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/pull/7173#issuecomment-1280906370,https://api.github.com/repos/pydata/xarray/issues/7173,1280906370,IC_kwDOAMm_X85MWRSC,14371165,2022-10-17T13:57:47Z,2024-03-20T23:12:49Z,MEMBER,"**Scatter vs. Lines:** ![image](https://user-images.githubusercontent.com/14371165/196196043-2485945e-29d7-4ff8-9321-3faca68d0dae.png)
```python ds = xr.tutorial.scatter_example_dataset(seed=42) hue_ = ""y"" x_ = ""y"" size_=""y"" z_ = ""z"" fig = plt.figure() ax = fig.add_subplot(1, 2, 1, projection='3d') ds.A.sel(w=""one"").plot.lines(x=x_, z=z_, hue=hue_, linewidth=size_, ax=ax) ax = fig.add_subplot(1, 2, 2, projection='3d') ds.A.sel(w=""one"").plot.scatter(x=x_, z=z_, hue=hue_, markersize=size_, ax=ax) ```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1410608825 https://github.com/pydata/xarray/pull/7891#issuecomment-1575756825,https://api.github.com/repos/pydata/xarray/issues/7891,1575756825,IC_kwDOAMm_X85d7CQZ,14371165,2023-06-04T22:29:18Z,2023-06-04T22:29:18Z,MEMBER,You could use `DataArray.round` to round to significant decimals.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1740268634 https://github.com/pydata/xarray/pull/7821#issuecomment-1570164833,https://api.github.com/repos/pydata/xarray/issues/7821,1570164833,IC_kwDOAMm_X85dltBh,14371165,2023-05-31T12:43:30Z,2023-05-31T12:43:30Z,MEMBER,Thanks @mgunyho !,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1698626185 https://github.com/pydata/xarray/pull/7875#issuecomment-1563788348,https://api.github.com/repos/pydata/xarray/issues/7875,1563788348,IC_kwDOAMm_X85dNYQ8,14371165,2023-05-26T04:17:07Z,2023-05-26T04:18:08Z,MEMBER,"`cos` is a float operation so I would lean towards using a isclose-check: `xr.testing.assert_allclose(a + 1, np.cos(a))`.","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1726529405 https://github.com/pydata/xarray/issues/7856#issuecomment-1556198984,https://api.github.com/repos/pydata/xarray/issues/7856,1556198984,IC_kwDOAMm_X85cwbZI,14371165,2023-05-21T14:51:55Z,2023-05-21T14:51:55Z,MEMBER,"Nope, I have not tried that. I suspect things will just self heal then considering the CI without understanding the root cause. Looking at the backends; we initialize a dict here: https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/backends/common.py#L435 Stores each of our entrypoints like this: https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/backends/h5netcdf_.py#L438 Then we append the local and other entrypoints together here: https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/backends/plugins.py#L106-L116 But `load_chunkmanagers` doesn't really seem to append from a dict: https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/core/parallelcompat.py#L48-L62 Why do the backends use the `BACKEND_ENTRYPOINTS` strategy? To avoid these cases? Or something else?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1718410975 https://github.com/pydata/xarray/issues/7856#issuecomment-1556191288,https://api.github.com/repos/pydata/xarray/issues/7856,1556191288,IC_kwDOAMm_X85cwZg4,14371165,2023-05-21T14:17:30Z,2023-05-21T14:17:30Z,MEMBER,"The CI recreates its entire environment all the time and I don't? ```python from xarray.core.parallelcompat import list_chunkmanagers list_chunkmanagers() Out[1]: {} ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1718410975 https://github.com/pydata/xarray/pull/7844#issuecomment-1556160022,https://api.github.com/repos/pydata/xarray/issues/7844,1556160022,IC_kwDOAMm_X85cwR4W,14371165,2023-05-21T11:54:28Z,2023-05-21T11:55:48Z,MEMBER,"``` before after ratio [05c7888d] [d135ab97] - 2.47±0.02s 806±6ms 0.33 pandas.ToDataFrameDask.time_to_dataframe ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1710752209 https://github.com/pydata/xarray/issues/7856#issuecomment-1556114932,https://api.github.com/repos/pydata/xarray/issues/7856,1556114932,IC_kwDOAMm_X85cwG30,14371165,2023-05-21T08:13:47Z,2023-05-21T08:13:47Z,MEMBER,"Our backends are stored in a dict like this: `BACKEND_ENTRYPOINTS[""h5netcdf""] = (""h5netcdf"", H5netcdfBackendEntrypoint)`. Is it something similar `daskmanager` needs to do?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1718410975 https://github.com/pydata/xarray/issues/7856#issuecomment-1556113793,https://api.github.com/repos/pydata/xarray/issues/7856,1556113793,IC_kwDOAMm_X85cwGmB,14371165,2023-05-21T08:09:09Z,2023-05-21T08:09:09Z,MEMBER,cc @TomNicholas ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1718410975 https://github.com/pydata/xarray/pull/7824#issuecomment-1547017905,https://api.github.com/repos/pydata/xarray/issues/7824,1547017905,IC_kwDOAMm_X85cNZ6x,14371165,2023-05-14T22:44:06Z,2023-05-15T08:40:51Z,MEMBER,"Think I'll stop here. @alimanfoo, feel free to try this out if you have the time. Results: ``` before after ratio [964d350a] [86ef9540] - 117±2ms 65.6±0.9ms 0.56 groupby.Resample.time_agg_large_num_groups('sum', 2, False) - 117±2ms 65.3±0.7ms 0.56 groupby.ResampleCFTime.time_agg_large_num_groups('sum', 2, False) - 113±1ms 62.0±0.4ms 0.55 groupby.ResampleCFTime.time_agg_large_num_groups('sum', 1, False) - 112±2ms 61.4±0.5ms 0.55 groupby.Resample.time_agg_large_num_groups('sum', 1, False) - 8.50±0.2ms 1.61±0.01ms 0.19 combine.Combine1d.time_combine_by_coords - 1.81±0.02s 224±2ms 0.12 combine.Combine1dDask.time_combine_by_coords SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY. PERFORMANCE INCREASED. ```","{""total_count"": 4, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 2, ""eyes"": 0}",,1699099029 https://github.com/pydata/xarray/issues/7833#issuecomment-1543284025,https://api.github.com/repos/pydata/xarray/issues/7833,1543284025,IC_kwDOAMm_X85b_KU5,14371165,2023-05-11T03:36:34Z,2023-05-11T03:36:34Z,MEMBER,"I've noticed this as well, see #7824.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1704950804 https://github.com/pydata/xarray/pull/7822#issuecomment-1537345671,https://api.github.com/repos/pydata/xarray/issues/7822,1537345671,IC_kwDOAMm_X85bogiH,14371165,2023-05-07T07:34:45Z,2023-05-07T07:34:45Z,MEMBER,"Thanks, @mgunyho !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1698632575 https://github.com/pydata/xarray/pull/7820#issuecomment-1536656773,https://api.github.com/repos/pydata/xarray/issues/7820,1536656773,IC_kwDOAMm_X85bl4WF,14371165,2023-05-05T19:03:08Z,2023-05-05T19:03:08Z,MEMBER,Indeed is pint.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1697987899 https://github.com/pydata/xarray/issues/7707#issuecomment-1534920140,https://api.github.com/repos/pydata/xarray/issues/7707,1534920140,IC_kwDOAMm_X85bfQXM,14371165,2023-05-04T14:50:01Z,2023-05-04T14:50:01Z,MEMBER,"Lots of pint errors with version 0.21, @keewis. I think pint 0.20.1 worked well?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1650481625 https://github.com/pydata/xarray/pull/7795#issuecomment-1530345382,https://api.github.com/repos/pydata/xarray/issues/7795,1530345382,IC_kwDOAMm_X85bNzem,14371165,2023-05-01T21:41:56Z,2023-05-01T21:41:56Z,MEMBER,"Feels like it worked quite recently, has something changed? Benchmarks still works on the flox side.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1688781350 https://github.com/pydata/xarray/pull/7787#issuecomment-1530096971,https://api.github.com/repos/pydata/xarray/issues/7787,1530096971,IC_kwDOAMm_X85bM21L,14371165,2023-05-01T19:13:57Z,2023-05-01T19:13:57Z,MEMBER,"Thanks, @ksunden and @tacaswell for the guidance we'll tackle these in separate PRs, see #7802.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1684281101 https://github.com/pydata/xarray/pull/7801#issuecomment-1529823367,https://api.github.com/repos/pydata/xarray/issues/7801,1529823367,IC_kwDOAMm_X85bL0CH,14371165,2023-05-01T15:15:30Z,2023-05-01T15:15:30Z,MEMBER,"Thanks, @dstansby !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1690872248 https://github.com/pydata/xarray/pull/5704#issuecomment-1528693660,https://api.github.com/repos/pydata/xarray/issues/5704,1528693660,IC_kwDOAMm_X85bHgOc,14371165,2023-04-29T06:56:37Z,2023-04-29T06:58:26Z,MEMBER,"Those issues indeed has to be fixed if opening files lazily is the _only_ option for xarray. But xarray could also accept that `chunks=None` will (for now) load all the files to memory. If that's ok we can merge this now I believe. I suspect there are a few in-memory users out there that could make use of this.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,970245117 https://github.com/pydata/xarray/issues/7794#issuecomment-1528527292,https://api.github.com/repos/pydata/xarray/issues/7794,1528527292,IC_kwDOAMm_X85bG3m8,14371165,2023-04-29T02:39:19Z,2023-04-29T02:39:19Z,MEMBER,Why/where do you get a cftime._cftime.Datetime360Day ? It is deprecated according to cftime.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1688779793 https://github.com/pydata/xarray/issues/7792#issuecomment-1526232602,https://api.github.com/repos/pydata/xarray/issues/7792,1526232602,IC_kwDOAMm_X85a-HYa,14371165,2023-04-27T19:21:54Z,2023-04-27T19:22:26Z,MEMBER,"It's because opening several files requires concatenating the files. xarray does not have any machinery to do that lazily without dask, so all your files will be loaded to memory. Maybe that's ok for you? If the files are small it should be fine. See #5704 for more discussion.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1687297423 https://github.com/pydata/xarray/pull/7787#issuecomment-1523703079,https://api.github.com/repos/pydata/xarray/issues/7787,1523703079,IC_kwDOAMm_X85a0d0n,14371165,2023-04-26T16:22:57Z,2023-04-26T16:22:57Z,MEMBER,"Realized I actually wanted to run mypy with the upstream packages. So added such a CI as well, but only when adding this label so that it doesn't mess with the scheduled runs and those results. I notice quite a few mypy errors from the plot parts. If you have any ideas @headtr1ck and @ksunden you're very welcome to push more PRs!
``` xarray/core/options.py:12: error: Cannot assign to a type [misc] xarray/core/options.py:12: error: Incompatible types in assignment (expression has type ""Type[str]"", variable has type ""Type[Colormap]"") [assignment] xarray/plot/utils.py:808: error: Argument 1 to ""set_xticks"" of ""_AxesBase"" has incompatible type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]""; expected ""Iterable[float]"" [arg-type] xarray/plot/utils.py:810: error: Argument 1 to ""set_yticks"" of ""_AxesBase"" has incompatible type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]""; expected ""Iterable[float]"" [arg-type] xarray/plot/utils.py:813: error: Argument 1 to ""set_xlim"" of ""_AxesBase"" has incompatible type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]""; expected ""Union[float, Tuple[float, float], None]"" [arg-type] xarray/plot/utils.py:815: error: Argument 1 to ""set_ylim"" of ""_AxesBase"" has incompatible type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]""; expected ""Union[float, Tuple[float, float], None]"" [arg-type] Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Installing missing stub packages: /home/runner/micromamba-root/envs/xarray-tests/bin/python -m pip install types-Pillow types-PyYAML types-Pygments types-babel types-colorama types-paramiko types-psutil types-pytz types-pywin32 types-setuptools types-urllib3 Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Found 154 errors in 10 files (checked 138 source files) xarray/plot/utils.py:1349: error: Unsupported operand types for * (""_SupportsArray[dtype[Any]]"" and ""float"") [operator] xarray/plot/utils.py:1349: error: Unsupported operand types for * (""_NestedSequence[_SupportsArray[dtype[Any]]]"" and ""float"") [operator] xarray/plot/utils.py:1349: error: Unsupported operand types for * (""_NestedSequence[Union[bool, int, float, complex, str, bytes]]"" and ""float"") [operator] xarray/plot/utils.py:1349: note: Left operand is of type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" xarray/plot/utils.py:1349: error: Unsupported operand types for * (""str"" and ""float"") [operator] xarray/plot/utils.py:1349: error: Unsupported operand types for * (""bytes"" and ""float"") [operator] xarray/plot/utils.py:1350: error: Item ""_SupportsArray[dtype[Any]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""_NestedSequence[_SupportsArray[dtype[Any]]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""int"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""float"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""complex"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""str"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""bytes"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1350: error: Item ""_NestedSequence[Union[bool, int, float, complex, str, bytes]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""_SupportsArray[dtype[Any]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""_NestedSequence[_SupportsArray[dtype[Any]]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""int"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""float"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""complex"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""str"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""bytes"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/utils.py:1351: error: Item ""_NestedSequence[Union[bool, int, float, complex, str, bytes]]"" of ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" has no attribute ""mask"" [union-attr] xarray/plot/facetgrid.py:684: error: ""FigureCanvasBase"" has no attribute ""get_renderer"" [attr-defined] xarray/plot/accessor.py:182: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:182: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:309: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:309: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:428: error: Overloaded function implementation cannot produce return type of signature 2 [misc] xarray/plot/accessor.py:428: error: Overloaded function implementation cannot produce return type of signature 3 [misc] xarray/plot/accessor.py:433: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:433: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:552: error: Overloaded function implementation cannot produce return type of signature 2 [misc] xarray/plot/accessor.py:552: error: Overloaded function implementation cannot produce return type of signature 3 [misc] xarray/plot/accessor.py:557: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:557: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:676: error: Overloaded function implementation cannot produce return type of signature 2 [misc] xarray/plot/accessor.py:676: error: Overloaded function implementation cannot produce return type of signature 3 [misc] xarray/plot/accessor.py:681: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:681: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:800: error: Overloaded function implementation cannot produce return type of signature 2 [misc] xarray/plot/accessor.py:800: error: Overloaded function implementation cannot produce return type of signature 3 [misc] xarray/plot/accessor.py:948: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:948: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:1075: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:1075: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/accessor.py:1190: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/accessor.py:1190: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:324: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:324: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:478: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:478: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""x"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""y"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""u"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""v"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""density"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""linewidth"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""color"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""cmap"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""norm"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""arrowsize"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""arrowstyle"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""minlength"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""transform"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""zorder"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""start_points"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""maxlength"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""integration_direction"" [misc] xarray/plot/dataset_plot.py:649: error: Function gets multiple values for keyword argument ""broken_streamlines"" [misc] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[float, Tuple[float, float]]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[str, Colormap, None]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[str, Normalize, None]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""float"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[str, ArrowStyle]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Optional[Transform]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Optional[float]"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Literal['forward', 'backward', 'both']"" [arg-type] xarray/plot/dataset_plot.py:649: error: Argument 1 has incompatible type ""*List[ndarray[Any, Any]]""; expected ""bool"" [arg-type] xarray/plot/dataset_plot.py:751: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataset_plot.py:751: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:718: error: Incompatible return value type (got ""Tuple[Union[ndarray[Any, Any], List[ndarray[Any, Any]]], ndarray[Any, Any], Union[BarContainer, Polygon, List[Union[BarContainer, Polygon]]]]"", expected ""Tuple[ndarray[Any, Any], ndarray[Any, Any], BarContainer]"") [return-value] xarray/plot/dataarray_plot.py:996: error: ""Axes"" has no attribute ""view_init"" [attr-defined] xarray/plot/dataarray_plot.py:1106: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:1106: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[Sequence[Union[Union[Tuple[float, float, float], str], Union[str, Tuple[float, float, float, float], Tuple[Union[Tuple[float, float, float], str], float], Tuple[Tuple[float, float, float, float], float]]]], Union[Union[Tuple[float, float, float], str], Union[str, Tuple[float, float, float, float], Tuple[Union[Tuple[float, float, float], str], float], Tuple[Tuple[float, float, float, float], float]]], None]"" [arg-type] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Optional[Union[str, Path, MarkerStyle]]"" [arg-type] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[str, Colormap, None]"" [arg-type] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[str, Normalize, None]"" [arg-type] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Optional[float]"" [arg-type] xarray/plot/dataarray_plot.py:1261: error: Argument 1 to ""scatter"" of ""Axes"" has incompatible type ""*List[ndarray[Any, Any]]""; expected ""Union[float, Sequence[float], None]"" [arg-type] xarray/plot/dataarray_plot.py:1615: error: ""Axes"" has no attribute ""set_zlabel"" [attr-defined] xarray/plot/dataarray_plot.py:1655: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:1655: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:1874: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:1874: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:2010: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:2010: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:2146: error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:2146: error: Overloaded function signatures 1 and 3 overlap with incompatible return types [misc] xarray/plot/dataarray_plot.py:2464: error: ""Axes"" has no attribute ""plot_surface"" [attr-defined] xarray/tests/test_plot.py:427: error: Value of type ""Union[_SupportsArray[dtype[Any]], _NestedSequence[_SupportsArray[dtype[Any]]], int, float, complex, str, bytes, _NestedSequence[Union[bool, int, float, complex, str, bytes]]]"" is not indexable [index] xarray/tests/test_plot.py:443: error: Module has no attribute ""viridis"" [attr-defined] xarray/tests/test_plot.py:457: error: ""None"" not callable [misc] xarray/tests/test_plot.py:462: error: ""None"" not callable [misc] xarray/tests/test_plot.py:465: error: ""None"" not callable [misc] xarray/tests/test_plot.py:471: error: Module has no attribute ""viridis"" [attr-defined] xarray/tests/test_plot.py:477: error: Module has no attribute ""viridis"" [attr-defined] xarray/tests/test_plot.py:482: error: Module has no attribute ""viridis"" [attr-defined] xarray/tests/test_plot.py:486: error: Module has no attribute ""viridis"" [attr-defined] xarray/tests/test_plot.py:493: error: ""None"" not callable [misc] xarray/tests/test_plot.py:498: error: ""None"" not callable [misc] xarray/tests/test_plot.py:501: error: ""None"" not callable [misc] xarray/tests/test_plot.py:931: error: Module has no attribute ""magma"" [attr-defined] xarray/tests/test_plot.py:933: error: Module has no attribute ""magma"" [attr-defined] xarray/tests/test_plot.py:1173: error: Module has no attribute ""RdBu"" [attr-defined] xarray/tests/test_plot.py:1746: error: Item ""Colormap"" of ""Optional[Colormap]"" has no attribute ""colors"" [union-attr] xarray/tests/test_plot.py:1746: error: Item ""None"" of ""Optional[Colormap]"" has no attribute ""colors"" [union-attr] xarray/tests/test_plot.py:1747: error: Item ""Colormap"" of ""Optional[Colormap]"" has no attribute ""colors"" [union-attr] xarray/tests/test_plot.py:1747: error: Item ""None"" of ""Optional[Colormap]"" has no attribute ""colors"" [union-attr] xarray/tests/test_plot.py:1749: error: Item ""Colormap"" of ""Optional[Colormap]"" has no attribute ""_rgba_over"" [union-attr] xarray/tests/test_plot.py:1749: error: Item ""None"" of ""Optional[Colormap]"" has no attribute ""_rgba_over"" [union-attr] xarray/tests/test_plot.py:1801: error: Item ""None"" of ""Optional[ndarray[Any, Any]]"" has no attribute ""size"" [union-attr] xarray/tests/test_plot.py:1952: error: Item ""None"" of ""Optional[ndarray[Any, Any]]"" has no attribute ""min"" [union-attr] xarray/tests/test_plot.py:1952: error: Item ""None"" of ""Optional[ndarray[Any, Any]]"" has no attribute ""max"" [union-attr] xarray/tests/test_plot.py:1968: error: Item ""None"" of ""Optional[ndarray[Any, Any]]"" has no attribute ""dtype"" [union-attr] xarray/tests/test_plot.py:1969: error: Value of type ""Optional[ndarray[Any, Any]]"" is not indexable [index] xarray/tests/test_plot.py:2125: error: ""Artist"" has no attribute ""get_clim"" [attr-defined] xarray/tests/test_plot.py:2135: error: ""Colorbar"" has no attribute ""vmin"" [attr-defined] xarray/tests/test_plot.py:2136: error: ""Colorbar"" has no attribute ""vmax"" [attr-defined] xarray/tests/test_plot.py:2202: error: ""Artist"" has no attribute ""get_clim"" [attr-defined] xarray/tests/test_plot.py:2218: error: ""Artist"" has no attribute ""norm"" [attr-defined] xarray/tests/test_plot.py:2747: error: Item ""_AxesBase"" of ""Optional[_AxesBase]"" has no attribute ""legend_"" [union-attr] xarray/tests/test_plot.py:2747: error: Item ""None"" of ""Optional[_AxesBase]"" has no attribute ""legend_"" [union-attr] xarray/tests/test_plot.py:2754: error: Item ""None"" of ""Optional[_AxesBase]"" has no attribute ""get_legend"" [union-attr] xarray/tests/test_plot.py:2775: error: Item ""None"" of ""Optional[FigureBase]"" has no attribute ""axes"" [union-attr] xarray/tests/test_plot.py:2775: error: Argument 1 to ""len"" has incompatible type ""Union[_AxesBase, None, Any]""; expected ""Sized"" [arg-type] xarray/tests/test_plot.py:2803: error: Module has no attribute ""dates"" [attr-defined] xarray/tests/test_plot.py:2812: error: Module has no attribute ""dates"" [attr-defined] xarray/tests/test_plot.py:2831: error: Item ""None"" of ""Optional[_AxesBase]"" has no attribute ""xaxis"" [union-attr] xarray/tests/test_plot.py:2831: error: Module has no attribute ""dates"" [attr-defined] xarray/tests/test_groupby.py:715: error: Argument 1 to ""groupby"" of ""Dataset"" has incompatible type ""ndarray[Any, dtype[signedinteger[Any]]]""; expected ""Union[Hashable, DataArray, IndexVariable]"" [arg-type] xarray/tests/test_groupby.py:715: note: Following member(s) of ""ndarray[Any, dtype[signedinteger[Any]]]"" have conflicts: xarray/tests/test_groupby.py:715: note: __hash__: expected ""Callable[[], int]"", got ""None"" xarray/tests/test_dataset.py:6964: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataset.py:6965: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataset.py:7007: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataset.py:7008: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataarray.py:6687: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataarray.py:6689: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataarray.py:6735: error: ""PlainQuantity[Any]"" not callable [operator] xarray/tests/test_dataarray.py:6737: error: ""PlainQuantity[Any]"" not callable [operator] ```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1684281101 https://github.com/pydata/xarray/pull/7752#issuecomment-1509228401,https://api.github.com/repos/pydata/xarray/issues/7752,1509228401,IC_kwDOAMm_X85Z9P9x,14371165,2023-04-14T20:38:08Z,2023-04-14T20:38:59Z,MEMBER,"The mypy 3.9 CI keeps installing the old version which hinders installing a new version with `python -m pip install mypy`.
``` INSTALLED VERSIONS ------------------ commit: c6eeaa6faa0f3d084f98bb5c9bad777533f07a40 python: 3.9.16 | packaged by conda-forge | (main, Feb 1 2023, 21:39:03) [GCC 11.3.0] python-bits: 64 OS: Linux OS-release: 5.15.0-1035-azure machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: C.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: 2023.3.1.dev56+gc6eeaa6f pandas: 2.0.0 numpy: 1.23.5 scipy: 1.10.1 netCDF4: 1.6.3 pydap: installed h5netcdf: 1.1.0 h5py: 3.8.0 Nio: None zarr: 2.14.2 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.4.1 bottleneck: 1.3.7 dask: 2023.3.2 distributed: 2023.3.2.1 matplotlib: 3.7.1 cartopy: 0.21.1 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.4.0 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.6.10 numpy_groupies: 0.9.20 setuptools: 67.6.1 pip: 23.0.1 conda: 23.3.1 pytest: 7.3.0 mypy: 0.982 IPython: None sphinx: None ```
Using `python -m pip install mypy --force-reinstall` seems to do the trick.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1665260014 https://github.com/pydata/xarray/pull/7752#issuecomment-1505965953,https://api.github.com/repos/pydata/xarray/issues/7752,1505965953,IC_kwDOAMm_X85ZwzeB,14371165,2023-04-12T21:21:40Z,2023-04-12T21:21:40Z,MEMBER,"Before: ``` xarray/core/utils.py:116: error: Unused ""type: ignore"" comment xarray/core/combine.py:374: error: Unused ""type: ignore"" comment xarray/core/rolling.py:379: error: Unused ""type: ignore"" comment xarray/core/rolling.py:756: error: Unused ""type: ignore"" comment xarray/tests/test_plot.py:2045: error: Argument ""col"" has incompatible type ""str""; expected ""None"" [arg-type] xarray/tests/test_plot.py:2054: error: Argument ""col"" has incompatible type ""str""; expected ""None"" [arg-type] xarray/tests/test_variable.py:65: error: ""staticmethod"" expects 2 type arguments, but 1 given [type-arg] xarray/tests/test_concat.py:543: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs [annotation-unchecked] Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Installing missing stub packages: /home/runner/micromamba-root/envs/xarray-tests/bin/python -m pip install types-PyYAML types-Pygments types-babel types-colorama types-paramiko types-psutil types-pytz types-pywin32 types-setuptools types-urllib3 Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Found 7 errors in 5 files (checked 138 source files) ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1665260014 https://github.com/pydata/xarray/pull/7720#issuecomment-1501602776,https://api.github.com/repos/pydata/xarray/issues/7720,1501602776,IC_kwDOAMm_X85ZgKPY,14371165,2023-04-10T09:27:10Z,2023-04-10T09:27:10Z,MEMBER,"Thanks, @kmuehlbauer !","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1655000231 https://github.com/pydata/xarray/pull/7561#issuecomment-1497352228,https://api.github.com/repos/pydata/xarray/issues/7561,1497352228,IC_kwDOAMm_X85ZP8gk,14371165,2023-04-05T11:47:34Z,2023-04-05T11:47:34Z,MEMBER,"I'm not sure about the rest of the errors, @dcherian. Maybe IndexVariable needs to use the DataWithCoords mixin? ``` xarray/core/groupby.py:577: error: Value of type variable ""DataAlignable"" of ""align"" cannot be ""Union[DataArray, IndexVariable]"" [type-var] xarray/core/groupby.py:577: error: Value of type variable ""DataAlignable"" of ""align"" cannot be ""Union[Dataset, DataArray, IndexVariable]"" [type-var] xarray/tests/test_groupby.py:55: error: List item 1 has incompatible type ""int""; expected ""slice"" [list-item] ``` https://github.com/pydata/xarray/blob/d4db16699f30ad1dc3e6861601247abf4ac96567/xarray/core/alignment.py#L581-L588 https://github.com/pydata/xarray/blob/d4db16699f30ad1dc3e6861601247abf4ac96567/xarray/core/alignment.py#L31 https://github.com/pydata/xarray/blob/d4db16699f30ad1dc3e6861601247abf4ac96567/xarray/core/common.py#L376-L377 ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1600382587 https://github.com/pydata/xarray/issues/7697#issuecomment-1489083542,https://api.github.com/repos/pydata/xarray/issues/7697,1489083542,IC_kwDOAMm_X85YwZyW,14371165,2023-03-29T18:17:35Z,2023-03-29T18:17:35Z,MEMBER,Looks like you almost got this figured out! You want to create a PR for this?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1646267547 https://github.com/pydata/xarray/pull/7690#issuecomment-1486221550,https://api.github.com/repos/pydata/xarray/issues/7690,1486221550,IC_kwDOAMm_X85YlfDu,14371165,2023-03-28T05:04:50Z,2023-03-28T05:04:50Z,MEMBER,How come the benchmarks is not failing? Shouldn't it be significantly slower now?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1643132089 https://github.com/pydata/xarray/pull/7668#issuecomment-1481852421,https://api.github.com/repos/pydata/xarray/issues/7668,1481852421,IC_kwDOAMm_X85YU0YF,14371165,2023-03-23T20:28:52Z,2023-03-23T20:28:52Z,MEMBER,"No need to use a release version now that #7667 is merged. Might be a good idea to use the next release version though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1638243008 https://github.com/pydata/xarray/pull/7667#issuecomment-1481849098,https://api.github.com/repos/pydata/xarray/issues/7667,1481849098,IC_kwDOAMm_X85YUzkK,14371165,2023-03-23T20:25:47Z,2023-03-23T20:25:47Z,MEMBER,"Ok, it doesn't use the current PR, confirmed in #7668. But it works!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1638194068 https://github.com/pydata/xarray/pull/7667#issuecomment-1481844145,https://api.github.com/repos/pydata/xarray/issues/7667,1481844145,IC_kwDOAMm_X85YUyWx,14371165,2023-03-23T20:22:29Z,2023-03-23T20:22:29Z,MEMBER,Maybe it's not using this PR? I'll try a merge.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1638194068 https://github.com/pydata/xarray/pull/7651#issuecomment-1481829293,https://api.github.com/repos/pydata/xarray/issues/7651,1481829293,IC_kwDOAMm_X85YUuut,14371165,2023-03-23T20:10:46Z,2023-03-23T20:10:46Z,MEMBER,"PR labeler error is unrelated, see #7667.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1632697004 https://github.com/pydata/xarray/pull/7667#issuecomment-1481827782,https://api.github.com/repos/pydata/xarray/issues/7667,1481827782,IC_kwDOAMm_X85YUuXG,14371165,2023-03-23T20:09:33Z,2023-03-23T20:09:33Z,MEMBER,Am I missing something obvious again?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1638194068 https://github.com/pydata/xarray/pull/7651#issuecomment-1481769212,https://api.github.com/repos/pydata/xarray/issues/7651,1481769212,IC_kwDOAMm_X85YUgD8,14371165,2023-03-23T19:22:46Z,2023-03-23T19:22:46Z,MEMBER,"```python xarray/core/computation.py:12:1: UP035 `typing.AbstractSet` is deprecated, use `collections.abc.Set` instead xarray/core/merge.py:5:1: UP035 `typing.AbstractSet` is deprecated, use `collections.abc.Set` instead xarray/core/parallel.py:7:1: UP035 `typing.DefaultDict` is deprecated, use `collections.defaultdict` instead ``` Isn't it odd that ruff doesn't automatically fix this?","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 1, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1632697004 https://github.com/pydata/xarray/issues/7645#issuecomment-1475150683,https://api.github.com/repos/pydata/xarray/issues/7645,1475150683,IC_kwDOAMm_X85X7QNb,14371165,2023-03-19T08:31:51Z,2023-03-19T08:31:51Z,MEMBER,"Probably from #7494. `encode_cf_variable` only accepts Variables. Replace ```python data = encode_cf_variable(out_data).values.astype(numpy_dtype) ``` with ```python data = encode_cf_variable(out_data.variable).values.astype(numpy_dtype) ``` should fix the error. mypy should have caught this a while ago when #7374 went in, does `out_data` have defined type hints?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1630746106 https://github.com/pydata/xarray/pull/7206#issuecomment-1475049548,https://api.github.com/repos/pydata/xarray/issues/7206,1475049548,IC_kwDOAMm_X85X63hM,14371165,2023-03-19T00:39:00Z,2023-03-19T00:39:00Z,MEMBER,"Hmm, did I mess something up? I believe I only changed typing related things. _bins suffix seems to have disappeared: ``` def test_groupby_bins_multidim(self): array = self.make_groupby_multidim_example_array() bins = [0, 15, 20] bin_coords = pd.cut(array[""lat""].values.flat, bins).categories expected = DataArray([16, 40], dims=""lat_bins"", coords={""lat_bins"": bin_coords}) actual = array.groupby_bins(""lat"", bins).map(lambda x: x.sum()) > assert_identical(expected, actual) E AssertionError: Left and right DataArray objects are not identical E Differing dimensions: E (lat_bins: 2) != (lat: 2) E Coordinates only on the left object: E * lat_bins (lat_bins) object (0, 15] (15, 20] E Coordinates only on the right object: E * lat (lat) object (0, 15] (15, 20] ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1421065459 https://github.com/pydata/xarray/pull/7603#issuecomment-1468702898,https://api.github.com/repos/pydata/xarray/issues/7603,1468702898,IC_kwDOAMm_X85XiqCy,14371165,2023-03-14T19:27:51Z,2023-03-14T19:27:51Z,MEMBER,"``` Error: [ 89.17%] ··· groupby.ResampleDask.time_binary_op_1d failed Error: [ 89.17%] ···· Traceback (most recent call last): File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 1293, in main_run_server main_run(run_args) File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 1167, in main_run result = benchmark.do_run() File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 573, in do_run return self.run(*self._current_params) File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 669, in run samples, number = self.benchmark_timing(timer, min_repeat, max_repeat, File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 705, in benchmark_timing timing = timer.timeit(number) File ""/home/runner/work/xarray/xarray/asv_bench/.asv/env/e3a5540da3d30da735a9fb168f264be6/lib/python3.10/timeit.py"", line 178, in timeit timing = self.inner(it, self.timer) File """", line 6, in inner File ""/home/runner/work/xarray/xarray/asv_bench/benchmarks/groupby.py"", line 127, in time_binary_op_1d raise NotImplementedError NotImplementedError asv: benchmark failed (exit status 1) ``` Comparing to https://github.com/pydata/xarray/blob/5043223ca7942c6eb582798aafa843d2efc0895b/asv_bench/benchmarks/__init__.py#L72-L74 It has to be initialized? Try adding a short description with why it's not implemented/link to issue.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1618336774 https://github.com/pydata/xarray/pull/7603#issuecomment-1463319021,https://api.github.com/repos/pydata/xarray/issues/7603,1463319021,IC_kwDOAMm_X85XOHnt,14371165,2023-03-10T06:03:20Z,2023-03-10T06:03:20Z,MEMBER,"Ahh, there are a few errors in the benchmarks. Are those fixed with your other PRs? ``` Error: [ 88.75%] ··· ...by.ResampleDask.peakmem_groupby_binary_op_2d failed Error: [ 88.75%] ···· Traceback (most recent call last): File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 1293, in main_run_server main_run(run_args) File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 1167, in main_run result = benchmark.do_run() File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 573, in do_run return self.run(*self._current_params) File ""/home/runner/micromamba-root/envs/xarray-tests/lib/python3.10/site-packages/asv/benchmark.py"", line 842, in run self.func(*param) File ""/home/runner/work/xarray/xarray/asv_bench/benchmarks/groupby.py"", line 136, in peakmem_groupby_binary_op_2d self.ds2d.resample(time=""48H"") - self.ds2d_mean File ""/home/runner/work/xarray/xarray/asv_bench/.asv/env/e3a5540da3d30da735a9fb168f264be6/lib/python3.10/site-packages/xarray/core/_typed_ops.py"", line 589, in __sub__ return self._binary_op(other, operator.sub) File ""/home/runner/work/xarray/xarray/asv_bench/.asv/env/e3a5540da3d30da735a9fb168f264be6/lib/python3.10/site-packages/xarray/core/groupby.py"", line 601, in _binary_op raise ValueError( ValueError: incompatible dimensions for a grouped binary operation: the group variable '__resample_dim__' is not a dimension on the other argument asv: benchmark failed (exit status 1) ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1618336774 https://github.com/pydata/xarray/pull/7600#issuecomment-1461318814,https://api.github.com/repos/pydata/xarray/issues/7600,1461318814,IC_kwDOAMm_X85XGfSe,14371165,2023-03-09T05:38:40Z,2023-03-09T05:38:40Z,MEMBER,"I think we should stick to default black values. Otherwise I want to start arguing for line width=79 so we follow pep8. ;) You can still run this cleanup though so you still get your LOCs. :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1615980379 https://github.com/pydata/xarray/pull/7595#issuecomment-1460756497,https://api.github.com/repos/pydata/xarray/issues/7595,1460756497,IC_kwDOAMm_X85XEWAR,14371165,2023-03-08T19:45:49Z,2023-03-08T19:45:49Z,MEMBER,"I don't enjoy using git so I'll plug [Github Desktop](https://desktop.github.com/). I think it will reduce so much of the friction git causes to beginners: https://www.youtube.com/watch?v=l7uo1d3R0Wo https://www.youtube.com/watch?v=qUYkRWGWntE ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1615570467 https://github.com/pydata/xarray/pull/7442#issuecomment-1452462512,https://api.github.com/repos/pydata/xarray/issues/7442,1452462512,IC_kwDOAMm_X85WktGw,14371165,2023-03-02T19:52:23Z,2023-03-02T19:52:23Z,MEMBER,"Seems we're experiencing this issue now: https://github.com/pydata/pydata-sphinx-theme/issues/1220","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1534634670 https://github.com/pydata/xarray/pull/7427#issuecomment-1445221673,https://api.github.com/repos/pydata/xarray/issues/7427,1445221673,IC_kwDOAMm_X85WJFUp,14371165,2023-02-25T22:51:37Z,2023-02-25T22:51:37Z,MEMBER,"This one is failing on CI / ubuntu-latest py3.9 bare-minimum, is it taking a path without flox installed perhaps? ``` ___________ TestDataArrayGroupBy.test_groupby_fastpath_for_monotonic ___________ [gw2] linux -- Python 3.9.16 /home/runner/micromamba-root/envs/xarray-tests/bin/python self = def test_groupby_fastpath_for_monotonic(self): # Fixes https://github.com/pydata/xarray/issues/6220 index = [1, 2, 3, 4, 7, 9, 10] array = DataArray(np.arange(len(index)), [(""idx"", index)]) array_rev = array.copy().assign_coords({""idx"": index[::-1]}) fwd = array.groupby(""idx"", squeeze=False) rev = array_rev.groupby(""idx"", squeeze=False) for gb in [fwd, rev]: assert all([isinstance(elem, slice) for elem in gb._group_indices]) assert_identical(fwd.sum(), array) > assert_identical(rev.sum(), array_rev.sortby(""idx"")) E AssertionError: Left and right DataArray objects are not identical E E Differing values: E L E array([0, 1, 2, 3, 4, 5, 6]) E R E array([6, 5, 4, 3, 2, 1, 0]) E Differing coordinates: E L * idx (idx) int64 10 9 7 4 3 2 1 E R * idx (idx) int64 1 2 3 4 7 9 10 ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1523260646 https://github.com/pydata/xarray/issues/4610#issuecomment-1433686861,https://api.github.com/repos/pydata/xarray/issues/4610,1433686861,IC_kwDOAMm_X85VdFNN,14371165,2023-02-16T20:39:54Z,2023-02-16T20:39:54Z,MEMBER,"Nice, I was looking at the real example too, `Temp_url = 'http://apdrc.soest.hawaii.edu:80/dods/public_data/WOA/WOA13/5_deg/annual/temp' etc..`, and it was triggering a load in set_dims: ![image](https://user-images.githubusercontent.com/14371165/219481554-992c3a65-5f41-4e24-bf33-148db47165da.png) ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,750985364 https://github.com/pydata/xarray/pull/6874#issuecomment-1433681353,https://api.github.com/repos/pydata/xarray/issues/6874,1433681353,IC_kwDOAMm_X85VdD3J,14371165,2023-02-16T20:34:16Z,2023-02-16T20:34:16Z,MEMBER,"I don't have a better idea than to do `DuckArray = Any # ndarray/cupy/sparse etc.` and add that as output, but that wont change anything mypy-wise besides making it easier for us to read the code.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1327380960 https://github.com/pydata/xarray/issues/4610#issuecomment-1433670641,https://api.github.com/repos/pydata/xarray/issues/4610,1433670641,IC_kwDOAMm_X85VdBPx,14371165,2023-02-16T20:24:51Z,2023-02-16T20:25:36Z,MEMBER,"> * Absolute speed of xhistogram appears to be 3-4x higher, and that's using `numpy_groupies` in flox. Possibly flox could be faster if using numba but not sure yet. Could you show the example that's this slow, @TomNicholas ? So I can play around with it too. One thing I noticed in your notebook is that you haven't used `chunks={}` on the open_dataset. Which seems to trigger data loading on strange places in xarray (places that calls self.data), but I'm not sure this is your actual problem.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,750985364 https://github.com/pydata/xarray/pull/7521#issuecomment-1426819173,https://api.github.com/repos/pydata/xarray/issues/7521,1426819173,IC_kwDOAMm_X85VC4hl,14371165,2023-02-11T16:42:44Z,2023-02-11T16:42:44Z,MEMBER,"``` dask-core 2023.2.0 pyhd8ed1ab_0 conda-forge distarray 2.12.2 pyh050c7b8_4 conda-forge distlib 0.3.6 pyhd8ed1ab_0 conda-forge distributed 2021.4.1 py39hf3d152e_1 conda-forge ``` Yeah looks like an old version. py.typed was around september so it makes sense that part.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1580266844 https://github.com/pydata/xarray/pull/7521#issuecomment-1426817848,https://api.github.com/repos/pydata/xarray/issues/7521,1426817848,IC_kwDOAMm_X85VC4M4,14371165,2023-02-11T16:36:34Z,2023-02-11T16:36:34Z,MEMBER,"I don't get the error. Distributed has a py.typed file https://github.com/dask/distributed/blob/main/distributed/py.typed And if it was py.typed issue we should have seen it in other PRs and I haven't seen one yet that has this error.. @TomNicholas added py.typed to package data, https://github.com/xarray-contrib/datatree/commit/927749a7702761491461f9bdfa8a0c1fbc244d85 But still, if distributed also needs to do this we should see this error in more PRs. ``` ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 49.2/49.2 kB 3.6 MB/s eta 0:00:00 Collecting types-docutils Downloading types_docutils-0.19.1.3-py3-none-any.whl (16 kB) Installing collected packages: types-PyYAML, types-pytz, types-docutils, types-setuptools Successfully installed types-PyYAML-6.0.12.5 types-docutils-0.19.1.3 types-pytz-2022.7.1.0 types-setuptools-67.2.0.1 xarray/tests/test_distributed.py:14: error: Skipping analyzing ""distributed"": module is installed, but missing library stubs or py.typed marker [import] xarray/tests/test_distributed.py:21: error: Skipping analyzing ""distributed.client"": module is installed, but missing library stubs or py.typed marker [import] xarray/tests/test_distributed.py:21: note: See https://mypy.readthedocs.io/en/stable/running_mypy.html#missing-imports xarray/tests/test_distributed.py:22: error: Skipping analyzing ""distributed.utils_test"": module is installed, but missing library stubs or py.typed marker [import] Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Installing missing stub packages: /home/runner/micromamba-root/envs/xarray-tests/bin/python -m pip install types-PyYAML types-pytz types-setuptools Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Found 3 errors in 1 file (checked 140 source files) ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1580266844 https://github.com/pydata/xarray/issues/5081#issuecomment-1414187606,https://api.github.com/repos/pydata/xarray/issues/5081,1414187606,IC_kwDOAMm_X85USspW,14371165,2023-02-02T18:32:23Z,2023-02-02T18:32:23Z,MEMBER,"It is recommended to use it for lazy backends though: https://docs.xarray.dev/en/stable/internals/how-to-add-new-backend.html#how-to-support-lazy-loading ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,842436143 https://github.com/pydata/xarray/pull/7418#issuecomment-1411536785,https://api.github.com/repos/pydata/xarray/issues/7418,1411536785,IC_kwDOAMm_X85UIleR,14371165,2023-02-01T06:34:08Z,2023-02-01T06:34:08Z,MEMBER,"Hmm, I don't understand. Adding py.typed should be all that's needed, did that in flox and it worked great there: https://github.com/xarray-contrib/flox/pull/92","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1519552711 https://github.com/pydata/xarray/pull/7494#issuecomment-1411177667,https://api.github.com/repos/pydata/xarray/issues/7494,1411177667,IC_kwDOAMm_X85UHNzD,14371165,2023-01-31T22:49:24Z,2023-01-31T22:49:24Z,MEMBER,"@agoodm, what you think of this version? Using xr.Variable directly seems a little easier to work with than trying to guess which type of array (cupy, dask, pint, backendarray, etc) is in the variable.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1563270549 https://github.com/pydata/xarray/pull/7496#issuecomment-1410959131,https://api.github.com/repos/pydata/xarray/issues/7496,1410959131,IC_kwDOAMm_X85UGYcb,14371165,2023-01-31T19:38:59Z,2023-01-31T19:38:59Z,MEMBER,It would be nice to have a good copy/paste example for open_dataset. For example I think `chunks` have different defaults compared to open_zarr.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1564661430 https://github.com/pydata/xarray/issues/7484#issuecomment-1409323892,https://api.github.com/repos/pydata/xarray/issues/7484,1409323892,IC_kwDOAMm_X85UAJN0,14371165,2023-01-30T20:59:36Z,2023-01-30T21:00:40Z,MEMBER,You can do `var._data` instead of `var.data`. There's been a few cases recently where `self.data` doesn't play so nice when reading from a file.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1561508426 https://github.com/pydata/xarray/issues/7484#issuecomment-1409243024,https://api.github.com/repos/pydata/xarray/issues/7484,1409243024,IC_kwDOAMm_X85T_1eQ,14371165,2023-01-30T19:53:03Z,2023-01-30T19:53:03Z,MEMBER,Feel free to start working on that PR. 👍 It looks like `_contains_cftime_datetimes` tries to do a similar thing as your solution so I think the change should be there.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1561508426 https://github.com/pydata/xarray/pull/7277#issuecomment-1405634513,https://api.github.com/repos/pydata/xarray/issues/7277,1405634513,IC_kwDOAMm_X85TyEfR,14371165,2023-01-26T20:51:43Z,2023-01-26T20:51:43Z,MEMBER,pre-commit.ci autofix,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 1, ""eyes"": 0}",,1444440024 https://github.com/pydata/xarray/pull/7472#issuecomment-1402675394,https://api.github.com/repos/pydata/xarray/issues/7472,1402675394,IC_kwDOAMm_X85TmyDC,14371165,2023-01-24T21:15:37Z,2023-01-24T21:57:10Z,MEMBER,"I like these kinds of improvements :) With ravel_chunks: ``` before after ratio [3ee7b5a6] [e549724e] - 983M 183M 0.19 pandas.ToDataFrameDask.peakmem_to_dataframe - 2.76±0s 7.76±0.08ms 0.00 pandas.ToDataFrameDask.time_to_dataframe ``` With reshape ``` before after ratio [3ee7b5a6] [02a4e97f] - 983M 183M 0.19 pandas.ToDataFrameDask.peakmem_to_dataframe - 2.78±0s 9.20±0.1ms 0.00 pandas.ToDataFrameDask.time_to_dataframe ```","{""total_count"": 2, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 2, ""rocket"": 0, ""eyes"": 0}",,1554036799 https://github.com/pydata/xarray/pull/7474#issuecomment-1402567748,https://api.github.com/repos/pydata/xarray/issues/7474,1402567748,IC_kwDOAMm_X85TmXxE,14371165,2023-01-24T20:13:12Z,2023-01-24T21:00:38Z,MEMBER,"Seems to work. :) I'll do a quick merge and continue in #7472. ``` [ 68.06%] ··· pandas.ToDataFrame.peakmem_to_dataframe 2.89G [ 68.19%] ··· pandas.ToDataFrame.time_to_dataframe 1.39±0.02s [ 68.33%] ··· pandas.ToDataFrameDask.peakmem_to_dataframe 983M [ 68.47%] ··· pandas.ToDataFrameDask.time_to_dataframe 2.77±0s ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1555497796 https://github.com/pydata/xarray/pull/7461#issuecomment-1402594544,https://api.github.com/repos/pydata/xarray/issues/7461,1402594544,IC_kwDOAMm_X85TmeTw,14371165,2023-01-24T20:27:02Z,2023-01-24T20:27:02Z,MEMBER,"I'm not sure at all about this but maybe you're supposed to go back to something like this? https://github.com/pydata/xarray/pull/6834/commits/7fcc11ffb20583caf1976191997bd2a7525ac218#diff-791d93adb64d0986ac499ce1ba831cc95b4ffbde0dfe98b28d929935b05d7134L49 ```python from numpy.typing._dtype_like import _DTypeLikeNested, _ShapeLike, _SupportsDType ``` From #6834. ","{""total_count"": 2, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 1, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1550109629 https://github.com/pydata/xarray/pull/7353#issuecomment-1400218891,https://api.github.com/repos/pydata/xarray/issues/7353,1400218891,IC_kwDOAMm_X85TdaUL,14371165,2023-01-23T11:51:56Z,2023-01-23T11:51:56Z,MEMBER,"Creating a separate environment file seems like a good idea. Feel free to push the changes you want, @keewis. I was thinking of coming back to this once 3.8 was dropped. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474717029 https://github.com/pydata/xarray/pull/7277#issuecomment-1399202401,https://api.github.com/repos/pydata/xarray/issues/7277,1399202401,IC_kwDOAMm_X85TZiJh,14371165,2023-01-21T07:54:29Z,2023-01-21T07:54:29Z,MEMBER,"This has stalled for long enough. I'll merge this at the end of next week unless someone disagrees, this pretty much reverts to original ds.plot.scatter behaviour because defining less than x and y in ds.plot.scatter was never allowed before anyway.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1444440024 https://github.com/pydata/xarray/pull/7318#issuecomment-1399201567,https://api.github.com/repos/pydata/xarray/issues/7318,1399201567,IC_kwDOAMm_X85TZh8f,14371165,2023-01-21T07:48:36Z,2023-01-21T07:48:36Z,MEMBER,"This has stalled for long enough. I'll merge this at the end of next week unless someone disagrees, at least it is an improvement to the bugged main.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1462470712 https://github.com/pydata/xarray/pull/7353#issuecomment-1398790498,https://api.github.com/repos/pydata/xarray/issues/7353,1398790498,IC_kwDOAMm_X85TX9li,14371165,2023-01-20T18:42:31Z,2023-01-20T18:42:31Z,MEMBER,"[87d689a](https://github.com/pydata/xarray/pull/7353/commits/87d689a21703940d505893947ea6c0f2572a45ca) shows that we have issues with 3.8 when either of numba/cdms2/numbagg are not available, then we take a different code path that fails somehow. Hopefully with python 3.9 it's fixed. Failing tests with only python 3.8 with windows, no numba/cdms2/numbagg:
``` FAILED xarray/tests/test_dataarray.py::TestNumpyCoercion::test_from_sparse - ValueError: Performing this operation would produce a dense result: FAILED xarray/tests/test_dataset.py::TestDataset::test_unstack_sparse - TypeError: __init__() got an unexpected keyword argument 'fill_value' FAILED xarray/tests/test_dataset.py::TestDataset::test_from_dataframe_sparse - TypeError: __init__() got an unexpected keyword argument 'fill_value' FAILED xarray/tests/test_dataset.py::TestNumpyCoercion::test_from_sparse - ValueError: Performing this operation would produce a dense result: FAILED xarray/tests/test_dataarray.py::TestDataArray::test_from_series_sparse - TypeError: __init__() got an unexpected keyword argument 'fill_value' FAILED xarray/tests/test_dataarray.py::TestDataArray::test_from_multiindex_series_sparse - TypeError: from_numpy() takes 2 positional arguments but 3 were given FAILED xarray/tests/test_sparse.py::test_variable_method[obj.all(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.any(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.astype(*(), **{'dtype': })-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.clip(*(), **{'min': 0, 'max': 1})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.coarsen(*(), **{'windows': {'x': 2}, 'func': 'sum'})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.compute(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.conj(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.copy(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.count(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.get_axis_num(*(), **{'dim': 'x'})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.isel(*(), **{'x': slice(2, 4, None)})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.isnull(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.load(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.mean(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.notnull(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.roll(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.round(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.set_dims(*(), **{'dims': ('x', 'y', 'z')})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.stack(*(), **{'dimensions': {'flat': ('x', 'y')}})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.to_base_variable(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.transpose(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.unstack(*(), **{'dimensions': {'x': {'x1': 5, 'x2': 2}}})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.broadcast_equals(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]]),), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.equals(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]]),), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.identical(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]]),), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.fillna(*(0,), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.max(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.min(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.prod(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.sum(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_variable_method[obj.where(*(), **{'cond': \narray([[False, False, False, True, False],\n [False, False, False, False, False],\n [False, False, False, False, False],\n [False, False, False, False, False],\n [False, False, False, False, False],\n [False, False, False, False, False],\n [False, False, False, False, False],\n [False, False, False, False, True],\n [False, False, False, False, False],\n [False, False, True, False, False]])})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_1d_variable_method[func0-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_nbytes - assert 192 == 120 + where 192 = \narray([[0. , 0.87001215, 0. , 0. , 0. ,\n 0. ]...6147936,\n 0.63992102],\n [0. , 0. , 0.77815675, 0. , 0.0202184 ,\n 0.79915856]]).nbytes + where \narray([[0. , 0.87001215, 0. , 0. , 0. ,\n 0. ]...6147936,\n 0.63992102],\n [0. , 0. , 0.77815675, 0. , 0.0202184 ,\n 0.79915856]]) = .var + and 120 = .nbytes + where = .data FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_unary_op - AssertionError: assert False + where False = isinstance(array([[-0. , -0.87001215, -0. , -0. , -0. ,\n -0. ],\n [-0.11827443, -0...,\n -0.63992102],\n [-0. , -0. , -0.77815675, -0. , -0.0202184 ,\n -0.79915856]]), (,)) FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_univariate_ufunc - AssertionError: assert False + where False = isinstance(array([[0. , 0.76433677, 0. , 0. , 0. ,\n 0. ],\n [0.11799887, 0. ...4527321,\n 0.59713209],\n [0. , 0. , 0.70196783, 0. , 0.02021702,\n 0.7167696 ]]), (,)) FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_bivariate_ufunc - AssertionError: assert False + where False = isinstance(array([[0. , 0.87001215, 0. , 0. , 0. ,\n 0. ],\n [0.11827443, 0. ...6147936,\n 0.63992102],\n [0. , 0. , 0.77815675, 0. , 0.0202184 ,\n 0.79915856]]), (,)) FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_repr - AssertionError: assert '' == ' + - array([[0. , 0.87001215, 0. , 0. , 0. , - 0. ], - [0.11827443, 0. , 0.78052918, 0. , 0.0871293 , - 0.07103606], - [0. , 0.97861834, 0.83261985, 0. , 0.46147936, - 0.63992102], - [0. , 0. , 0.77815675, 0. , 0.0202184 , - 0.79915856]]) FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_pickle - AssertionError: assert False + where False = isinstance(array([[0. , 0.87001215, 0. , 0. , 0. ,\n 0. ],\n [0.11827443, 0. ...6147936,\n 0.63992102],\n [0. , 0. , 0.77815675, 0. , 0.0202184 ,\n 0.79915856]]), (,)) FAILED xarray/tests/test_sparse.py::TestSparseVariable::test_missing_values - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.all(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.any(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.assign_attrs(*({'foo': 'bar'},), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.assign_coords(*(), **{'x': \narray([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])\nCoordinates:\n * x (x) int32 0 1 2 3 4 5 6 7 8 9})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.astype(*(,), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.clip(*(), **{'min': 0, 'max': 1})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.compute(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.conj(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.copy(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.count(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.diff(*('x',), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.drop_vars(*('x',), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.expand_dims(*({'z': 2},), **{'axis': 2})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.get_axis_num(*('x',), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.get_index(*('x',), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.identical(*(\narray([[0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0.71518937, 0. , 0. ],\n [0.60276338, 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ]])\nCoordinates:\n * x (x) int32 0 1 2 3 4\n * y (y) int32 0 1 2 3 4,), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.integrate(*('x',), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.isel(*({'x': slice(0, 3, None), 'y': slice(2, 4, None)},), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.isnull(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.load(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.mean(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.persist(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.reindex(*({'x': [1, 2, 3]},), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.rename(*('foo',), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.reorder_levels(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.reset_coords(*(), **{'drop': True})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.reset_index(*('x',), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.round(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.sel(*(), **{'x': [0, 1, 2]})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.shift(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.sortby(*('x',), **{'ascending': False})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.stack(*(), **{'z': ['x', 'y']})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.transpose(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.broadcast_equals(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]]),), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.equals(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]]),), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.combine_first(*(\narray([[0.43758721, 0. , 0. , 0.891773 , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0. ],\n [0. , 0. , 0. , 0. , 0.96366276],\n [0. , 0. , 0. , 0. , 0.4236548 ],\n [0. , 0. , 0.64589411, 0. , 0. ]])\nCoordinates:\n * x (x) int32 0 1 2 3 4 5 6 7 8 9\n * y (y) int32 0 1 2 3 4,), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.fillna(*(0,), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.max(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.min(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.notnull(*(), **{})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.pipe(*(), **{'func': 'sum', 'axis': 1})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.prod(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.roll(*(), **{'x': 2, 'roll_coords': True})-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dataarray_method[obj.sum(*(), **{})-False] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_datarray_1d_method[func0-True] - AttributeError: 'numpy.ndarray' object has no attribute 'todense' FAILED xarray/tests/test_sparse.py::test_dask_token - AssertionError: assert False + where False = isinstance(array([0, 0, 1, 2]), ) + where array([0, 0, 1, 2]) = \narray([0, 0, 1, 2])\nDimensions without coordinates: dim_0.data + and = sparse.COO FAILED xarray/tests/test_sparse.py::test_apply_ufunc_check_meta_coherence - AssertionError: assert False + where False = isinstance(array([], dtype=int32), (,)) FAILED xarray/tests/test_variable.py::TestVariableWithSparse::test_as_sparse - ValueError: coo is not a valid sparse format ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_to_dataset_roundtrip - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_align - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_align_outer - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_concat - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_stack - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_dataarray_repr - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_dataset_repr - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_sparse_dask_dataset_repr - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_dataarray_pickle - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_dataset_pickle - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) ERROR xarray/tests/test_sparse.py::TestSparseDataArrayAndDataset::test_coarsen - ValueError: could not broadcast input array from shape (4,6) into shape (4,1) = 93 failed, 14715 passed, 1640 skipped, 211 xfailed, 66 xpassed, 327 warnings, 11 errors in 699.08s (0:11:39) = ```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474717029 https://github.com/pydata/xarray/pull/7353#issuecomment-1398730901,https://api.github.com/repos/pydata/xarray/issues/7353,1398730901,IC_kwDOAMm_X85TXvCV,14371165,2023-01-20T17:41:22Z,2023-01-20T17:41:22Z,MEMBER,"Deprecation warning in pydap failing the docstring tests: ``` ImportError while loading conftest '/home/runner/work/xarray/xarray/xarray/tests/conftest.py'. xarray/tests/__init__.py:64: in has_pydap, requires_pydap = _importorskip(""pydap.client"") xarray/tests/__init__.py:51: in _importorskip mod = importlib.import_module(modname) ../../../micromamba-root/envs/xarray-tests/lib/python3.11/site-packages/pydap/client.py:52: in from .net import GET, raise_for_status ../../../micromamba-root/envs/xarray-tests/lib/python3.11/site-packages/pydap/net.py:1: in from webob.request import Request ../../../micromamba-root/envs/xarray-tests/lib/python3.11/site-packages/webob/__init__.py:1: in from webob.datetime_utils import ( # noqa: F401 ../../../micromamba-root/envs/xarray-tests/lib/python3.11/site-packages/webob/datetime_utils.py:18: in from webob.compat import ( ../../../micromamba-root/envs/xarray-tests/lib/python3.11/site-packages/webob/compat.py:5: in from cgi import parse_header ../../../micromamba-root/envs/xarray-tests/lib/python3.11/cgi.py:57: in warnings._deprecated(__name__, remove=(3,13)) ../../../micromamba-root/envs/xarray-tests/lib/python3.11/warnings.py:514: in _deprecated warn(msg, DeprecationWarning, stacklevel=3) E DeprecationWarning: 'cgi' is deprecated and slated for removal in Python 3.13 ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474717029 https://github.com/pydata/xarray/pull/7461#issuecomment-1398702023,https://api.github.com/repos/pydata/xarray/issues/7461,1398702023,IC_kwDOAMm_X85TXn_H,14371165,2023-01-20T17:21:34Z,2023-01-20T17:21:34Z,MEMBER,"@jhamman, I believe you should simply remove `GenericAlias` and the `__class_getitem__` it was a hack copied from a newer version of `collections`, see https://github.com/pydata/xarray/pull/7285#discussion_r1027253337. Commit testing the hack: https://github.com/pydata/xarray/pull/7285/commits/d8bef27e54aa9e81873d5d64fca6a1d4d324ca62","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1550109629 https://github.com/pydata/xarray/issues/7457#issuecomment-1397515014,https://api.github.com/repos/pydata/xarray/issues/7457,1397515014,IC_kwDOAMm_X85TTGMG,14371165,2023-01-19T19:49:19Z,2023-01-19T19:49:19Z,MEMBER,"> I feel like this has been mentioned before. Yes, now I recall, it was here #6894. I think it could be interesting to try out: https://github.com/pmeier/array-protocol Another good read: https://github.com/data-apis/array-api/issues/229","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548948097 https://github.com/pydata/xarray/issues/7457#issuecomment-1397074522,https://api.github.com/repos/pydata/xarray/issues/7457,1397074522,IC_kwDOAMm_X85TRapa,14371165,2023-01-19T14:35:37Z,2023-01-19T14:35:37Z,MEMBER,"I've been thinking that a good and safe start on this issue is to replace all these raw `Any`'s with T_DuckArray where `T_DuckArray = Any`. It won't help in the typing but it gives some traceability and makes it easier to determine what the intention was.","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1548948097 https://github.com/pydata/xarray/pull/7424#issuecomment-1373979208,https://api.github.com/repos/pydata/xarray/issues/7424,1373979208,IC_kwDOAMm_X85R5UJI,14371165,2023-01-06T18:18:56Z,2023-01-15T16:09:05Z,MEMBER,"The array api standard doesn't define any [`nan*`-functions](https://data-apis.org/array-api/latest/API_specification/statistical_functions.html). xarray pretty much always defaults to using `nan*`-function. :( So any time an array has a `__array_namespace__` we have to use our own nan-solution, like for `.sum`: https://github.com/pydata/xarray/blob/d6d24507793af9bcaed79d7f8d3ac910e176f1ce/xarray/core/duck_array_ops.py#L288-L295 Any thoughts? Are there any clever ways to handle the aggregations with NaNs in a generic way? edit: numpy implementations: https://github.com/numpy/numpy/blob/main/numpy/lib/nanfunctions.py","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1522810384 https://github.com/pydata/xarray/issues/7439#issuecomment-1383112964,https://api.github.com/repos/pydata/xarray/issues/7439,1383112964,IC_kwDOAMm_X85ScKEE,14371165,2023-01-15T10:24:55Z,2023-01-15T10:31:29Z,MEMBER,"I've found this part of the documentation a bit scary in the past because there is so much stuff to do for a simple ""typo fix"" so I welcome changes here! Nowadays, since the CI runs [pytest](https://github.com/pydata/xarray/actions/runs/3914705703/jobs/6692077250), [ASV performance benchmarks](https://github.com/pydata/xarray/actions/runs/3888041731/jobs/6634964516), [pre-commit](https://github.com/pydata/xarray/pull/7438/commits/93cd752fe58b8cd7047b15bb217e2ebbcb7a6d38) and [builds the documentation](https://xray--7438.org.readthedocs.build/en/7438/) on every PR it isn't really necessary for new contributors to get it to run locally. The only thing left is setting up a new branch with git, change the code and create a PR. If the CI fails check the details of that test, correct the code, push a new commit. Setting up git can also be scary for new users but then there is [github desktop](https://desktop.github.com/) which hides away all of that in a quite user friendly GUI. Sure, if you're doing bigger changes running the specific tests locally is probably faster but at that point you're probably a more experienced contributor anyway. ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1532853152 https://github.com/pydata/xarray/pull/7374#issuecomment-1379571092,https://api.github.com/repos/pydata/xarray/issues/7374,1379571092,IC_kwDOAMm_X85SOpWU,14371165,2023-01-11T22:33:55Z,2023-01-11T22:33:55Z,MEMBER,"Benchmark are improved if I understand the logs correctly. Unfortunately not significant enough to make ASV report it though. The ratio has to be >1.5 and the improvements on .time_open_dataset are around 1.3-1.4. ``` # PR: [ 50.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 50.85%] ··· ======== ========= chunks -------- --------- None 130±1ms {} 689±6ms ======== ========= [ 54.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 54.69%] ··· ========= ============= ============= -- chunks --------- --------------------------- engine None {} ========= ============= ============= scipy 5.48±0.04ms 6.91±0.01ms netcdf4 2.93±0.04ms 4.32±0.02ms ========= ============= ============= # Baseline: [ 75.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 75.85%] ··· ======== =========== chunks -------- ----------- None 177±0.5ms {} 737±3ms ======== =========== [ 79.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 79.69%] ··· ========= ============ ============ -- chunks --------- ------------------------- engine None {} ========= ============ ============ scipy 4.47±0.6ms 5.74±0.7ms netcdf4 4.39±0.7ms 5.82±0.6ms ========= ============ ============ ``` ``` # PR: [ 50.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 50.85%] ··· ======== ========== chunks -------- ---------- None 149±4ms {} 797±20ms ======== ========== [ 54.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 54.69%] ··· ========= ============ ============= -- chunks --------- -------------------------- engine None {} ========= ============ ============= scipy 6.57±0.2ms 7.77±0.01ms netcdf4 3.71±0.1ms 6.17±0.5ms ========= ============ ============= # Baseline: [ 75.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 75.85%] ··· ======== ========== chunks -------- ---------- None 204±2ms {} 857±20ms ======== ========== [ 79.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 79.69%] ··· ========= ============ ============ -- chunks --------- ------------------------- engine None {} ========= ============ ============ scipy 5.53±1ms 7.12±0.8ms netcdf4 4.96±0.6ms 6.74±0.8ms ========= ============ ============ ``` ``` # PR: [ 50.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 50.85%] ··· ======== ============ chunks -------- ------------ None 204±8ms {} 1.20±0.04s ======== ============ [ 54.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 54.69%] ··· ========= ============ ============ -- chunks --------- ------------------------- engine None {} ========= ============ ============ netcdf4 6.86±0.7ms 9.81±0.6ms scipy 6.74±1ms 9.10±1ms ========= ============ ============ # Baseline: [ 75.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 75.85%] ··· ======== ============ chunks -------- ------------ None 282±5ms {} 1.20±0.04s ======== ============ [ 79.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 79.69%] ··· ========= ============ ============ -- chunks --------- ------------------------- engine None {} ========= ============ ============ netcdf4 6.91±1ms 9.77±0.7ms scipy 6.91±0.7ms 9.11±1ms ========= ============ ============ ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1490160140 https://github.com/pydata/xarray/pull/7431#issuecomment-1378015095,https://api.github.com/repos/pydata/xarray/issues/7431,1378015095,IC_kwDOAMm_X85SItd3,14371165,2023-01-10T23:10:32Z,2023-01-10T23:10:32Z,MEMBER,"Seems to work, tested a little here #7426.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1528100871 https://github.com/pydata/xarray/pull/7431#issuecomment-1378010601,https://api.github.com/repos/pydata/xarray/issues/7431,1378010601,IC_kwDOAMm_X85SIsXp,14371165,2023-01-10T23:05:43Z,2023-01-10T23:05:58Z,MEMBER,Seems bot uses labeler from main? I'll merge and see what want happens..,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1528100871 https://github.com/pydata/xarray/pull/7426#issuecomment-1376318165,https://api.github.com/repos/pydata/xarray/issues/7426,1376318165,IC_kwDOAMm_X85SCPLV,14371165,2023-01-09T21:09:05Z,2023-01-09T22:31:51Z,MEMBER,"Timings for the new ASV-tests: ``` [ 50.85%] ··· dataset_io.IOReadCustomEngine.time_open_dataset ok [ 50.85%] ··· ======== ============ chunks -------- ------------ None 265±4ms {} 1.17±0.02s ======== ============ [ 54.69%] ··· dataset_io.IOReadSingleFile.time_read_dataset ok [ 54.69%] ··· ========= ============= ============= -- chunks --------- --------------------------- engine None {} ========= ============= ============= scipy 4.81±0.1ms 6.65±0.01ms netcdf4 8.41±0.08ms 10.9±0.2ms ========= ============= ============= ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1523232313 https://github.com/pydata/xarray/issues/7430#issuecomment-1376029728,https://api.github.com/repos/pydata/xarray/issues/7430,1376029728,IC_kwDOAMm_X85SBIwg,14371165,2023-01-09T17:59:17Z,2023-01-09T17:59:17Z,MEMBER,"Try updating to latest xarray and dask. dask has had some nice updates lately, https://medium.com/pangeo/dask-distributed-and-pangeo-better-performance-for-everyone-thanks-to-science-software-63f85310a36b","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1525802030 https://github.com/pydata/xarray/pull/7382#issuecomment-1372796814,https://api.github.com/repos/pydata/xarray/issues/7382,1372796814,IC_kwDOAMm_X85R0zeO,14371165,2023-01-05T21:26:13Z,2023-01-05T21:26:13Z,MEMBER,"Thanks, @benbovy !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1498386428 https://github.com/pydata/xarray/issues/7422#issuecomment-1372763950,https://api.github.com/repos/pydata/xarray/issues/7422,1372763950,IC_kwDOAMm_X85R0rcu,14371165,2023-01-05T21:09:15Z,2023-01-05T21:09:15Z,MEMBER,"Hmm, this worked at some point. Must've gotten lost somewhere in one of the bigger plot refactors. Positional arguments have been deprecated though, so you should start getting used to using keyword arguments: https://docs.xarray.dev/en/stable/whats-new.html#v2022-11-0-nov-4-2022","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1521002414 https://github.com/pydata/xarray/pull/7418#issuecomment-1371430929,https://api.github.com/repos/pydata/xarray/issues/7418,1371430929,IC_kwDOAMm_X85RvmAR,14371165,2023-01-04T21:18:05Z,2023-01-04T21:18:05Z,MEMBER,Add a py.typed file in datatree to fix the mypy error: https://github.com/pydata/xarray/blob/main/xarray/py.typed,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,1519552711 https://github.com/pydata/xarray/pull/7400#issuecomment-1370866073,https://api.github.com/repos/pydata/xarray/issues/7400,1370866073,IC_kwDOAMm_X85RtcGZ,14371165,2023-01-04T12:25:45Z,2023-01-04T12:25:45Z,MEMBER,"Benchmark is a numba issue, probably #7306. Mypy is real, cannot getitem a object. Try out using isinstance instead of the try/except to narrow the typing.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1508009922 https://github.com/pydata/xarray/pull/7382#issuecomment-1353473644,https://api.github.com/repos/pydata/xarray/issues/7382,1353473644,IC_kwDOAMm_X85QrF5s,14371165,2022-12-15T17:43:29Z,2022-12-15T17:43:38Z,MEMBER,No benchmark is catching this? Maybe we can add a small one in https://github.com/pydata/xarray/blob/main/asv_bench/benchmarks/indexing.py ?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1498386428 https://github.com/pydata/xarray/pull/7360#issuecomment-1342256217,https://api.github.com/repos/pydata/xarray/issues/7360,1342256217,IC_kwDOAMm_X85QATRZ,14371165,2022-12-08T08:22:16Z,2022-12-08T08:22:16Z,MEMBER,The mypy errors should be fixed soon I think: https://github.com/dask/distributed/issues/7378,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1477162465 https://github.com/pydata/xarray/pull/7356#issuecomment-1339575144,https://api.github.com/repos/pydata/xarray/issues/7356,1339575144,IC_kwDOAMm_X85P2Eto,14371165,2022-12-06T15:44:01Z,2022-12-06T15:44:01Z,MEMBER,"I'm not really opposed to this change, shape and dtype uses `self._data` aswell. Without using `chunks={}` in open_dataset? I just find it a little odd that it's not a duck_array, what type is `self._data`? This test just looked so similar to the tests in #6797. I think you can do a similar lazy test taking inspiration from: https://github.com/pydata/xarray/blob/ed60c6ccd3d6725cd91190b8796af4355f3085c2/xarray/tests/test_formatting.py#L715-L727","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1475567394 https://github.com/pydata/xarray/pull/7356#issuecomment-1339423992,https://api.github.com/repos/pydata/xarray/issues/7356,1339423992,IC_kwDOAMm_X85P1fz4,14371165,2022-12-06T13:53:03Z,2022-12-06T13:53:03Z,MEMBER,"Is that test targetting your issue with RAM crashing the laptop? Shouldn't there be some check if the values were loaded? How did you import your data? self.data looks like this: https://github.com/pydata/xarray/blob/ed60c6ccd3d6725cd91190b8796af4355f3085c2/xarray/core/variable.py#L420-L435 I was expecting your data to be a duck_array?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1475567394 https://github.com/pydata/xarray/pull/7353#issuecomment-1336402438,https://api.github.com/repos/pydata/xarray/issues/7353,1336402438,IC_kwDOAMm_X85Pp-IG,14371165,2022-12-04T12:41:05Z,2022-12-04T12:41:05Z,MEMBER,"``` error libmamba Could not solve for environment specs Encountered problems while solving: - nothing provides hdf5 1.8.15* needed by netcdf4-1.2.4-np110py27_1 The environment can't be solved, aborting the operation ``` It's a bit annoying the ci isn't showing which package has netcdf4 as a dependency. Is that possible?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1474717029 https://github.com/pydata/xarray/pull/7323#issuecomment-1328331087,https://api.github.com/repos/pydata/xarray/issues/7323,1328331087,IC_kwDOAMm_X85PLLlP,14371165,2022-11-27T20:15:53Z,2022-11-27T20:16:24Z,MEMBER,"How about converting the dataset to dask dataframe? ```python ddf = ds.to_dask_dataframe() ddf.to_json(filename) ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1465047346 https://github.com/pydata/xarray/pull/7204#issuecomment-1328070169,https://api.github.com/repos/pydata/xarray/issues/7204,1328070169,IC_kwDOAMm_X85PKL4Z,14371165,2022-11-26T15:54:02Z,2022-11-26T15:54:02Z,MEMBER,I am merging this on friday next week if no one minds. :),"{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1420242462 https://github.com/pydata/xarray/pull/7315#issuecomment-1328068423,https://api.github.com/repos/pydata/xarray/issues/7315,1328068423,IC_kwDOAMm_X85PKLdH,14371165,2022-11-26T15:43:28Z,2022-11-26T15:43:28Z,MEMBER,Thank you @headtr1ck ! :),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1462057503 https://github.com/pydata/xarray/pull/7301#issuecomment-1328068009,https://api.github.com/repos/pydata/xarray/issues/7301,1328068009,IC_kwDOAMm_X85PKLWp,14371165,2022-11-26T15:41:07Z,2022-11-26T15:41:07Z,MEMBER,"Thanks, @jhamman !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1456026667 https://github.com/pydata/xarray/pull/7319#issuecomment-1326789280,https://api.github.com/repos/pydata/xarray/issues/7319,1326789280,IC_kwDOAMm_X85PFTKg,14371165,2022-11-24T19:20:31Z,2022-11-24T19:20:31Z,MEMBER,"Yeah it must be unrelated, I can't see how the doctest could be related to this.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1462833576 https://github.com/pydata/xarray/pull/7318#issuecomment-1325718667,https://api.github.com/repos/pydata/xarray/issues/7318,1325718667,IC_kwDOAMm_X85PBNyL,14371165,2022-11-23T22:14:38Z,2022-11-23T22:17:21Z,MEMBER,"Seaborn did something similar as the original but had a little check if the marker was filled or not: https://github.com/mwaskom/seaborn/blob/bf4695466d742f301f361b8d0c8168c5c4bdf889/seaborn/relational.py#L563","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1462470712 https://github.com/pydata/xarray/pull/6963#issuecomment-1322674412,https://api.github.com/repos/pydata/xarray/issues/6963,1322674412,IC_kwDOAMm_X85O1mjs,14371165,2022-11-21T21:31:48Z,2022-11-21T21:31:48Z,MEMBER,"Thanks, @lukeconibear !","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1353467346 https://github.com/pydata/xarray/pull/6963#issuecomment-1321501372,https://api.github.com/repos/pydata/xarray/issues/6963,1321501372,IC_kwDOAMm_X85OxIK8,14371165,2022-11-21T05:59:36Z,2022-11-21T05:59:36Z,MEMBER,"> > A good ol' copy/paste job works as expected though. :) I think we can discuss more elegant solutions in a follow up PR. > > So now mypy is not crashing anymore? Thats weird, we should open an issue on mypy about this... This one throws errors still: `python -m mypy --install-types --non-interactive --python-version 3.8 --follow-imports=silent` Did it ever crash if we used the normal mypy CI but with changed python version?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1353467346 https://github.com/pydata/xarray/pull/6963#issuecomment-1321231227,https://api.github.com/repos/pydata/xarray/issues/6963,1321231227,IC_kwDOAMm_X85OwGN7,14371165,2022-11-20T20:12:00Z,2022-11-20T20:12:00Z,MEMBER,"Dask is on the ignore list: https://github.com/pydata/xarray/blob/d6671dd414370d006254ba3156cb96256ce0e9c7/pyproject.toml#L31-L43 This seems to ignore the list and follow-imports doesn't seem to work either: ``` - name: Run mypy with python3.8 # silent all imports, since external repos might not support this run: | python -m mypy --install-types --non-interactive --python-version 3.8 --follow-imports=silent ``` A good ol' copy/paste job works as expected though. :) I think we can discuss more elegant solutions in a follow up PR.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1353467346 https://github.com/pydata/xarray/pull/7296#issuecomment-1321212836,https://api.github.com/repos/pydata/xarray/issues/7296,1321212836,IC_kwDOAMm_X85OwBuk,14371165,2022-11-20T18:52:12Z,2022-11-20T18:52:12Z,MEMBER,"Yeah, sounds reasonable. Maybe the reason for the ignore disappeared once DuckArrayModule was implemented?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1452339775 https://github.com/pydata/xarray/pull/7285#issuecomment-1321200061,https://api.github.com/repos/pydata/xarray/issues/7285,1321200061,IC_kwDOAMm_X85Ov-m9,14371165,2022-11-20T17:49:56Z,2022-11-20T17:49:56Z,MEMBER,"Mypy errors with python 3.8. Doesn't appear related to this PR at least. ``` Run python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report shell: /usr/bin/bash -l {0} env: CONDA_ENV_FILE: ci/requirements/environment.yml PYTHON_VERSION: 3.8 TODAY: 2022-11-20 MAMBA_ROOT_PREFIX: /home/runner/micromamba-root MAMBA_EXE: /home/runner/micromamba-bin/micromamba Collecting types-PyYAML Downloading types_PyYAML-6.0.12.2-py3-none-any.whl (14 kB) Collecting types-paramiko Downloading types_paramiko-2.12.0.1-py3-none-any.whl (32 kB) Collecting types-pytz Downloading types_pytz-2022.6.0.1-py3-none-any.whl (4.7 kB) Collecting types-setuptools Downloading types_setuptools-65.6.0.0-py3-none-any.whl (48 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.9/48.9 kB 19.4 MB/s eta 0:00:00 Collecting types-cryptography Downloading types_cryptography-3.3.23.2-py3-none-any.whl (30 kB) Installing collected packages: types-setuptools, types-PyYAML, types-pytz, types-cryptography, types-paramiko Successfully installed types-PyYAML-6.0.12.2 types-cryptography-3.3.23.2 types-paramiko-2.12.0.1 types-pytz-2022.6.0.1 types-setuptools-65.6.0.0 xarray/core/types.py:73: error: ""tuple"" is not subscriptable [misc] Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Installing missing stub packages: /home/runner/micromamba-root/envs/xarray-tests/bin/python -m pip install types-PyYAML types-paramiko types-pytz types-setuptools xarray/core/types.py:75: error: ""tuple"" is not subscriptable [misc] xarray/core/types.py:77: error: ""tuple"" is not subscriptable [misc] xarray/core/types.py:79: error: ""list"" is not subscriptable [misc] xarray/core/merge.py:43: error: ""tuple"" is not subscriptable [misc] xarray/core/merge.py:44: error: ""tuple"" is not subscriptable [misc] xarray/core/merge.py:45: error: ""tuple"" is not subscriptable [misc] xarray/backends/api.py:65: error: ""dict"" is not subscriptable [misc] Generated Cobertura report: /home/runner/work/xarray/xarray/mypy_report/cobertura.xml Found 8 errors in 3 files (checked 140 source files) ```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1447049720 https://github.com/pydata/xarray/pull/7277#issuecomment-1321100829,https://api.github.com/repos/pydata/xarray/issues/7277,1321100829,IC_kwDOAMm_X85OvmYd,14371165,2022-11-20T11:00:50Z,2022-11-20T11:00:50Z,MEMBER,"@dcherian, as you noted in that PR as well it's not just `matplotlib` but `xarray` too that does a lot of guessing already, `x,y` in `plot2d` for example. I was more concerned about consistency and believed we got closer to what the majority of the plotting functions does by guessing. These are the coords that we currently guess in plot1d: https://github.com/pydata/xarray/blob/d6671dd414370d006254ba3156cb96256ce0e9c7/xarray/plot/dataarray_plot.py#L154 Should we remove them, (empty tuple) and let the user explicitly define all of them? If so should we remove any guessing in the other plot functions as well?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1444440024 https://github.com/pydata/xarray/pull/7296#issuecomment-1321084794,https://api.github.com/repos/pydata/xarray/issues/7296,1321084794,IC_kwDOAMm_X85Ovid6,14371165,2022-11-20T09:52:02Z,2022-11-20T09:52:02Z,MEMBER,"I think the CI wasn't catching this because of: https://github.com/pydata/xarray/blob/63a69fe4b2fa7a4de8a1b65826f6af4869818166/pyproject.toml#L73-L77","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1452339775 https://github.com/pydata/xarray/pull/7281#issuecomment-1312087585,https://api.github.com/repos/pydata/xarray/issues/7281,1312087585,IC_kwDOAMm_X85ONN4h,14371165,2022-11-11T19:14:35Z,2022-11-11T19:16:42Z,MEMBER,"Markersize before PR: ![image](https://user-images.githubusercontent.com/14371165/201413282-cc4ffef5-473a-41e9-ad6c-3673300ddb76.png) Markersize after PR: ![image](https://user-images.githubusercontent.com/14371165/201413436-59738062-7b74-4d14-88e8-9d9a110339ac.png)
```python import numpy as np import matplotlib.pyplot as plt import xarray as xr temp = xr.DataArray(np.random.randn(10, 10, 2), coords=[np.arange(10), np.arange(10), [2021, 2022]], dims=[""lon"", ""lat"", ""year""]) prec = xr.DataArray(np.random.randn(10, 10, 2), coords=[np.arange(10), np.arange(10), [2021, 2022]], dims=[""lon"", ""lat"", ""year""]) one = xr.DataArray(np.random.randn(10, 10, 2), coords=[np.arange(10), np.arange(10), [2021, 2022]], dims=[""lon"", ""lat"", ""year""]) blue = xr.DataArray(np.random.randn(10, 10, 2), coords=[np.arange(10), np.arange(10), [2021, 2022]], dims=[""lon"", ""lat"", ""year""]) ds = xr.Dataset({""temperature"": temp, ""precipitation"": prec, 1: one, ""blue"": blue}) # Stack the non interesting dims: # fig, ax = plt.subplots() # ds.stack(stacked_dim=[...]).plot.scatter(x=""temperature"", y=""precipitation"") fig, ax = plt.subplots() ds.plot.scatter(x=""temperature"", y=""precipitation"", markersize=1) ```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1445870847 https://github.com/pydata/xarray/pull/7272#issuecomment-1311279880,https://api.github.com/repos/pydata/xarray/issues/7272,1311279880,IC_kwDOAMm_X85OKIsI,14371165,2022-11-11T06:24:06Z,2022-11-11T06:26:40Z,MEMBER,"* default markersize values of widths are 18 to 72. * plt.scatter default markersize is 36. * plt.plot default linewidth is 6. With the current version of the PR we would get 18 for 1-sized arrays, but 36 if markersize was undefined. This seems a bit inconsistent to me. I think we should default to 36 instead for 1-sized arrays, but this would require a bit more tweaks than the scope of the current PR. I think we'll merge this to fix the zero division -> np.nan -> empty plots. And then I'll come up with a another PR where the size is the same.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1440711212 https://github.com/pydata/xarray/pull/7277#issuecomment-1310792821,https://api.github.com/repos/pydata/xarray/issues/7277,1310792821,IC_kwDOAMm_X85OIRx1,14371165,2022-11-10T19:26:44Z,2022-11-10T19:26:44Z,MEMBER,"@jorisvandenbossche, feel free to try out this PR.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1444440024 https://github.com/pydata/xarray/pull/7123#issuecomment-1299061501,https://api.github.com/repos/pydata/xarray/issues/7123,1299061501,IC_kwDOAMm_X85Nbhr9,14371165,2022-11-01T19:57:53Z,2022-11-01T19:57:53Z,MEMBER,"Thanks, @DanielGoman !","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1396401446 https://github.com/pydata/xarray/pull/7204#issuecomment-1297256807,https://api.github.com/repos/pydata/xarray/issues/7204,1297256807,IC_kwDOAMm_X85NUpFn,14371165,2022-10-31T15:24:25Z,2022-10-31T15:24:25Z,MEMBER,"A lot of pep8 is quite gentle with the phrasing I think: `Avoid trailing whitespace anywhere.` is only a recommendation. `Limit all lines to a maximum of 79 characters.` is also only a recommendation, we ignore this one for automation consistency. Another nice perk with absolute paths is that you can immediately run a `utils.py` file and test out the functions, much faster workflow than having to do the proper `import` route.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1420242462 https://github.com/pydata/xarray/pull/7236#issuecomment-1297227274,https://api.github.com/repos/pydata/xarray/issues/7236,1297227274,IC_kwDOAMm_X85NUh4K,14371165,2022-10-31T15:04:13Z,2022-10-31T15:04:13Z,MEMBER,Thanks @hmaarrfk !,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1428274982 https://github.com/pydata/xarray/pull/7221#issuecomment-1293815240,https://api.github.com/repos/pydata/xarray/issues/7221,1293815240,IC_kwDOAMm_X85NHg3I,14371165,2022-10-27T16:58:45Z,2022-10-27T16:58:45Z,MEMBER,"``` before after ratio [c000690c] [24753f1f] - 3.17±0.02ms 1.94±0.01ms 0.61 merge.DatasetAddVariable.time_variable_insertion(100) - 81.5±2ms 17.0±0.2ms 0.21 merge.DatasetAddVariable.time_variable_insertion(1000) SOME BENCHMARKS HAVE CHANGED SIGNIFICANTLY. PERFORMANCE INCREASED. ``` Nice improvements. :) I haven't fully understood why we had that code though?","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1423312198