSIONS', try_nczarr = True
def _get_zarr_dims_and_attrs(zarr_obj, dimension_key, try_nczarr):
# Zarr arrays do not have dimensions. To get around this problem, we add
# an attribute that specifies the dimension. We have to hide this attribute
# when we send the attributes to the user.
# zarr_obj can be either a zarr group or zarr array
try:
# Xarray-Zarr
> dimensions = zarr_obj.attrs[dimension_key]
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:183:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <zarr.attrs.Attributes object at 0x7f697d934ad0>
item = '_ARRAY_DIMENSIONS'
def __getitem__(self, item):
> return self.asdict()[item]
E KeyError: '_ARRAY_DIMENSIONS'
/usr/lib/python3.11/site-packages/zarr/attrs.py:74: KeyError
During handling of the above exception, another exception occurred:
zarr_obj = <zarr.core.Array '/dim2' (9,) float64 read-only>
dimension_key = '_ARRAY_DIMENSIONS', try_nczarr = True
def _get_zarr_dims_and_attrs(zarr_obj, dimension_key, try_nczarr):
# Zarr arrays do not have dimensions. To get around this problem, we add
# an attribute that specifies the dimension. We have to hide this attribute
# when we send the attributes to the user.
# zarr_obj can be either a zarr group or zarr array
try:
# Xarray-Zarr
dimensions = zarr_obj.attrs[dimension_key]
except KeyError as e:
if not try_nczarr:
raise KeyError(
f""Zarr object is missing the attribute `{dimension_key}`, which is ""
""required for xarray to determine variable dimensions.""
) from e
# NCZarr defines dimensions through metadata in .zarray
zarray_path = os.path.join(zarr_obj.path, "".zarray"")
zarray = json.loads(zarr_obj.store[zarray_path])
try:
# NCZarr uses Fully Qualified Names
dimensions = [
> os.path.basename(dim) for dim in zarray[""_NCZARR_ARRAY""][""dimrefs""]
]
E KeyError: '_NCZARR_ARRAY'
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:197: KeyError
The above exception was the direct cause of the following exception:
self = <xarray.tests.test_backends.TestNCZarr object at 0x7f697ed62f10>
def test_open_nczarr(self) -> None:
with create_tmp_file(suffix="".zarr"") as tmp:
expected = self._create_nczarr(tmp)
> actual = xr.open_zarr(tmp, consolidated=False)
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/tests/test_backends.py:5741:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:819: in open_zarr
ds = open_dataset(
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/api.py:540: in open_dataset
backend_ds = backend.open_dataset(
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:897: in open_dataset
ds = store_entrypoint.open_dataset(
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/store.py:28: in open_dataset
vars, attrs = store.load()
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/common.py:128: in load
(_decode_variable_name(k), v) for k, v in self.get_variables().items()
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:480: in get_variables
return FrozenDict(
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/core/utils.py:469: in FrozenDict
return Frozen(dict(*args, **kwargs))
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:481: in <genexpr>
(k, self.open_store_variable(k, v)) for k, v in self.zarr_group.arrays()
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:457: in open_store_variable
dimensions, attributes = _get_zarr_dims_and_attrs(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
zarr_obj = <zarr.core.Array '/dim2' (9,) float64 read-only>
dimension_key = '_ARRAY_DIMENSIONS', try_nczarr = True
def _get_zarr_dims_and_attrs(zarr_obj, dimension_key, try_nczarr):
# Zarr arrays do not have dimensions. To get around this problem, we add
# an attribute that specifies the dimension. We have to hide this attribute
# when we send the attributes to the user.
# zarr_obj can be either a zarr group or zarr array
try:
# Xarray-Zarr
dimensions = zarr_obj.attrs[dimension_key]
except KeyError as e:
if not try_nczarr:
raise KeyError(
f""Zarr object is missing the attribute `{dimension_key}`, which is ""
""required for xarray to determine variable dimensions.""
) from e
# NCZarr defines dimensions through metadata in .zarray
zarray_path = os.path.join(zarr_obj.path, "".zarray"")
zarray = json.loads(zarr_obj.store[zarray_path])
try:
# NCZarr uses Fully Qualified Names
dimensions = [
os.path.basename(dim) for dim in zarray[""_NCZARR_ARRAY""][""dimrefs""]
]
except KeyError as e:
> raise KeyError(
f""Zarr object is missing the attribute `{dimension_key}` and the NCZarr metadata, ""
""which are required for xarray to determine variable dimensions.""
) from e
E KeyError: 'Zarr object is missing the attribute `_ARRAY_DIMENSIONS` and the NCZarr metadata, which are required for xarray to determine variable dimensions.'
/builddir/build/BUILDROOT/python-xarray-2022.12.0-1.fc38.x86_64/usr/lib/python3.11/site-packages/xarray/backends/zarr.py:200: KeyError
```
Does that look like a problem in netcdf or a problem in xarray here?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180
https://github.com/pydata/xarray/issues/6854#issuecomment-1330143162,https://api.github.com/repos/pydata/xarray/issues/6854,1330143162,IC_kwDOAMm_X85PSF-6,302469,2022-11-29T06:21:17Z,2022-11-29T06:21:17Z,CONTRIBUTOR,"I could, but I'm not sure what to try. I tried running https://github.com/Unidata/netcdf4-python/blob/master/examples/tutorial.py with those versions and that worked without issue.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180
https://github.com/pydata/xarray/issues/6854#issuecomment-1328135253,https://api.github.com/repos/pydata/xarray/issues/6854,1328135253,IC_kwDOAMm_X85PKbxV,302469,2022-11-26T23:57:28Z,2022-11-26T23:57:28Z,CONTRIBUTOR,Still broken in 2022.11.0; any ideas what to look at here?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180
https://github.com/pydata/xarray/issues/6854#issuecomment-1200757563,https://api.github.com/repos/pydata/xarray/issues/6854,1200757563,IC_kwDOAMm_X85Hkhs7,302469,2022-08-01T06:14:42Z,2022-08-01T06:14:42Z,CONTRIBUTOR,"Backporting netcdf 4.9.0 to Fedora 36 also OOMs, so there's something weird there, but not sure if it's netCDF, or something that xarray is doing.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180
https://github.com/pydata/xarray/issues/6854#issuecomment-1200657104,https://api.github.com/repos/pydata/xarray/issues/6854,1200657104,IC_kwDOAMm_X85HkJLQ,302469,2022-08-01T03:35:39Z,2022-08-01T03:35:39Z,CONTRIBUTOR,"Hmm, I seem to be able to build on Fedora 36 (instead of Rawhide above), with the following versions:
<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.5 (main, Jun 9 2022, 00:00:00) [GCC 12.1.1 20220507 (Red Hat 12.1.1-1)]
python-bits: 64
OS: Linux
OS-release: 5.17.13-300.fc36.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: C.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.12.1
libnetcdf: 4.8.1
xarray: 2022.6.0
pandas: 1.3.5
numpy: 1.22.0
scipy: 1.8.1
netCDF4: 1.5.8
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.11.3
cftime: 1.5.2
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.2.10
cfgrib: None
iris: None
bottleneck: 1.3.2
dask: 2022.05.0
distributed: None
matplotlib: 3.5.2
cartopy: None
seaborn: 0.11.1
numbagg: None
fsspec: 2022.5.0
cupy: None
pint: 0.16.1
sparse: None
flox: None
numpy_groupies: None
setuptools: 59.6.0
pip: 21.3.1
conda: None
pytest: 6.2.5
IPython: None
sphinx: 4.4.0
</details>","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1323734180