id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type 2163675672,PR_kwDOAMm_X85obI_8,8803,missing chunkmanager: update error message,10194086,open,0,,,4,2024-03-01T15:48:00Z,2024-03-15T11:02:45Z,,MEMBER,,0,pydata/xarray/pulls/8803,"When dask is missing we get the following error message: ```python-traceback ValueError: unrecognized chunk manager dask - must be one of: [] ``` this could be confusing - the error message seems geared towards a typo in the requested manager. However, I think it's much more likely that a chunk manager is just not installed. I tried to update the error message - happy to get feedback.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8803/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2137065741,PR_kwDOAMm_X85nAXC5,8756,suppress base & loffset deprecation warnings,10194086,closed,0,,,2,2024-02-15T17:23:27Z,2024-02-16T09:44:32Z,2024-02-15T19:11:10Z,MEMBER,,0,pydata/xarray/pulls/8756," Supress some more internal warnings in the test suite. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8756/reactions"", ""total_count"": 3, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 3, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2090265314,PR_kwDOAMm_X85kiCi8,8627,unify freq strings (independent of pd version),10194086,closed,0,,,4,2024-01-19T10:57:04Z,2024-02-15T17:53:42Z,2024-02-15T16:53:36Z,MEMBER,,0,pydata/xarray/pulls/8627," - [ ] Adresses points 2 and 3 and closes #8612 - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Probably not ready for review yet. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8627/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2083501344,I_kwDOAMm_X858L7Ug,8612,more frequency string updates?,10194086,closed,0,,,5,2024-01-16T09:56:48Z,2024-02-15T16:53:37Z,2024-02-15T16:53:37Z,MEMBER,,,,"### What is your issue? I looked a bit into the frequency string update & found 3 issues we could improve upon. 1. Apart from `""M""`, pandas also deprecated `""Y""`, and `""Q""`, in favor of `""YE""` and `""QE""`. (And they are discussing renaming `""MS""` to `""MB""`). Should we do the same? 2. Should we translate the new freq strings to the old ones if pandas < 2.2 is installed? Otherwise we get the following situation: ```python import xarray as xr xr.date_range(""1600-02-01"", periods=3, freq=""M"") # deprecation warning xr.date_range(""1600-02-01"", periods=3, freq=""ME"") # ValueError: Invalid frequency: ME ``` 3. `date_range_like` can emit deprecation warnings without a way to mitigate them if pandas < 2.2 is installed. (When a `DatetimeIndex`) is passed. Could be nice to translate the old freq string to the new one without a warning. I have played around with 2. and 3. and can open a PR if you are on board. @spencerkclark @aulemahal - pandas-dev/pandas#55792 - pandas-dev/pandas#55553 - pandas-dev/pandas#56840 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8612/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 2130313810,PR_kwDOAMm_X85mpS8i,8737,unstack: require unique MultiIndex,10194086,closed,0,,,2,2024-02-12T14:58:06Z,2024-02-13T09:48:51Z,2024-02-13T09:48:36Z,MEMBER,,0,pydata/xarray/pulls/8737," - [x] Closes #7104 - [x] Tests added - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Unstacking non-unique MultiIndex can lead to silent data loss, so we raise an error.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8737/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1918089795,I_kwDOAMm_X85yU7pD,8252,cannot use negative step to sel from zarr (without dask),10194086,closed,0,,,0,2023-09-28T18:52:07Z,2024-02-10T02:57:33Z,2024-02-10T02:57:33Z,MEMBER,,,,"### What happened? As per: https://github.com/pydata/xarray/pull/8246#discussion_r1340357405 Passing a negative step in a `slice` to select a non-chunked zarr-backed datasets raises an error. ### What did you expect to happen? zarr should allow negative step (probably?) ### Minimal Complete Verifiable Example ```Python import xarray as xr # create a zarr dataset air = xr.tutorial.open_dataset(""air_temperature"") air.to_zarr(""test.zarr"") ds = xr.open_dataset(""test.zarr"", engine=""zarr"") ds.air[::-1, ].load() # note that this works if the dataset is backed by dask ds_dask = xr.open_dataset(""test.zarr"", engine=""zarr"", chunks=""auto"") ds_dask.air[::-1, ].load() ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python File ~/code/xarray/xarray/core/parallelcompat.py:93, in guess_chunkmanager(manager) 91 if isinstance(manager, str): 92 if manager not in chunkmanagers: ---> 93 raise ValueError( 94 f""unrecognized chunk manager {manager} - must be one of: {list(chunkmanagers)}"" 95 ) 97 return chunkmanagers[manager] 98 elif isinstance(manager, ChunkManagerEntrypoint): 99 # already a valid ChunkManager so just pass through ValueError: unrecognized chunk manager dask - must be one of: [] ``` ### Anything else we need to know? The error comes from https://github.com/zarr-developers/zarr-python/blob/6ec746ef1242dd9fec26b128cc0b3455d28ad6f0/zarr/indexing.py#L174 so it would need an upstream fix first. cc @dcherian is this what you had in mind? ### Environment
INSTALLED VERSIONS ------------------ commit: f6d69a1f6d952dcd67609c97f3fb3069abdda586 python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] python-bits: 64 OS: Linux OS-release: 6.2.0-33-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.14.2 libnetcdf: 4.9.2 xarray: 2023.9.1.dev8+gf6d69a1f pandas: 2.1.1 numpy: 1.24.4 scipy: 1.11.3 netCDF4: 1.6.4 pydap: installed h5netcdf: 1.2.0 h5py: 3.9.0 Nio: None zarr: 2.16.1 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.7.0 bottleneck: 1.3.7 dask: 2023.9.2 distributed: None matplotlib: 3.8.0 cartopy: 0.22.0 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.9.2 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.7.2 numpy_groupies: 0.10.1 setuptools: 68.2.2 pip: 23.2.1 conda: None pytest: 7.4.2 mypy: None IPython: 8.15.0 sphinx: None
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8252/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 2126795367,PR_kwDOAMm_X85mdn7J,8727,ruff: move some config to lint section,10194086,closed,0,,,0,2024-02-09T09:48:17Z,2024-02-09T15:49:03Z,2024-02-09T15:49:03Z,MEMBER,,0,pydata/xarray/pulls/8727," Fix a warning from ruff concerning the config: warning: The top-level linter settings are deprecated in favour of their counterparts in the `lint` section. Please update the following options in `pyproject.toml`: - `'extend-safe-fixes'` -> `'lint.extend-safe-fixes'` - `'per-file-ignores'` -> `'lint.per-file-ignores'` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8727/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2105703882,I_kwDOAMm_X859gn3K,8679,Dataset.weighted along a dimension not on weights errors,10194086,open,0,,,2,2024-01-29T15:03:39Z,2024-02-04T11:24:54Z,,MEMBER,,,,"### What happened? `ds.weighted(weights).mean(dims)` errors when reducing over a dimension that is neither on the `weights` nor on the variable. ### What did you expect to happen? This used to work and was ""broken"" by #8606. However, we may want to fix this by ignoring (?) those data vars instead (#7027). ### Minimal Complete Verifiable Example ```Python import xarray as xr ds = xr.Dataset({""a"": ((""y"", ""x""), [[1, 2]]), ""scalar"": 1}) weights = xr.DataArray([1, 2], dims=""x"") ds.weighted(weights).mean(""y"") ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. - [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies. ### Relevant log output ```Python ValueError Traceback (most recent call last) Cell In[1], line 6 3 ds = xr.Dataset({""a"": ((""y"", ""x""), [[1, 2]]), ""scalar"": 1}) 4 weights = xr.DataArray([1, 2], dims=""x"") ----> 6 ds.weighted(weights).mean(""y"") File ~/code/xarray/xarray/util/deprecation_helpers.py:115, in _deprecate_positional_args.._decorator..inner(*args, **kwargs) 111 kwargs.update({name: arg for name, arg in zip_args}) 113 return func(*args[:-n_extra_args], **kwargs) --> 115 return func(*args, **kwargs) File ~/code/xarray/xarray/core/weighted.py:497, in Weighted.mean(self, dim, skipna, keep_attrs) 489 @_deprecate_positional_args(""v2023.10.0"") 490 def mean( 491 self, (...) 495 keep_attrs: bool | None = None, 496 ) -> T_Xarray: --> 497 return self._implementation( 498 self._weighted_mean, dim=dim, skipna=skipna, keep_attrs=keep_attrs 499 ) File ~/code/xarray/xarray/core/weighted.py:558, in DatasetWeighted._implementation(self, func, dim, **kwargs) 555 def _implementation(self, func, dim, **kwargs) -> Dataset: 556 self._check_dim(dim) --> 558 return self.obj.map(func, dim=dim, **kwargs) File ~/code/xarray/xarray/core/dataset.py:6924, in Dataset.map(self, func, keep_attrs, args, **kwargs) 6922 if keep_attrs is None: 6923 keep_attrs = _get_keep_attrs(default=False) -> 6924 variables = { 6925 k: maybe_wrap_array(v, func(v, *args, **kwargs)) 6926 for k, v in self.data_vars.items() 6927 } 6928 if keep_attrs: 6929 for k, v in variables.items(): File ~/code/xarray/xarray/core/dataset.py:6925, in (.0) 6922 if keep_attrs is None: 6923 keep_attrs = _get_keep_attrs(default=False) 6924 variables = { -> 6925 k: maybe_wrap_array(v, func(v, *args, **kwargs)) 6926 for k, v in self.data_vars.items() 6927 } 6928 if keep_attrs: 6929 for k, v in variables.items(): File ~/code/xarray/xarray/core/weighted.py:286, in Weighted._weighted_mean(self, da, dim, skipna) 278 def _weighted_mean( 279 self, 280 da: T_DataArray, 281 dim: Dims = None, 282 skipna: bool | None = None, 283 ) -> T_DataArray: 284 """"""Reduce a DataArray by a weighted ``mean`` along some dimension(s)."""""" --> 286 weighted_sum = self._weighted_sum(da, dim=dim, skipna=skipna) 288 sum_of_weights = self._sum_of_weights(da, dim=dim) 290 return weighted_sum / sum_of_weights File ~/code/xarray/xarray/core/weighted.py:276, in Weighted._weighted_sum(self, da, dim, skipna) 268 def _weighted_sum( 269 self, 270 da: T_DataArray, 271 dim: Dims = None, 272 skipna: bool | None = None, 273 ) -> T_DataArray: 274 """"""Reduce a DataArray by a weighted ``sum`` along some dimension(s)."""""" --> 276 return self._reduce(da, self.weights, dim=dim, skipna=skipna) File ~/code/xarray/xarray/core/weighted.py:231, in Weighted._reduce(da, weights, dim, skipna) 227 da = da.fillna(0.0) 229 # `dot` does not broadcast arrays, so this avoids creating a large 230 # DataArray (if `weights` has additional dimensions) --> 231 return dot(da, weights, dim=dim) File ~/code/xarray/xarray/util/deprecation_helpers.py:140, in deprecate_dims..wrapper(*args, **kwargs) 132 emit_user_level_warning( 133 ""The `dims` argument has been renamed to `dim`, and will be removed "" 134 ""in the future. This renaming is taking place throughout xarray over the "" (...) 137 PendingDeprecationWarning, 138 ) 139 kwargs[""dim""] = kwargs.pop(""dims"") --> 140 return func(*args, **kwargs) File ~/code/xarray/xarray/core/computation.py:1885, in dot(dim, *arrays, **kwargs) 1883 dim = tuple(d for d, c in dim_counts.items() if c > 1) 1884 else: -> 1885 dim = parse_dims(dim, all_dims=tuple(all_dims)) 1887 dot_dims: set[Hashable] = set(dim) 1889 # dimensions to be parallelized File ~/code/xarray/xarray/core/utils.py:1046, in parse_dims(dim, all_dims, check_exists, replace_none) 1044 dim = (dim,) 1045 if check_exists: -> 1046 _check_dims(set(dim), set(all_dims)) 1047 return tuple(dim) File ~/code/xarray/xarray/core/utils.py:1131, in _check_dims(dim, all_dims) 1129 if wrong_dims: 1130 wrong_dims_str = "", "".join(f""'{d!s}'"" for d in wrong_dims) -> 1131 raise ValueError( 1132 f""Dimension(s) {wrong_dims_str} do not exist. Expected one or more of {all_dims}"" 1133 ) ValueError: Dimension(s) 'y' do not exist. Expected one or more of {'x'} ``` ### Anything else we need to know? _No response_ ### Environment Newest main (i.e. 2024.01) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8679/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 2098122391,PR_kwDOAMm_X85k8eI1,8651,allow negative freq strings,10194086,closed,0,,,2,2024-01-24T12:04:39Z,2024-02-01T09:17:11Z,2024-02-01T09:01:44Z,MEMBER,,0,pydata/xarray/pulls/8651," - [ ] Closes #xxxx - [x] Tests added - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` This allows negative freq strings as discussed in https://github.com/pydata/xarray/pull/8627#issuecomment-1905981660 Deciding which tests to update was not easy. The pandas `_generate_range` function was moved to https://github.com/pandas-dev/pandas/blob/3c96b8ff6d399fbec8d4d533e8e8618c592bb64b/pandas/core/arrays/datetimes.py#L2725 They no longer `rollback` the `end`. I had to remove this as well such that the following are eqivalent: ```python xr.date_range(""2001"", ""2000"", freq=""-1YE"", calendar=""noleap"") pd.date_range(""2001"", ""2000"", freq=""-1YE"") ``` I am slightly nervous about this but all the tests still pass... Once again cc @spencerkclark ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8651/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2105738254,PR_kwDOAMm_X85lVsgz,8680,use ruff.flake8-tidy-imports to enforce absolute imports,10194086,closed,0,,,1,2024-01-29T15:19:34Z,2024-01-30T16:42:46Z,2024-01-30T16:38:48Z,MEMBER,,0,pydata/xarray/pulls/8680," use ruff.flake8-tidy-imports to enforce absolute imports - https://github.com/MarcoGorelli/absolufy-imports has been archived (no reason given) - removes a pre-commit hook which should make it faster locally ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8680/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2098131640,PR_kwDOAMm_X85k8gJe,8652,new whats-new section,10194086,closed,0,,,2,2024-01-24T12:10:07Z,2024-01-26T10:07:39Z,2024-01-24T12:59:49Z,MEMBER,,0,pydata/xarray/pulls/8652," - [ ] Closes #xxxx - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8652/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2097971637,PR_kwDOAMm_X85k789-,8649,ruff: use extend-exclude,10194086,closed,0,,,1,2024-01-24T10:39:46Z,2024-01-24T18:32:20Z,2024-01-24T15:59:11Z,MEMBER,,0,pydata/xarray/pulls/8649," I think we should use `extend-exclude` instead of `exclude` for ruff. We can then also remove `"".eggs""` as this is in the default. From https://docs.astral.sh/ruff/settings/#exclude: > Note that you'll typically want to use [extend-exclude](https://docs.astral.sh/ruff/settings/#extend-exclude) to modify the excluded paths. > > Default value: ["".bzr"", "".direnv"", "".eggs"", "".git"", "".git-rewrite"", "".hg"", "".mypy_cache"", "".nox"", "".pants.d"", "".pytype"", "".ruff_cache"", "".svn"", "".tox"", "".venv"", ""\_\_pypackages\_\_"", ""_build"", ""buck-out"", ""build"", ""dist"", ""node_modules"", ""venv""] (I really dislike how github formats toml files... What would be the correct syntax, then?)","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8649/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2094542307,PR_kwDOAMm_X85kwUlb,8642,infer_freq: return 'YE' (#8629 follow-up),10194086,closed,0,,,0,2024-01-22T18:53:52Z,2024-01-23T12:44:14Z,2024-01-23T12:44:14Z,MEMBER,,0,pydata/xarray/pulls/8642," I realized that the return value of `infer_freq` was not updated. #8627 will try to suppress all warnings in the test suite, so this is just the minimal PR. Sorry for all the spam @spencerkclark ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8642/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2090340727,PR_kwDOAMm_X85kiTjg,8629,"rename ""Y"" freq string to ""YE"" (pandas parity)",10194086,closed,0,,,10,2024-01-19T11:31:58Z,2024-01-22T18:38:06Z,2024-01-22T08:01:24Z,MEMBER,,0,pydata/xarray/pulls/8629," - [x] Adresses point 1 of #8612 - [x] Fixes one of the failures in #8623 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` This renames the frequency string `""Y""` (formerly `""A""`) to `""YE""` to achieve pandas parity. It could be better to wait for the conclusion of pandas-dev/pandas#56840 before doing this (but fixing the related failure in #8623 seemed a good reason as any to do it know). Let me know what you think @spencerkclark @aulemahal ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8629/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2070895451,PR_kwDOAMm_X85jf-2J,8600,fix and test empty CFTimeIndex,10194086,closed,0,,,1,2024-01-08T17:11:43Z,2024-01-17T12:29:11Z,2024-01-15T21:49:34Z,MEMBER,,0,pydata/xarray/pulls/8600," - [x] Closes #7298 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Otherwise `da.indexes` and the html repr raise a `ValueError`. I first had `""""` but I think `None` is better. cc @spencerkclark @keewis ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8600/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1455395909,I_kwDOAMm_X85Wv5RF,7298,html repr fails for empty cftime arrays,10194086,closed,0,,,1,2022-11-18T16:09:00Z,2024-01-15T21:49:36Z,2024-01-15T21:49:35Z,MEMBER,,,,"### What happened? The html repr of a cftime array wants to display the ""calendar"", which it cannot if it is empty. ### What did you expect to happen? No error. ### Minimal Complete Verifiable Example ```Python import numpy as np import xarray as xr data_obs = np.random.randn(3) time_obs = xr.date_range(""2000-01-01"", periods=3, freq=""YS"", calendar=""noleap"") obs = xr.DataArray(data_obs, coords={""time"": time_obs}) o = obs[:0] xr.core.formatting_html.array_repr(o) ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python ValueError Traceback (most recent call last) Input In [1], in () 8 obs = xr.DataArray(data_obs, coords={""time"": time_obs}) 10 o = obs[:0] ---> 12 xr.core.formatting_html.array_repr(o) File ~/code/xarray/xarray/core/formatting_html.py:318, in array_repr(arr) 316 if hasattr(arr, ""xindexes""): 317 indexes = _get_indexes_dict(arr.xindexes) --> 318 sections.append(index_section(indexes)) 320 sections.append(attr_section(arr.attrs)) 322 return _obj_repr(arr, header_components, sections) File ~/code/xarray/xarray/core/formatting_html.py:195, in _mapping_section(mapping, name, details_func, max_items_collapse, expand_option_name, enabled) 188 expanded = _get_boolean_with_default( 189 expand_option_name, n_items < max_items_collapse 190 ) 191 collapsed = not expanded 193 return collapsible_section( 194 name, --> 195 details=details_func(mapping), 196 n_items=n_items, 197 enabled=enabled, 198 collapsed=collapsed, 199 ) File ~/code/xarray/xarray/core/formatting_html.py:155, in summarize_indexes(indexes) 154 def summarize_indexes(indexes): --> 155 indexes_li = """".join( 156 f""
  • {summarize_index(v, i)}
    • "" 157 for v, i in indexes.items() 158 ) 159 return f""
      {indexes_li}
    "" File ~/code/xarray/xarray/core/formatting_html.py:156, in (.0) 154 def summarize_indexes(indexes): 155 indexes_li = """".join( --> 156 f""
  • {summarize_index(v, i)}
    • "" 157 for v, i in indexes.items() 158 ) 159 return f""
      {indexes_li}
    "" File ~/code/xarray/xarray/core/formatting_html.py:140, in summarize_index(coord_names, index) 138 index_id = f""index-{uuid.uuid4()}"" 139 preview = escape(inline_index_repr(index)) --> 140 details = short_index_repr_html(index) 142 data_icon = _icon(""icon-database"") 144 return ( 145 f""
    {name}
    "" 146 f""
    {preview}
    "" (...) 150 f""
    {details}
    "" 151 ) File ~/code/xarray/xarray/core/formatting_html.py:132, in short_index_repr_html(index) 129 if hasattr(index, ""_repr_html_""): 130 return index._repr_html_() --> 132 return f""
    {escape(repr(index))}
    "" File ~/code/xarray/xarray/core/indexes.py:547, in PandasIndex.__repr__(self) 546 def __repr__(self): --> 547 return f""PandasIndex({repr(self.index)})"" File ~/code/xarray/xarray/coding/cftimeindex.py:353, in CFTimeIndex.__repr__(self) 345 end_str = format_times( 346 self.values[-REPR_ELLIPSIS_SHOW_ITEMS_FRONT_END:], 347 display_width, 348 offset=offset, 349 first_row_offset=offset, 350 ) 351 datastr = ""\n"".join([front_str, f""{' '*offset}..."", end_str]) --> 353 attrs_str = format_attrs(self) 354 # oneliner only if smaller than display_width 355 full_repr_str = f""{klass_name}([{datastr}], {attrs_str})"" File ~/code/xarray/xarray/coding/cftimeindex.py:272, in format_attrs(index, separator) 267 def format_attrs(index, separator="", ""): 268 """"""Format attributes of CFTimeIndex for __repr__."""""" 269 attrs = { 270 ""dtype"": f""'{index.dtype}'"", 271 ""length"": f""{len(index)}"", --> 272 ""calendar"": f""'{index.calendar}'"", 273 ""freq"": f""'{index.freq}'"" if len(index) >= 3 else None, 274 } 276 attrs_str = [f""{k}={v}"" for k, v in attrs.items()] 277 attrs_str = f""{separator}"".join(attrs_str) File ~/code/xarray/xarray/coding/cftimeindex.py:698, in CFTimeIndex.calendar(self) 695 """"""The calendar used by the datetimes in the index."""""" 696 from .times import infer_calendar_name --> 698 return infer_calendar_name(self) File ~/code/xarray/xarray/coding/times.py:374, in infer_calendar_name(dates) 371 return sample.calendar 373 # Error raise if dtype is neither datetime or ""O"", if cftime is not importable, and if element of 'O' dtype is not cftime. --> 374 raise ValueError(""Array does not contain datetime objects."") ValueError: Array does not contain datetime objects. ``` ### Anything else we need to know? Bisected to 7379923de756a2bcc59044d548f8ab7a68b91d4e use `_repr_inline_` for indexes that define it. ### Environment
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7298/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 2070231449,PR_kwDOAMm_X85jdtRr,8597,_infer_dtype: remove duplicated code,10194086,closed,0,,,0,2024-01-08T11:12:18Z,2024-01-08T19:40:06Z,2024-01-08T19:40:06Z,MEMBER,,0,pydata/xarray/pulls/8597," By chance I saw that in #4700 the same code block was added twice. I think this can be removed. cc @andersy005 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8597/reactions"", ""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 1, ""eyes"": 0}",,,13221727,pull 2070561434,PR_kwDOAMm_X85je1rK,8598,small string fixes,10194086,closed,0,,,1,2024-01-08T14:20:56Z,2024-01-08T16:59:27Z,2024-01-08T16:53:00Z,MEMBER,,0,pydata/xarray/pulls/8598," ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8598/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2025652693,PR_kwDOAMm_X85hJh0D,8521,test and fix empty xindexes repr,10194086,closed,0,,,4,2023-12-05T08:54:56Z,2024-01-08T10:58:09Z,2023-12-06T17:06:15Z,MEMBER,,0,pydata/xarray/pulls/8521," - [x] Closes #8367 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Uses `max` with a default, which work with empty iterators, in contrast to `if col_items else 0`.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8521/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1959175248,I_kwDOAMm_X850xqRQ,8367,`da.xindexes` or `da.indexes` raises an error if there are none (in the repr),10194086,closed,0,,,1,2023-10-24T12:45:12Z,2023-12-06T17:06:16Z,2023-12-06T17:06:16Z,MEMBER,,,,"### What happened? `da.xindexes` or `da.indexes` raises an error when trying to generate the repr if there are no coords (indexes) ### What did you expect to happen? Displaying an empty Mappable? ### Minimal Complete Verifiable Example ```Python xr.DataArray([3, 5]).indexes xr.DataArray([3, 5]).xindexes ``` ### MVCE confirmation - [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [x] Complete example — the example is self-contained, including all data and the text of any traceback. - [x] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [x] New issue — a search of GitHub Issues suggests this is not a duplicate. - [x] Recent environment — the issue occurs with the latest version of xarray and its dependencies. ### Relevant log output ```Python Out[9]: --------------------------------------------------------------------------- ValueError Traceback (most recent call last) File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/core/formatters.py:708, in PlainTextFormatter.__call__(self, obj) 701 stream = StringIO() 702 printer = pretty.RepresentationPrinter(stream, self.verbose, 703 self.max_width, self.newline, 704 max_seq_length=self.max_seq_length, 705 singleton_pprinters=self.singleton_printers, 706 type_pprinters=self.type_printers, 707 deferred_pprinters=self.deferred_printers) --> 708 printer.pretty(obj) 709 printer.flush() 710 return stream.getvalue() File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/lib/pretty.py:410, in RepresentationPrinter.pretty(self, obj) 407 return meth(obj, self, cycle) 408 if cls is not object \ 409 and callable(cls.__dict__.get('__repr__')): --> 410 return _repr_pprint(obj, self, cycle) 412 return _default_pprint(obj, self, cycle) 413 finally: File ~/.conda/envs/xarray_dev/lib/python3.10/site-packages/IPython/lib/pretty.py:778, in _repr_pprint(obj, p, cycle) 776 """"""A pprint that just redirects to the normal repr function."""""" 777 # Find newlines and replace them with p.break_() --> 778 output = repr(obj) 779 lines = output.splitlines() 780 with p.group(): File ~/code/xarray/xarray/core/indexes.py:1659, in Indexes.__repr__(self) 1657 def __repr__(self): 1658 indexes = formatting._get_indexes_dict(self) -> 1659 return formatting.indexes_repr(indexes) File ~/code/xarray/xarray/core/formatting.py:474, in indexes_repr(indexes, max_rows) 473 def indexes_repr(indexes, max_rows: int | None = None) -> str: --> 474 col_width = _calculate_col_width(chain.from_iterable(indexes)) 476 return _mapping_repr( 477 indexes, 478 ""Indexes"", (...) 482 max_rows=max_rows, 483 ) File ~/code/xarray/xarray/core/formatting.py:341, in _calculate_col_width(col_items) 340 def _calculate_col_width(col_items): --> 341 max_name_length = max(len(str(s)) for s in col_items) if col_items else 0 342 col_width = max(max_name_length, 7) + 6 343 return col_width ValueError: max() arg is an empty sequence ``` ### Anything else we need to know? _No response_ ### Environment
    INSTALLED VERSIONS ------------------ commit: ccc8f9987b553809fb6a40c52fa1a8a8095c8c5f python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] python-bits: 64 OS: Linux OS-release: 6.2.0-35-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.14.2 libnetcdf: 4.9.2 xarray: 2023.9.1.dev8+gf6d69a1f pandas: 2.1.1 numpy: 1.24.4 scipy: 1.11.3 netCDF4: 1.6.4 pydap: installed h5netcdf: 1.2.0 h5py: 3.9.0 Nio: None zarr: 2.16.1 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.7.0 bottleneck: 1.3.7 dask: 2023.9.2 distributed: None matplotlib: 3.8.0 cartopy: 0.22.0 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.9.2 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.7.2 numpy_groupies: 0.10.1 setuptools: 68.2.2 pip: 23.2.1 conda: None pytest: 7.4.2 mypy: 1.5.1 IPython: 8.15.0 sphinx: None
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8367/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 722168932,MDU6SXNzdWU3MjIxNjg5MzI=,4513,"where should keep_attrs be set in groupby, resample, weighted etc.?",10194086,closed,0,,,2,2020-10-15T09:36:43Z,2023-11-10T16:58:35Z,2023-11-10T16:58:35Z,MEMBER,,,,"I really should not open this can of worms but per https://github.com/pydata/xarray/issues/4450#issuecomment-697507489: > I'm always confused about whether `ds.groupby(..., keep_attrs=True).mean()` or `ds.groupby(...).mean(keep_attrs=True)` is correct. (similarly for rolling, coarsen etc.) Also as I try to fix the `keep_attr` behavior in #4510 it would be good to know where they should go. So I tried to figure out how this is currently handled and found the following: **`ds.xxx(keep_attrs=True).yyy()`** - all fixed **`ds.xxx().yyy(keep_attrs=True)`** - `coarsen` (fixed in #5227) - `groupby` - `groupby_bin` - `resample` - `rolling` (adjusted in #4510) - `rolling_exp` (fixed in #4592) - `weighted` So the working consensus seems to be to to `ds.xxx().yyy(keep_attrs=True)` - any comments on that? (Edit: looking at this it is only half as bad, ""only"" `coarsen`, `rolling` (#4510), and `rolling_exp` would need to be fixed.) ### Detailed analysis
    ```python import xarray as xr ds = xr.tutorial.open_dataset(""air_temperature"") da = ds.air ``` ### coarsen ```python ds.coarsen(time=2, keep_attrs=True).mean() # keeps global attributes ds.coarsen(time=2).mean(keep_attrs=True) # keeps DataArray attributes ds.coarsen(time=2, keep_attrs=True).mean(keep_attrs=True) # keeps both da.coarsen(time=2).mean(keep_attrs=True) # error da.coarsen(time=2, keep_attrs=True).mean() # keeps DataArray attributes ``` ### groupby ```python ds.groupby(""time.month"").mean(keep_attrs=True) # keeps both da.groupby(""time.month"").mean(keep_attrs=True) # keeps DataArray attributes ds.groupby(""time.month"", keep_attrs=True).mean() # error da.groupby(""time.month"", keep_attrs=True).mean() # error ``` ### groupby_bins ```python ds.groupby_bins(ds.lat, np.arange(0, 90, 10)).mean(keep_attrs=True) # keeps both da.groupby_bins(ds.lat, np.arange(0, 90, 10)).mean(keep_attrs=True) # keeps DataArray attrs ds.groupby_bins(ds.lat, np.arange(0, 90, 10), keep_attrs=True) # errors da.groupby_bins(ds.lat, np.arange(0, 90, 10), keep_attrs=True) # errors ``` ### resample ```python ds.resample(time=""A"").mean(keep_attrs=True) # keeps both da.resample(time=""A"").mean(keep_attrs=True) # keeps DataArray attributes ds.resample(time=""A"", keep_attrs=False).mean() # ignored da.resample(time=""A"", keep_attrs=False).mean() # ignored ``` ### rolling ```python ds.rolling(time=2).mean(keep_attrs=True) # keeps both da.rolling(time=2).mean(keep_attrs=True) # keeps DataArray attributes ds.rolling(time=2, keep_attrs=True).mean() # DeprecationWarning; keeps both da.rolling(time=2, keep_attrs=True).mean() # DeprecationWarning; keeps DataArray attributes ``` see #4510 ### rolling_exp ```python ds.rolling_exp(time=5, keep_attrs=True).mean() # ignored da.rolling_exp(time=5, keep_attrs=True).mean() # ignored ds.rolling_exp(time=5).mean(keep_attrs=True) # keeps both da.rolling_exp(time=5).mean(keep_attrs=True) # keeps DataArray attributes ``` ### weighted ```python ds.weighted(ds.lat).mean(keep_attrs=True) # keeps both da.weighted(ds.lat).mean(keep_attrs=True) # keeps DataArray attrs ```
    edit: moved `rolling` after #4510, moved `rolling_exp` after #4592 and `coarsen` after #5227","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4513/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1986324822,I_kwDOAMm_X852ZOlW,8436,align fails when more than one xindex is set,10194086,closed,0,,,2,2023-11-09T20:07:52Z,2023-11-10T12:53:49Z,2023-11-10T12:53:49Z,MEMBER,,,,"### What happened? I tried a DataArray with more than one dimension coordinate. Unfortunately `xr.align` fails, which disallows any arithmetic operation - even when the coords are exactly the same. ### What did you expect to happen? _No response_ ### Minimal Complete Verifiable Example ```Python import numpy as np import xarray as xr data = np.arange(12).reshape(3, 4) y = [10, 20, 30] s = [""a"", ""b"", ""c""] x = [1, 2, 3, 4] da = xr.DataArray(data, dims=(""y"", ""x""), coords={""x"": x, ""y"": y, ""s"": (""y"", s)}) da = da.set_xindex(""s"") xr.align(da, da.y) # errors da + da # errors da + da.x # errors ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. - [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies. ### Relevant log output ```Python --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /home/mathause/code/mesmer/devel/prepare_for_surfer.ipynb Cell 28 line 1 12 da = xr.DataArray(data, dims=(""y"", ""x""), coords={""x"": x, ""y"": y, ""s"": (""y"", s)}) 13 da = da.set_xindex(""s"") ---> 15 xr.align(da, da.y) # errors 17 da + da.x # errors File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:888, in align(join, copy, indexes, exclude, fill_value, *objects) 692 """""" 693 Given any number of Dataset and/or DataArray objects, returns new 694 objects with aligned indexes and dimension sizes. ref='~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:0'>0;32m (...) 878 879 """""" 880 aligner = Aligner( 881 objects, 882 join=join, ref='~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:0'>0;32m (...) 886 fill_value=fill_value, 887 ) --> 888 aligner.align() 889 return aligner.results File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:573, in Aligner.align(self) 571 self.find_matching_indexes() 572 self.find_matching_unindexed_dims() --> 573 self.assert_no_index_conflict() 574 self.align_indexes() 575 self.assert_unindexed_dim_sizes_equal() File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:318, in Aligner.assert_no_index_conflict(self) 314 if dup: 315 items_msg = "", "".join( 316 f""{k!r} ({v} conflicting indexes)"" for k, v in dup.items() 317 ) --> 318 raise ValueError( 319 ""cannot re-index or align objects with conflicting indexes found for "" 320 f""the following {msg}: {items_msg}\n"" 321 ""Conflicting indexes may occur when\n"" 322 ""- they relate to different sets of coordinate and/or dimension names\n"" 323 ""- they don't have the same type\n"" 324 ""- they may be used to reindex data along common dimensions"" 325 ) ValueError: cannot re-index or align objects with conflicting indexes found for the following dimensions: 'y' (2 conflicting indexes) Conflicting indexes may occur when - they relate to different sets of coordinate and/or dimension names - they don't have the same type - they may be used to reindex data along common dimensions ``` ### Anything else we need to know? _No response_ ### Environment
    INSTALLED VERSIONS ------------------ commit: feba6984aa914327408fee3c286dae15969d2a2f python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] python-bits: 64 OS: Linux OS-release: 6.2.0-36-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.14.2 libnetcdf: 4.9.2 xarray: 2023.9.1.dev8+gf6d69a1f pandas: 2.1.1 numpy: 1.24.4 scipy: 1.11.3 netCDF4: 1.6.4 pydap: installed h5netcdf: 1.2.0 h5py: 3.9.0 Nio: None zarr: 2.16.1 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.7.0 bottleneck: 1.3.7 dask: 2023.9.2 distributed: None matplotlib: 3.8.0 cartopy: 0.22.0 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.9.2 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.7.2 numpy_groupies: 0.10.1 setuptools: 68.2.2 pip: 23.2.1 conda: None pytest: 7.4.2 mypy: 1.5.1 IPython: 8.15.0 sphinx: None
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8436/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1657036222,I_kwDOAMm_X85ixF2-,7730,flox performance regression for cftime resampling,10194086,closed,0,,,8,2023-04-06T09:38:03Z,2023-10-15T03:48:44Z,2023-10-15T03:48:44Z,MEMBER,,,,"### What happened? Running an in-memory `groupby` operation took much longer than expected. Turning off flox fixed this - but I don't think that's the idea ;-) ### What did you expect to happen? flox to be at least on par with our naive implementation ### Minimal Complete Verifiable Example ```Python import numpy as np import xarray as xr arr = np.random.randn(10, 10, 365*30) time = xr.date_range(""2000"", periods=30*365, calendar=""noleap"") da = xr.DataArray(arr, dims=(""y"", ""x"", ""time""), coords={""time"": time}) # using max print(""max:"") xr.set_options(use_flox=True) %timeit da.groupby(""time.year"").max(""time"") %timeit da.groupby(""time.year"").max(""time"", engine=""flox"") xr.set_options(use_flox=False) %timeit da.groupby(""time.year"").max(""time"") # as reference %timeit [da.sel(time=str(year)).max(""time"") for year in range(2000, 2030)] # using mean print(""mean:"") xr.set_options(use_flox=True) %timeit da.groupby(""time.year"").mean(""time"") %timeit da.groupby(""time.year"").mean(""time"", engine=""flox"") xr.set_options(use_flox=False) %timeit da.groupby(""time.year"").mean(""time"") # as reference %timeit [da.sel(time=str(year)).mean(""time"") for year in range(2000, 2030)] ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python max: 158 ms ± 4.41 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) 28.1 ms ± 318 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) 11.5 ms ± 52.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) mean: 95.6 ms ± 10.8 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) 34.8 ms ± 2.88 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) 15.2 ms ± 232 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ``` ### Anything else we need to know? _No response_ ### Environment
    INSTALLED VERSIONS ------------------ commit: f8127fc9ad24fe8b41cce9f891ab2c98eb2c679a python: 3.10.10 | packaged by conda-forge | (main, Mar 24 2023, 20:08:06) [GCC 11.3.0] python-bits: 64 OS: Linux OS-release: 5.15.0-69-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: main pandas: 1.5.3 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: 2023.3.0 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: None pytest: 7.2.2 mypy: None IPython: 8.12.0 sphinx: None
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7730/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1177919687,PR_kwDOAMm_X8403yVS,6403,make more args kw only (except 'dim'),10194086,closed,0,,,9,2022-03-23T10:28:02Z,2023-10-05T20:38:49Z,2023-10-05T20:38:49Z,MEMBER,,0,pydata/xarray/pulls/6403," - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` This makes many arguments keyword-only, except for `dim` to avoid `da.weighted(...).mean(""lat"", ""lon"")` (i.e. `da.weighted(...).mean(dim=""lat"", skipna=""lon"")`) which silently does the wrong thing. I am sure I forgot some and for some I was unsure so I left them as is. Question: do we want an deprecation cycle? Currently it just errors for `da.weighted(...).mean(""dim"", True)`. Might be nice to do it, however, @dcherian if I am not mistaken you did this without a deprecation in #5950, e.g. for `da.mean` etc.? ```python import numpy as np import xarray as xr air = xr.tutorial.open_dataset(""air_temperature"") wgt = np.cos(np.deg2rad(air.lat)) air.weighted(wgt).mean(""lat"", ""lon"") ``` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6403/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1917660013,PR_kwDOAMm_X85bc7Pv,8246,update pytest config and un-xfail some tests,10194086,closed,0,,,1,2023-09-28T14:21:58Z,2023-09-30T01:26:39Z,2023-09-30T01:26:35Z,MEMBER,,0,pydata/xarray/pulls/8246," - [ ] Towards #8239 - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` This partly updates the pytest config as suggested in #8239 and un-xfails some tests (or xfails the tests more precisely). See https://github.com/pydata/xarray/issues/8239#issuecomment-1739363809 for why we cannot exactly follow the suggestions given in #8239 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8246/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 748684119,MDU6SXNzdWU3NDg2ODQxMTk=,4601,Don't type check __getattr__?,10194086,open,0,,,8,2020-11-23T10:41:21Z,2023-09-25T05:33:09Z,,MEMBER,,,,"In #4592 I had the issue that mypy did not raise an error on a missing method: ```python from xarray.core.common import DataWithCoords hasattr(xr.core.common.DataWithCoords, ""reduce"") # -> False def test(x: ""DataWithCoords""): x.reduce() # mypy does not error ``` This is because `DataWithCoords` implements `__getattr__`: ```python class A: pass class B: def __getattr__(self, name): ... def testA(x: ""A""): x.reduce() # mypy errors def testB(x: ""B""): x.reduce() # mypy does not error ``` The solution seems to be to not typecheck `__getattr__` (see https://github.com/python/mypy/issues/6251#issuecomment-457287161): ```python from typing import no_type_check class C: @no_type_check def __getattr__(self, name): ... def testC(x: ""C""): x.reduce() # mypy errors ``` The only `__getattr__` within xarray is here: https://github.com/pydata/xarray/blob/17358922d480c038e66430735bf4c365a7677df8/xarray/core/common.py#L221 Using `@no_type_check` leads to 24 errors and not all of them can be trivially solved. E.g. `DataWithCoords` [wants of use](https://github.com/pydata/xarray/blob/17358922d480c038e66430735bf4c365a7677df8/xarray/core/common.py#L368) `self.isel` but does not implement the method. The solution is probably to add `isel` to `DataWithCoords` as an `ABC` or using `NotImplemented`. Thoughts? **All errors**
    ```python-traceback xarray/core/common.py:370: error: ""DataWithCoords"" has no attribute ""isel"" xarray/core/common.py:374: error: ""DataWithCoords"" has no attribute ""dims"" xarray/core/common.py:378: error: ""DataWithCoords"" has no attribute ""indexes"" xarray/core/common.py:381: error: ""DataWithCoords"" has no attribute ""sizes"" xarray/core/common.py:698: error: ""DataWithCoords"" has no attribute ""_groupby_cls"" xarray/core/common.py:761: error: ""DataWithCoords"" has no attribute ""_groupby_cls"" xarray/core/common.py:866: error: ""DataWithCoords"" has no attribute ""_rolling_cls""; maybe ""_rolling_exp_cls""? xarray/core/common.py:977: error: ""DataWithCoords"" has no attribute ""_coarsen_cls"" xarray/core/common.py:1108: error: ""DataWithCoords"" has no attribute ""dims"" xarray/core/common.py:1109: error: ""DataWithCoords"" has no attribute ""dims"" xarray/core/common.py:1133: error: ""DataWithCoords"" has no attribute ""indexes"" xarray/core/common.py:1144: error: ""DataWithCoords"" has no attribute ""_resample_cls""; maybe ""resample""? xarray/core/common.py:1261: error: ""DataWithCoords"" has no attribute ""isel"" xarray/core/alignment.py:278: error: ""DataAlignable"" has no attribute ""copy"" xarray/core/alignment.py:283: error: ""DataAlignable"" has no attribute ""dims"" xarray/core/alignment.py:286: error: ""DataAlignable"" has no attribute ""indexes"" xarray/core/alignment.py:288: error: ""DataAlignable"" has no attribute ""sizes"" xarray/core/alignment.py:348: error: ""DataAlignable"" has no attribute ""dims"" xarray/core/alignment.py:351: error: ""DataAlignable"" has no attribute ""copy"" xarray/core/alignment.py:353: error: ""DataAlignable"" has no attribute ""reindex"" xarray/core/alignment.py:356: error: ""DataAlignable"" has no attribute ""encoding"" xarray/core/weighted.py:157: error: ""DataArray"" has no attribute ""notnull"" xarray/core/dataset.py:3792: error: ""Dataset"" has no attribute ""virtual_variables"" xarray/core/dataset.py:6135: error: ""DataArray"" has no attribute ""isnull"" ```
    Edit: one problem is certainly the method injection, as mypy cannot detect those types.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4601/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 235224055,MDU6SXNzdWUyMzUyMjQwNTU=,1449,time.units truncated when saving to_netcdf,10194086,closed,0,,,6,2017-06-12T12:58:37Z,2023-09-13T13:25:25Z,2023-09-13T13:25:24Z,MEMBER,,,,"When I manually specify the `units` attribute for time, and then save the Dataset `to_netcdf` the string is truncated. See exaple import pandas as pd import xarray as xr time = pd.date_range('2000-01-01', '2000-01-31', freq='6h') ds = xr.Dataset(coords=dict(time=time)) units = 'days since 1975-01-01 00:00:00' calendar = 'gregorian' encoding=dict(time=dict(units=units, calendar=calendar)) ds.to_netcdf('test.nc', format='NETCDF4_CLASSIC', encoding=encoding) ! ncdump -h test.nc # time:units = ""days since 1975-01-01"" ; Some programs seem to require the hours to be present to interpret the time properly (e.g. panoply). When specifying the hour, a 'T' is added. units = 'days since 1975-01-01 01:00:00' ! ncdump -h test.nc # time:units = ""days since 1975-01-01T01:00:00"" ; When xarray defines the `time.units` it works fine. ds = xr.Dataset(coords=dict(time=time)) ds.to_netcdf('test.nc', format='NETCDF4_CLASSIC',) ! ncdump -h test.nc # time:units = ""hours since 2000-01-01 00:00:00"" ; xarray version 0.9.6","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1449/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1876205625,PR_kwDOAMm_X85ZRl7U,8130,to_stacked_array: better error msg & refactor,10194086,closed,0,,,0,2023-08-31T19:51:08Z,2023-09-10T15:33:41Z,2023-09-10T15:33:37Z,MEMBER,,0,pydata/xarray/pulls/8130," - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` I found the error message in `ds.to_stacked_array` confusing, so I tried to make it clearer. Also renames some if the _internal_ symbols (so should have no user facing change).","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8130/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1371397741,I_kwDOAMm_X85Rvd5t,7027,"don't apply `weighted`, `groupby`, etc. to `DataArray` without `dims`?",10194086,open,0,,,1,2022-09-13T12:44:34Z,2023-08-26T19:13:39Z,,MEMBER,,,,"### What is your issue? Applying e.g. `ds.weighted(weights).mean()` applies the operation over all `DataArray` objects - even if they don't have the dimensions over which it is applied (or is a scalar variable). I don't think this is wanted. ```python import xarray as xr air = xr.tutorial.open_dataset(""air_temperature"") air.attrs = {} # add variable without dims air[""foo""] = 5 print(""resample"") print(air.resample(time=""MS"").mean(dim=""time"").foo.dims) print(""groupby"") print(air.groupby(""time.year"").mean(dim=""time"").foo.dims) print(""weighted"") print(air.weighted(weights=air.time.dt.year).mean(""lat"").foo.dims) print(""where"") print(air.where(air.air > 5).foo.dims) ``` Results ``` resample ('time',) groupby ('year',) weighted ('time',) ``` Related #6952 - I am sure there are other issues, but couldn't find them quickly... `rolling` and `coarsen` don't seem to do this. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7027/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1719805837,I_kwDOAMm_X85mgieN,7860,diff of cftime.Datetime,10194086,open,0,,,3,2023-05-22T14:21:06Z,2023-08-04T12:01:33Z,,MEMBER,,,,"### What happened? A cftime variable returns a timedelta64[ns] when calling `diff` / `+` / `-` and it can then not be added/ subtracted from the original data. ### What did you expect to happen? We can `add` cftime timedeltas. ### Minimal Complete Verifiable Example ```Python import xarray as xr air = xr.tutorial.open_dataset(""air_temperature"", use_cftime=True) air.time + air.time.diff(""time"") / 2 ``` ### MVCE confirmation - [x] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [x] Complete example — the example is self-contained, including all data and the text of any traceback. - [x] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [x] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python air.time.variable.values[1:] - air.time.variable.values[:-1] ``` returns `array([datetime.timedelta(seconds=21600), ...])` but then ```Python xr.Variable((""time"",), np.array([datetime.timedelta(0)])) ``` returns a `dtype='timedelta64[ns]'` array. ### Anything else we need to know? - See upstream PR: xarray-contrib/cf-xarray#441 - Similar to #7381 (but I don't think it's the same issue, feel free to close if you disagree) - That might need a special data type for timedeltas of cftime.Datetime objects, or allowing to add `'timedelta64[ns]'` to cftime.Datetime objects - The casting comes from https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/core/variable.py#L366 https://github.com/pydata/xarray/blob/d8ec3a3f6b02a8b941b484b3d254537af84b5fde/xarray/core/variable.py#L272 ### Environment
    INSTALLED VERSIONS ------------------ commit: d8ec3a3f6b02a8b941b484b3d254537af84b5fde python: 3.10.9 | packaged by conda-forge | (main, Feb 2 2023, 20:20:04) [GCC 11.3.0] python-bits: 64 OS: Linux OS-release: 5.14.21-150400.24.63-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: 2023.2.1.dev20+g06a87062 pandas: 1.5.3 numpy: 1.23.5 scipy: 1.10.1 netCDF4: 1.6.2 pydap: installed h5netcdf: 1.1.0 h5py: 3.8.0 Nio: None zarr: 2.13.6 cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: 3.2.2 iris: 3.4.1 bottleneck: 1.3.6 dask: 2023.2.1 distributed: 2023.2.1 matplotlib: 3.7.0 cartopy: 0.21.1 seaborn: 0.12.2 numbagg: 0.2.2 fsspec: 2023.1.0 cupy: None pint: 0.20.1 sparse: 0.14.0 flox: 0.6.8 numpy_groupies: 0.9.20 setuptools: 67.4.0 pip: 23.0.1 conda: None pytest: 7.2.1 mypy: None IPython: 8.11.0 sphinx: None
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7860/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 594669577,MDU6SXNzdWU1OTQ2Njk1Nzc=,3937,"compose weighted with groupby, coarsen, resample, rolling etc.",10194086,open,0,,,7,2020-04-05T22:00:40Z,2023-07-27T18:10:10Z,,MEMBER,,,,"It would be nice to make `weighted` work with `groupby` - e.g. [#3935 (comment)](https://github.com/pydata/xarray/pull/3935/files#r403742055) However, it is not entirely clear to me how that should be done. One way would be to do: ```python da.groupby(...).weighted(weights).mean() ``` this would require that the `groupby` operation is applied over the `weights` (how would this be done?) Or should it be ```python da.weighted(weights).groupby(...).mean() ``` but this seems less intuitive to me. Or ```python da.groupby(..., weights=weights).mean() ``` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3937/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1596025651,PR_kwDOAMm_X85Kj_KM,7548,supress namespace_package deprecation warning (doctests),10194086,closed,0,,,0,2023-02-23T00:15:41Z,2023-02-23T18:38:16Z,2023-02-23T18:38:15Z,MEMBER,,0,pydata/xarray/pulls/7548," Suppress the `pkg_resources.namespace_package` `DeprecationError` to make the doctest pass again (similar to #7322). This is reported upstream: pydap/pydap#277 and matplotlib/matplotlib#25244 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7548/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1086346755,PR_kwDOAMm_X84wKOjC,6096,Replace distutils.version with packaging.version,10194086,closed,0,,,9,2021-12-22T00:51:21Z,2023-01-20T21:00:42Z,2021-12-24T14:50:48Z,MEMBER,,0,pydata/xarray/pulls/6096," - [x] Closes #6092 - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` One change is that it is no longer possible to compare to a string, i.e. `version.parse(xr.__version__) < ""0.20.0""` errors. As mentioned in #6092 there are 3 options - if there is a preference I am happy to update this PR. ```python from distutils.version import LooseVersion from packaging import version LooseVersion(xr.__version__) version.parse(xr.__version__) version.Version(xr.__version__) # currently: if LooseVersion(mod.__version__) < LooseVersion(minversion): pass # options: if version.parse(mod.__version__) < version.parse(minversion): pass if version.Version(mod.__version__) < version.Version(minversion): pass if Version(mod.__version__) < Version(minversion): pass ``` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6096/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1466191758,PR_kwDOAMm_X85Dylku,7326,fix doctests: supress urllib3 warning,10194086,closed,0,,,1,2022-11-28T10:40:46Z,2022-12-05T20:11:16Z,2022-11-28T19:31:03Z,MEMBER,,0,pydata/xarray/pulls/7326," - [x] Closes #7322 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7326/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1285767883,PR_kwDOAMm_X846ahUs,6730,move da and ds fixtures to conftest.py,10194086,closed,0,,,9,2022-06-27T12:56:05Z,2022-12-05T20:11:08Z,2022-07-11T12:44:55Z,MEMBER,,0,pydata/xarray/pulls/6730," This PR renames the `da` and `ds` fixtures (to `da_fixture` and `ds_fixture`) and moves them to conftest.py. This allows to remove the flake8 error suppression for the tests and seems more how the fixtures are [intended to be used](https://docs.pytest.org/en/6.2.x/fixture.html#conftest-py-sharing-fixtures-across-multiple-files) (from the pytest side). I think the name changes makes it a bit more obvious what happens but moving them to may make it a bit less obvious (if you don't know where to look). Removing the flake8 error ignores also unearthed some unused imports: https://github.com/pydata/xarray/blob/787a96c15161c9025182291b672b3d3c5548a6c7/setup.cfg#L155-L156 (What I actually wanted to do is move the tests for `rolling` to it's own file - but I think it makes sense to do this first.)","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6730/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1344222732,PR_kwDOAMm_X849c2Wu,6934,deprecate_positional_args: remove stray print,10194086,closed,0,,,0,2022-08-19T09:58:53Z,2022-12-05T20:11:08Z,2022-08-19T10:25:32Z,MEMBER,,0,pydata/xarray/pulls/6934," I [forgot to remove](https://github.com/pydata/xarray/pull/6910#discussion_r948145640) some debug print statements in #6910 - thanks for noting @shoyer & @dcherian","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6934/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1464824094,PR_kwDOAMm_X85DuSjU,7321,fix flake8 config,10194086,closed,0,,,2,2022-11-25T18:16:07Z,2022-11-28T10:36:29Z,2022-11-28T10:33:00Z,MEMBER,,0,pydata/xarray/pulls/7321," flake8 v6 now errors on inline comments in the config file. I don't like it but oh well... ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7321/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 715730538,MDU6SXNzdWU3MTU3MzA1Mzg=,4491,deprecate pynio backend,10194086,closed,0,,,21,2020-10-06T14:27:20Z,2022-11-26T15:40:37Z,2022-11-26T15:40:37Z,MEMBER,,,," We are currently not testing with the newest version of netCDF4 because it is incompatible with pynio (the newest version is [1.5.4](https://github.com/Unidata/netcdf4-python/blob/master/Changelog), we are at [1.5.3](https://dev.azure.com/xarray/xarray/_build/results?buildId=3974&view=logs&j=ba13898e-1dfb-5ace-9966-8b7af3677790&t=0a8d5551-2e87-575f-4689-3e85d9688898&l=220)). This is unlikely to be fixed, see conda-forge/pynio-feedstock#90. Therefore we need to think how to setup the tests so we use the newest version of netCDF4. Maybe just remove it from `py38.yml`? And long term what to do with the pynio backend? Deprecate? Move to an external repo? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4491/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1372729718,I_kwDOAMm_X85R0jF2,7036,index refactor: more `_coord_names` than `_variables` on Dataset,10194086,closed,0,,,3,2022-09-14T10:19:00Z,2022-09-27T10:35:40Z,2022-09-27T10:35:40Z,MEMBER,,,,"### What happened? `xr.core.dataset.DataVariables` assumes that everything that is in `ds._dataset._variables` and not in `self._dataset._coord_names` is a ""data variable"". However, since the index refactor we can end up with more `_coord_names` than `_variables` which breaks a number of stuff (e.g. the repr). ### What did you expect to happen? Well it seems this assumption is now wrong. ### Minimal Complete Verifiable Example ```Python ds = xr.Dataset(coords={""a"": (""x"", [1, 2, 3]), ""b"": (""x"", ['a', 'b', 'c'])}) ds.set_index(z=['a', 'b']).reset_index(""z"", drop=True) ``` ### MVCE confirmation - [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [ ] Complete example — the example is self-contained, including all data and the text of any traceback. - [ ] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result. - [ ] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python ValueError: __len__() should return >= 0 ``` ### Anything else we need to know? The error comes from here https://github.com/pydata/xarray/blob/63ba862d03c8d0cd8b44d2071bc360e9fed4519d/xarray/core/dataset.py#L368 Bisected to #5692 - which probably does not help too much. ### Environment
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7036/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1118802352,PR_kwDOAMm_X84xzhTi,6212,better warning filter for assert_*,10194086,closed,0,,,1,2022-01-31T00:22:37Z,2022-09-05T07:52:09Z,2022-09-05T07:52:06Z,MEMBER,,0,pydata/xarray/pulls/6212,"In #4864 I added a a decorator for the `xarray.testing.assert_*` functions to ensure warnings that were to errors (`pytest.mark.filterwarnings(""error"")`) do not error in `assert_*` (see https://github.com/pydata/xarray/pull/4760#issuecomment-774101639). As a solution I added https://github.com/pydata/xarray/blob/5470d933452d88deb17cc9294a164c4a03f55dec/xarray/testing.py#L32 However, this is sub-optimal because this now removes all `ignore` filters! As dask stuff only gets evaluated in `assert_*` filters like `warnings.filterwarnings(""ignore"", ""Mean of empty slice"")` don't work for dask arrays! I thought of setting ```python warnings.simplefilter(""ignore"") ``` but this could suppress warnings we want to keep. So now I remove all `""error""` warning filters and keep the rest. Note that the original filters get restored after `with warnings.catch_warnings():`. (). --- I am not sure I expressed myself very clearly... let me know and I can try again. @keewis you had a look at #4864 maybe you can review this PR as well? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6212/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1355581692,PR_kwDOAMm_X84-Cbgk,6967,fix _deprecate_positional_args helper,10194086,closed,0,,,0,2022-08-30T11:02:33Z,2022-09-02T21:54:07Z,2022-09-02T21:54:03Z,MEMBER,,0,pydata/xarray/pulls/6967," I tried to use the `_deprecate_positional_args` decorator from #6934 & it turns out that it still had some errors - passing on the arguments did not work properly in certain cases... I now added tests for this as well (which I should have done in the first place...). ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6967/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1355361572,PR_kwDOAMm_X84-Brev,6966,enable pydap in tests again,10194086,closed,0,,,1,2022-08-30T08:18:07Z,2022-09-01T10:16:05Z,2022-09-01T10:16:03Z,MEMBER,,0,pydata/xarray/pulls/6966," #5844 excluded pydap from our tests - but the new version has been released in the meantime (on conda not on pypi, though, pydap/pydap#268) - so let's see if this still works.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6966/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1355349486,PR_kwDOAMm_X84-Bo54,6965,no longer install pydap for 'io' extras in py3.10,10194086,closed,0,,,2,2022-08-30T08:08:12Z,2022-09-01T10:15:30Z,2022-09-01T10:15:27Z,MEMBER,,0,pydata/xarray/pulls/6965," - [x] Closes #6960 - [ ] Tests added - tested manually ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6965/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1331969418,PR_kwDOAMm_X8480cLZ,6890,tests don't use `pytest.warns(None)`,10194086,closed,0,,,0,2022-08-08T14:36:01Z,2022-08-30T12:15:33Z,2022-08-08T17:27:53Z,MEMBER,,0,pydata/xarray/pulls/6890," Get rid of some warnings in the tests. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6890/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1344900323,PR_kwDOAMm_X849fIGC,6937,terminology: fix italics [skip-ci],10194086,closed,0,,,0,2022-08-19T21:13:52Z,2022-08-20T07:30:41Z,2022-08-20T07:30:41Z,MEMBER,,0,pydata/xarray/pulls/6937,"- [x] Closes #6932 @zmoon - obviously it would be nice if we had a linter for this but this is for another time. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6937/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1337166287,PR_kwDOAMm_X849FuuD,6910,decorator to deprecate positional arguments,10194086,closed,0,,,7,2022-08-12T12:48:47Z,2022-08-18T18:14:09Z,2022-08-18T15:59:52Z,MEMBER,,0,pydata/xarray/pulls/6910," - [x] Supersedes #6403, see also #5531 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Adds a helper function to deprecate positional arguments. IMHO this offers a good trade-off between magic and complexity. (As mentioned this was adapted from scikit-learn). edit: I suggest to actually deprecate positional arguments in another PR. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6910/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1155634014,PR_kwDOAMm_X84zvnTl,6316,fix typos (using codespell),10194086,closed,0,,,2,2022-03-01T17:52:24Z,2022-07-18T13:33:02Z,2022-03-02T13:57:29Z,MEMBER,,0,pydata/xarray/pulls/6316," fix some typos (using [codespell](https://github.com/codespell-project/codespell)). Called using: ```bash codespell --skip="".git,.mypy_cache,*.tex"" --ignore-words-list coo,nd,inferrable,hist,ND,splitted,soler,slowy,ba,ser,nin,te,fo -w -i 3 ```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6316/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1094725752,I_kwDOAMm_X85BQDB4,6142,dimensions: type as `str | Iterable[Hashable]`?,10194086,open,0,,,14,2022-01-05T20:39:00Z,2022-06-26T11:57:40Z,,MEMBER,,,,"### What happened? We generally type dimensions as: ```python dims: Hashable | Iterable[Hashable] ``` However, this is in conflict with passing a tuple of independent dimensions to a method - e.g. `da.mean((""x"", ""y""))` because a tuple is also hashable. Also mypy requires an `isinstance(dims, Hashable)` check when typing a function. We use an `isinstance(dims, str)` check in many places to wrap a single dimension in a list. Changing this to `isinstance(dims, Hashable)` will change the behavior for tuples. ### What did you expect to happen? In the community call today we discussed to change this to ```python dims: str | Iterable[Hashable] ``` i.e. if a single dim is passed it has to be a string and wrapping it in a list is a convenience function. Special use cases with `Hashable` types should be wrapped in a `Iterable` by the user. This probably best reflects the current state of the repo (`dims = [dims] if isinstance(dims, str) else dims`). The disadvantage could be that it is a bit more difficult to explain in the docstrings? @shoyer - did I get this right from the discussion? --- Other options 1. Require `str` as dimension names. This could be too restrictive. @keewis mentioned that tuple dimension names are already used somwehere in the xarray repo. Also we discussed in another issue or PR (which I cannot find right know) that we want to keep allowing `Hashable`. 2. Disallow passing tuples (only allow tuples if a dimension is a tuple), require lists to pass several dimensions. This is too restrictive in the other direction and will probably lead to a lot of downstream troubles. Naming a single dimension with a tuple will be a very rare case, in contrast to passing several dimension names as a tuple. 3. Special case tuples. We could potentially check if `dims` is a tuple and if there are any dimension names consisting of a tuple. Seems more complicated and potentially brittle for probably small gains (IMO). ### Minimal Complete Verifiable Example _No response_ ### Relevant log output _No response_ ### Anything else we need to know? * We need to check carefully where general `Hashable` are really allowed. E.g. `dims` of a `DataArray` are typed as https://github.com/pydata/xarray/blob/e056cacdca55cc9d9118c830ca622ea965ebcdef/xarray/core/dataarray.py#L380 but tuples are not actually allowed: ```python import xarray as xr xr.DataArray([1], dims=(""x"", ""y"")) # ValueError: different number of dimensions on data and dims: 1 vs 2 xr.DataArray([1], dims=[(""x"", ""y"")]) # TypeError: dimension ('x', 'y') is not a string ``` * We need to be careful typing functions where only one dim is allowed, e.g. `xr.concat`, which should probably set `dim: Hashable` (and make sure it works). * Do you have examples for other real-world hashable types except for `str` and `tuple`? (Would be good for testing purposes). ### Environment N/A","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6142/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 685739084,MDU6SXNzdWU2ODU3MzkwODQ=,4375,allow using non-dimension coordinates in polyfit,10194086,open,0,,,1,2020-08-25T19:40:55Z,2022-04-09T02:58:48Z,,MEMBER,,,," `polyfit` currently only allows to fit along a dimension and not along a non-dimension coordinate (or a virtual coordinate) Example: ```python da = xr.DataArray( [1, 3, 2], dims=[""x""], coords=dict(x=[""a"", ""b"", ""c""], y=(""x"", [0, 1, 2])) ) print(da) da.polyfit(""y"", 1) ``` Output: ```python array([1, 3, 2]) Coordinates: * x (x) in 5 print(da) 6 ----> 7 da.polyfit(""y"", 1) ~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/dataarray.py in polyfit(self, dim, deg, skipna, rcond, w, full, cov) 3507 """""" 3508 return self._to_temp_dataset().polyfit( -> 3509 dim, deg, skipna=skipna, rcond=rcond, w=w, full=full, cov=cov 3510 ) 3511 ~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/dataset.py in polyfit(self, dim, deg, skipna, rcond, w, full, cov) 6005 skipna_da = skipna 6006 -> 6007 x = get_clean_interp_index(self, dim, strict=False) 6008 xname = ""{}_"".format(self[dim].name) 6009 order = int(deg) + 1 ~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/missing.py in get_clean_interp_index(arr, dim, use_coordinate, strict) 246 247 if use_coordinate is True: --> 248 index = arr.get_index(dim) 249 250 else: # string ~/.conda/envs/ipcc_ar6/lib/python3.7/site-packages/xarray/core/common.py in get_index(self, key) 378 """""" 379 if key not in self.dims: --> 380 raise KeyError(key) 381 382 try: KeyError: 'y' ``` **Describe the solution you'd like** Would be nice if that worked. **Describe alternatives you've considered** One could just set the non-dimension coordinate as index, e.g.: `da = da.set_index(x=""y"")` **Additional context** Allowing this *may* be as easy as replacing https://github.com/pydata/xarray/blob/9c85dd5f792805bea319f01f08ee51b83bde0f3b/xarray/core/missing.py#L248 by ``` index = arr[dim] ``` but I might be missing something. Or probably a `use_coordinate` must be threaded through to `get_clean_interp_index` (although I am a bit confused by this argument). ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4375/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 144630996,MDU6SXNzdWUxNDQ2MzA5OTY=,810,correct DJF mean,10194086,closed,0,,,4,2016-03-30T15:36:42Z,2022-04-06T16:19:47Z,2016-05-04T12:56:30Z,MEMBER,,,,"This started as a question and I add it as reference. Maybe you have a comment. There are several ways to calculate time series of seasonal data (starting from monthly or daily data): ``` # load libraries import pandas as pd import matplotlib.pyplot import numpy as np import xarray as xr # Create Example Dataset time = pd.date_range('2000.01.01', '2010.12.31', freq='M') data = np.random.rand(*time.shape) ds = xr.DataArray(data, coords=dict(time=time)) # (1) using resample ds_res = ds.resample('Q-FEB', 'time') ds_res = ds_res.sel(time=ds_res['time.month'] == 2) ds_res = ds_res.groupby('time.year').mean('time') # (2) this is wrong ds_season = ds.where(ds['time.season'] == 'DJF').groupby('time.year').mean('time') # (3) using where and rolling # mask other months with nan ds_DJF = ds.where(ds['time.season'] == 'DJF') # rolling mean -> only Jan is not nan # however, we loose Jan/ Feb in the first year and Dec in the last ds_DJF = ds_DJF.rolling(min_periods=3, center=True, time=3).mean() # make annual mean ds_DJF = ds_DJF.groupby('time.year').mean('time') ds_res.plot(marker='*') ds_season.plot() ds_DJF.plot() plt.show() ``` (1) The first is to use resample with 'Q-FEB' as argument. This works fine. It does include Jan/ Feb in the first year, and Dec in the last year + 1. If this makes sense can be debated. One case where this does not work is when you have, say, two regions in your data set, for one you want to calculate DJF and for the other you want NovDecJan. (2) Using 'time.season' is wrong as it combines Jan, Feb and Dec from the same year. (3) The third uses `where` and `rolling` and you lose 'incomplete' seasons. If you replace `ds.where(ds['time.season'] == 'DJF')` with `ds.groupby('time.month').where(summer_months)`, where `summer_months` is a boolean array it works also for non-standard 'summers' (or seasons) across the globe. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/810/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 310833761,MDU6SXNzdWUzMTA4MzM3NjE=,2037,to_netcdf -> _fill_value without NaN,10194086,open,0,,,8,2018-04-03T13:20:19Z,2022-03-10T10:59:17Z,,MEMBER,,,,"#### Code Sample, a copy-pastable example if possible ```python # Your code here import xarray as xr import numpy as np x = np.arange(10.) da = xr.Dataset(data_vars=dict(data=('dim1', x)), coords=dict(dim1=('dim1', x))) da.to_netcdf('tst.nc') ``` #### Problem description Apologies if this was discussed somwhere and it probably does not matter much, but `tst.nc` has `_FillValue` although it is not really necessary. #### Output of ``xr.show_versions()``
    # Paste the output here xr.show_versions() here
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2037/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1150224882,PR_kwDOAMm_X84zdCrl,6303,quantile: use skipna=None,10194086,closed,0,,,0,2022-02-25T09:24:05Z,2022-03-03T09:43:38Z,2022-03-03T09:43:35Z,MEMBER,,0,pydata/xarray/pulls/6303," - [x] Tests added - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` `skipna=None` did not skip missing values for `quantile`, inconsistent with other methods. Discovered while testing #6059.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6303/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1149708477,PR_kwDOAMm_X84zbVnG,6302,from_dict: doctest,10194086,closed,0,,,0,2022-02-24T20:17:24Z,2022-02-28T09:11:05Z,2022-02-28T09:11:02Z,MEMBER,,0,pydata/xarray/pulls/6302," - [x] Closes #6136 Convert the code block in `xr.DataArray.from_dict` and `xr.Dataset.from_dict` to doctest/ examples.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6302/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1150251120,I_kwDOAMm_X85Ej3Bw,6304,add join argument to xr.broadcast?,10194086,open,0,,,1,2022-02-25T09:52:14Z,2022-02-25T21:50:16Z,,MEMBER,,,,"### Is your feature request related to a problem? `xr.broadcast` always does an outer join: https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L702 https://github.com/pydata/xarray/blob/de965f342e1c9c5de92ab135fbc4062e21e72453/xarray/core/alignment.py#L768 This is not how the (default) broadcasting (arithmetic join) works, e.g. the following first does an inner join and then broadcasts: ```python import xarray as xr da1 = xr.DataArray([[0, 1, 2]], dims=(""y"", ""x""), coords={""x"": [0, 1, 2]}) da2 = xr.DataArray([0, 1, 2, 3, 4], dims=""x"", coords={""x"": [0, 1, 2, 3, 4]}) da1 + da2 ``` ``` array([[0, 2, 4]]) Coordinates: * x (x) int64 0 1 2 Dimensions without coordinates: y ``` ### Describe the solution you'd like Add a `join` argument to `xr.broadcast`. I would propose to leave the default as is ```python def broadcast(*args, exclude=None, join=""outer""): args = align(*args, join=join, copy=False, exclude=exclude) ``` ### Describe alternatives you've considered - We could make `broadcast` respect `options -> arithmetic_join` but that would be a breaking change and I am not sure how the deprecation should/ would be handled... - We could leave it as is. ### Additional context - `xr.broadcast` should not be used often because this is should happen automatically in most cases - in #6059 I use `broadcast` because I couldn't get it to work otherwise (maybe there is a better way?). However, the ""outer elements"" are immediately discarded again - so it's kind of pointless to do an outer join. ```python import numpy as np import xarray as xr da = xr.DataArray(np.arange(6).reshape(3, 2), coords={""dim_0"": [0, 1, 2]}) w = xr.DataArray([1, 1, 1, 1, 1, 1], coords={""dim_0"": [0, 1, 2, 4, 5, 6]}) da.weighted(w).quantile(0.5) ```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6304/reactions"", ""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1126086052,PR_kwDOAMm_X84yLQ48,6251,use `warnings.catch_warnings(record=True)` instead of `pytest.warns(None)`,10194086,closed,0,,,4,2022-02-07T14:42:26Z,2022-02-18T16:51:58Z,2022-02-18T16:51:55Z,MEMBER,,0,pydata/xarray/pulls/6251," pytest v7.0.0 no longer want's us to use ` pytest.warns(None)` to test for no warning, so we can use `warnings.catch_warnings(record=True)` instead. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6251/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1088615118,PR_kwDOAMm_X84wRifr,6108,quantile: rename interpolation arg to method,10194086,closed,0,,,3,2021-12-25T15:06:44Z,2022-02-08T17:09:47Z,2022-02-07T09:40:05Z,MEMBER,,0,pydata/xarray/pulls/6108," numpy/numpy#20327 introduces some changes to `np.quantile` (and related) for the upcoming numpy release (v1.22.0). It renames the `interpolation` keyword to `method` and offers some new interpolation methods. This PR does two things 1. it restores compatibility with numpy 1.22 2. it renames the `interpolation` keyword to `method` in xarray - this change is not strictly necessary but I thought better to be consistent with numpy - [x] Tests added - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` (Side note in `dask.array.percentile` the `method` keyword is used differently from the `interpolation` keyword ([docs](https://docs.dask.org/en/stable/generated/dask.array.percentile.html#dask.array.percentile)). However, xarray does not use the dask function.) --- TODO: need to import `ArrayLike` from npcompat. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6108/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1125661464,PR_kwDOAMm_X84yJ3Rz,6248,test bottleneck master in upstream CI [test-upstream] [skip-ci],10194086,closed,0,,,1,2022-02-07T08:25:35Z,2022-02-07T09:05:28Z,2022-02-07T09:05:24Z,MEMBER,,0,pydata/xarray/pulls/6248," - [x] Closes #6186 pydata/bottleneck#378 was merged - so this should work again.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6248/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1111644832,I_kwDOAMm_X85CQlqg,6186,upstream dev CI: enable bottleneck again,10194086,closed,0,,,2,2022-01-22T18:11:25Z,2022-02-07T09:05:24Z,2022-02-07T09:05:24Z,MEMBER,,,,bottleneck cannot be built with python 3.10. See https://github.com/pydata/xarray/actions/runs/1731371015,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6186/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1118836906,PR_kwDOAMm_X84xzojx,6213,fix or suppress test warnings,10194086,closed,0,,,1,2022-01-31T01:34:20Z,2022-02-01T09:40:15Z,2022-02-01T09:40:11Z,MEMBER,,0,pydata/xarray/pulls/6213,"Fixes or suppresses a number of warnings that turn up in our upstream CI. `pd.Index.is_monotonic` is an alias for `pd.Index.is_monotonic_increasing` and does _not_ stand for `pd.Index.is_monotonic_increasing or pd.Index.is_monotonic_decreasing`. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6213/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1118168483,PR_kwDOAMm_X84xxms4,6208,"Revert ""MNT: prepare h5netcdf backend for (coming) change in dimension handling""",10194086,closed,0,,,8,2022-01-29T10:27:11Z,2022-01-29T13:48:17Z,2022-01-29T13:20:51Z,MEMBER,,0,pydata/xarray/pulls/6208,Reverts pydata/xarray#6200,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6208/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1114414215,PR_kwDOAMm_X84xlfet,6194,doc: fix pd datetime parsing warning [skip-ci],10194086,closed,0,,,0,2022-01-25T22:12:53Z,2022-01-28T08:37:18Z,2022-01-28T05:41:49Z,MEMBER,,0,pydata/xarray/pulls/6194," And another tiny one... The somewhat ambiguous date string triggers a warning in pandas which makes our doc build fail. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6194/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1115026697,PR_kwDOAMm_X84xneFL,6195,MAINT: pandas 1.4: no longer use get_loc with method,10194086,closed,0,,,5,2022-01-26T13:35:04Z,2022-01-27T22:11:04Z,2022-01-27T21:06:40Z,MEMBER,,0,pydata/xarray/pulls/6195," - [x] Closes #5721 - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` Fixed as per @shoyer & @spencerkclark suggestion from https://github.com/pydata/xarray/issues/5721#issuecomment-903095007 Now that pandas 1.4 is out it would be good to get this fixed (there are about 5000 warnings in our tests, mostly because of `interp`, though). Also leads to a warning in our docs which breaks them (although that can also be fixed with an `:okwarning:` directive). ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6195/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 975385095,MDU6SXNzdWU5NzUzODUwOTU=,5721,pandas deprecates Index.get_loc with method,10194086,closed,0,,,7,2021-08-20T08:24:16Z,2022-01-27T21:06:40Z,2022-01-27T21:06:40Z,MEMBER,,,,"pandas deprecates the `method` keyword in `Index.get_loc`, see pandas-dev/pandas#42269. Therefore we end up with about 5000 warnings in our upstream tests: `FutureWarning: Passing method to Index.get_loc is deprecated and will raise in a future version. Use index.get_indexer([item], method=...) instead` We should fix this before pandas releases because the warning will not be silent (`FutureWarning`) or ask pandas to give us more time and use a `DeprecationWarning` at the moment.
    We use this here: https://github.com/pydata/xarray/blob/4bb9d9c6df77137f05e85c7cc6508fe7a93dc0e4/xarray/core/indexes.py#L233-L235 Is this only ever called with one item? Then we might be able to use ```python indexer = self.index.get_indexer( [label_value], method=method, tolerance=tolerance ).item() if indexer == -1: raise KeyError(label_value) ``` --- https://github.com/pydata/xarray/blob/3956b73a7792f41e4410349f2c40b9a9a80decd2/xarray/core/missing.py#L571-L572 This one could be easy to fix (replace with `imin = index.get_indexer([minval], method=""nearest"").item()`) --- It is also defined in `CFTimeIndex`, which complicates things: https://github.com/pydata/xarray/blob/eea76733770be03e78a0834803291659136bca31/xarray/coding/cftimeindex.py#L461-L466 because `get_indexer` expects an iterable and thus the `if isinstance(key, str)` test no longer works.
    @benbovy @spencerkclark ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5721/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1114392372,PR_kwDOAMm_X84xla15,6192,fix cftime doctests,10194086,closed,0,,,0,2022-01-25T21:43:55Z,2022-01-26T21:45:19Z,2022-01-26T21:45:17Z,MEMBER,,0,pydata/xarray/pulls/6192," Fixes the doctests for the newest version of cftime. @spencerkclark This of course means that the doctests will fail for environments with older versions of cftime present. I don't think there is anything we can do. Thanks for pytest-accept b.t.w @max-sixty ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6192/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1039272725,PR_kwDOAMm_X84t1ecc,5914, #5740 follow up: supress xr.ufunc warnings in tests,10194086,closed,0,,,2,2021-10-29T07:53:07Z,2022-01-26T08:41:41Z,2021-10-29T15:16:03Z,MEMBER,,0,pydata/xarray/pulls/5914," #5740 changed `PendingDeprecationWarning` to `FutureWarning` - suppress the warnings again in the test suite. https://github.com/pydata/xarray/blob/36f05d70c864ee7c61603c8a43ba721bf7f434b3/xarray/ufuncs.py#L47-L49 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5914/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1083281083,PR_kwDOAMm_X84wATnw,6082,cftime: 'gregorian' -> 'standard' [test-upstream],10194086,closed,0,,,3,2021-12-17T13:51:07Z,2022-01-26T08:41:33Z,2021-12-22T11:40:05Z,MEMBER,,0,pydata/xarray/pulls/6082," - [x] Closes #6016 cftime 1.5.2 renames ""gregorian"" to ""standard"". AFAIK this only changes the repr of cftime indices and does not seem to influence the creation of cftime indices.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6082/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1088419434,PR_kwDOAMm_X84wQ-nD,6107,is_dask_collection: micro optimization,10194086,closed,0,,,1,2021-12-24T15:04:42Z,2022-01-26T08:41:28Z,2021-12-29T16:27:55Z,MEMBER,,0,pydata/xarray/pulls/6107,"In #6096 I realized that `DuckArrayModule(""dask"")` is called a lot in our tests - 145'835 times. Most of those are from `is_dask_collection` (`is_duck_dask_array`) This change avoids that the instance needs to be built every time. ```python import xarray as xr %timeit xr.core.pycompat.DuckArrayModule(""dask"").available %timeit xr.core.pycompat.dsk.available ``` ``` 18.9 µs ± 97.7 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) 77.1 ns ± 1.22 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each) ``` Which leads to an incredible speed up of our tests of about 2.7 s :grin: ((18.9 - 0.0771) * 145835 / 1e6).","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6107/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 752870062,MDExOlB1bGxSZXF1ZXN0NTI5MDc4NDA0,4616,don't type check __getattr__,10194086,closed,0,,,4,2020-11-29T08:53:09Z,2022-01-26T08:41:18Z,2021-10-18T14:06:30Z,MEMBER,,1,pydata/xarray/pulls/4616," - [x] Closes #4601 - [x] Passes `isort . && black . && mypy . && flake8` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` It's not pretty as I had to define a number of empty methods... I think this should wait for 0.17","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4616/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 778069594,MDExOlB1bGxSZXF1ZXN0NTQ4MjI1MDQz,4760,WIP: testing.assert_* check dtype,10194086,closed,0,,,8,2021-01-04T12:45:00Z,2022-01-26T08:41:17Z,2021-10-18T14:06:38Z,MEMBER,,1,pydata/xarray/pulls/4760," - [x] Closes #4727 - [ ] Tests added - [ ] Passes `isort . && black . && mypy . && flake8` - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` --- This adds a dtype check for `equal`, `identical`, `broadcast_equal`, and the `xr.testing.assert_*` functions. It is far from complete: tests and documentation are still missing, but I wanted to get it online for feedback. When I set `check_dtype=True` there are around 600 failures. Fixing that is for another PR. #4759 should help a bit. - [ ] I added the checks to `lazy_array_equiv`, however, sometimes dask can get the dtype wrong before the compute (see below). Do you think I need to put it in the non-lazy part? ```python import numpy as np import xarray as xr da = xr.DataArray(np.array([0, np.nan], dtype=object)).chunk() da.prod().dtype # -> dtype('O') da.prod().compute().dtype # -> dtype('int64') ``` - [ ] `check_dtype` is still missing from `assert_duckarray_allclose` & `assert_duckarray_equal` - do you think there are required? - [ ] The dtypes of array elements are not tested (see below). I don't think I'll implement that here. ```python da0 = xr.DataArray(np.array([0], dtype=object)) da1 = xr.DataArray(np.array([0.], dtype=object)) xr.testting.assert_equal(da0, da1, check_dtype=True) ``` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4760/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1107431006,PR_kwDOAMm_X84xOsZX,6171,unpin dask again,10194086,closed,0,,,1,2022-01-18T22:37:31Z,2022-01-26T08:41:02Z,2022-01-18T23:39:12Z,MEMBER,,0,pydata/xarray/pulls/6171," - dask 2022.01 is out, so we can remove the pin","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6171/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1109572055,PR_kwDOAMm_X84xVqMq,6177,remove no longer necessary version checks,10194086,closed,0,,,2,2022-01-20T17:24:21Z,2022-01-26T08:40:55Z,2022-01-21T18:00:51Z,MEMBER,,0,pydata/xarray/pulls/6177," I hunted down some version checks that should no longer be necessary as we have moved beyond the minimum versions.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6177/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1114401347,PR_kwDOAMm_X84xlcvk,6193,don't install bottleneck wheel for upstream CI,10194086,closed,0,,,3,2022-01-25T21:55:49Z,2022-01-26T08:31:42Z,2022-01-26T08:31:39Z,MEMBER,,0,pydata/xarray/pulls/6193," - [x] see #6186 I think it would be good to re-enable the upstream CI, even if this means we have to stick to py3.9 for the moment. I just subscribed to pydata/bottleneck#378, so I should see when we can switch to 3.10.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6193/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1099288617,PR_kwDOAMm_X84wzh1F,6155,typing fixes for mypy 0.931 and numpy 1.22,10194086,closed,0,,,2,2022-01-11T15:19:43Z,2022-01-13T17:13:00Z,2022-01-13T17:12:57Z,MEMBER,,0,pydata/xarray/pulls/6155,typing fixes for mypy 0.931 and numpy 1.22. Also tested with numpy 1.20 which probably many still have installed.,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6155/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 432074821,MDU6SXNzdWU0MzIwNzQ4MjE=,2889,nansum vs nanmean for all-nan vectors,10194086,closed,0,,,3,2019-04-11T15:04:39Z,2022-01-05T21:59:48Z,2019-04-11T16:08:02Z,MEMBER,,,," ```python import xarray as xr import numpy as np ds = xr.DataArray([np.NaN, np.NaN]) ds.mean() ds.sum() ``` #### Problem description `ds.mean()` returns `NaN`, `ds.sum()` returns `0`. This comes from numpy (cp `np.nanmean` vs. `np.nansum`), so it might have to be discussed upstream, but I wanted to ask the xarray community first on their opinion. This is also relevant for #422 (what happens if the all weights are NaN or sum up to 0). #### Expected Output I would expect both to return `np.nan`. #### Output of ``xr.show_versions()``
    INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Mar 27 2019, 23:01:00) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.4.176-96-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_GB.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.12.1 pandas: 0.24.2 numpy: 1.16.2 scipy: 1.2.1 netCDF4: 1.5.0.1 pydap: None h5netcdf: 0.7.1 h5py: 2.9.0 Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: 1.2.0 PseudonetCDF: None rasterio: 1.0.22 cfgrib: None iris: None bottleneck: 1.2.1 dask: 1.1.5 distributed: 1.26.1 matplotlib: 3.0.3 cartopy: 0.17.0 seaborn: 0.9.0 setuptools: 41.0.0 pip: 19.0.3 conda: None pytest: 4.4.0 IPython: 7.4.0 sphinx: 2.0.1
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2889/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1078998718,PR_kwDOAMm_X84vyLHe,6077,disable pytest-xdist (to check CI failure),10194086,closed,0,,,3,2021-12-13T20:43:38Z,2022-01-03T08:30:02Z,2021-12-22T12:55:23Z,MEMBER,,0,pydata/xarray/pulls/6077," Our CI fails with some pytest-xdist error. Let's see if we get a clearer picture when disabling parallel tests. (Maybe some interaction between dask and pytest-xdist?). ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6077/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1090752550,PR_kwDOAMm_X84wYT5m,6127,"Revert ""disable pytest-xdist (to check CI failure)""",10194086,closed,0,,,2,2021-12-29T21:15:36Z,2022-01-03T08:29:52Z,2022-01-03T08:29:49Z,MEMBER,,0,pydata/xarray/pulls/6127,"- [x] Closes #6101 Reverts pydata/xarray#6077 (after dask has been pinned in #6111)","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6127/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1086797050,I_kwDOAMm_X85AxzT6,6101,enable pytest-xdist again (after dask release),10194086,closed,0,,,0,2021-12-22T12:57:03Z,2022-01-03T08:29:48Z,2022-01-03T08:29:48Z,MEMBER,,,,I disabled pytest-xdist because a dask issue renders our CI unusable. As soon as dask releases a new version we should revert #6077 again.,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6101/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1086360190,PR_kwDOAMm_X84wKRVp,6097,fix tests for h5netcdf v0.12,10194086,closed,0,,,6,2021-12-22T01:22:09Z,2021-12-23T20:29:33Z,2021-12-23T20:29:12Z,MEMBER,,0,pydata/xarray/pulls/6097," h5netcdf no longer warns for invalid netCDF (unless passing `save_kwargs = {""invalid_netcdf"": True}`. We need to adapt our tests. @kmuehlbauer --- edit: I added h5netcdf to the upstream tests - I can also revert this change if you prefer. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6097/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1036287825,PR_kwDOAMm_X84tryph,5899,[test-upstream] fix pd skipna=None,10194086,closed,0,,,2,2021-10-26T13:16:21Z,2021-10-28T11:54:49Z,2021-10-28T11:46:04Z,MEMBER,,0,pydata/xarray/pulls/5899," - [x] Closes #5872 - [x] Passes `pre-commit run --all-files` pandas will disallow `skipna=None` (pandas-dev/pandas#44178) - this fixes a test which relies on this. I don't think we have any user facing use of this. AFAIK we don't use pandas for reductions anywhere)","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5899/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1029142676,PR_kwDOAMm_X84tVCEd,5875,fix test with pseudonetcdf 3.2,10194086,closed,0,,,5,2021-10-18T13:49:23Z,2021-10-22T21:24:09Z,2021-10-22T21:23:34Z,MEMBER,,0,pydata/xarray/pulls/5875,"Fixes one part of #5872 pseudoNETCDF adds two attrs to ict files, which breaks the following two tests: Test 1: https://github.com/pydata/xarray/blob/07de257c5884df49335496ee6347fb633a7c302c/xarray/tests/test_backends.py#L3944 Test 2: https://github.com/pydata/xarray/blob/07de257c5884df49335496ee6347fb633a7c302c/xarray/tests/test_backends.py#L4030 I reproduced the test file so that the tests pass again. To reproduce the file I used the following bit of code: ```python import xarray as xr from xarray.tests import test_backends fN = ""xarray/tests/data/example.ict"" fmtkw = {""format"": ""ffi1001""} ds = xr.open_dataset(fN, engine=""pseudonetcdf"", backend_kwargs={""format"": ""ffi1001""}) c = test_backends.TestPseudoNetCDFFormat() c.save(ds, fN, **fmtkw) ``` The `save` method is here: https://github.com/pydata/xarray/blob/07de257c5884df49335496ee6347fb633a7c302c/xarray/tests/test_backends.py#L4124 @barronh I would appreciate your review here - I am not sure if this is the right approach. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5875/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 877166445,MDExOlB1bGxSZXF1ZXN0NjMxMTcwNzI4,5265,Warn ignored keep attrs,10194086,closed,0,,,1,2021-05-06T07:20:16Z,2021-10-18T14:06:37Z,2021-05-06T16:31:05Z,MEMBER,,0,pydata/xarray/pulls/5265," - [x] Part of #4513 - [x] Tests added - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` This PR warns when passing ` keep_attrs` to `resample(..., keep_attrs=True)` and `rolling_exp(..., keep_attrs=True)` as they have no effect (rightfully). Also removes `keep_attrs` from the docstring of `resample`.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5265/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 869763597,MDExOlB1bGxSZXF1ZXN0NjI1MDc0NjA5,5227,coarsen: better keep_attrs,10194086,closed,0,,,0,2021-04-28T09:56:45Z,2021-10-18T14:06:35Z,2021-04-29T17:40:57Z,MEMBER,,0,pydata/xarray/pulls/5227," - [x] Part of #4513 (maybe the last one - need to double check) - [x] Tests added - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` As per https://github.com/pydata/xarray/issues/3891#issuecomment-612522628 I also changed the default to `True`. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5227/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 758033677,MDExOlB1bGxSZXF1ZXN0NTMzMjc0NDY3,4656,unpin pip 20.2 again,10194086,closed,0,,,7,2020-12-06T22:00:12Z,2021-10-18T14:06:34Z,2021-04-18T21:42:25Z,MEMBER,,0,pydata/xarray/pulls/4656,Another enormous PR from my side ;) unpin pip again. numpy probably fixed the issue re the name of the nightly build. But I also need to doublecheck if scipy is ok.,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4656/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 802400938,MDExOlB1bGxSZXF1ZXN0NTY4NTUwNDEx,4865,fix da.pad example for numpy 1.20,10194086,closed,0,,,4,2021-02-05T19:00:04Z,2021-10-18T14:06:33Z,2021-02-07T21:57:34Z,MEMBER,,0,pydata/xarray/pulls/4865," - [x] Closes #4858 - [x] Passes `pre-commit run --all-files`","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4865/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 794344392,MDExOlB1bGxSZXF1ZXN0NTYxODc2OTg5,4845,iris update doc url,10194086,closed,0,,,1,2021-01-26T15:51:18Z,2021-10-18T14:06:31Z,2021-01-26T17:30:20Z,MEMBER,,0,pydata/xarray/pulls/4845," iris moved its documentation to https://scitools-iris.readthedocs.io/en/stable/","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4845/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 738958305,MDExOlB1bGxSZXF1ZXN0NTE3NzA0OTI2,4569,pin h5py to v2.10,10194086,closed,0,,,0,2020-11-09T11:46:39Z,2021-10-18T14:06:28Z,2020-11-09T12:52:27Z,MEMBER,,0,pydata/xarray/pulls/4569,"There is a compatibility issue with h5py v3. Pin h5py to version 2 for the moment. I can open an issue shortly. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4569/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 724975973,MDExOlB1bGxSZXF1ZXN0NTA2Mjc3OTk4,4525,unpin eccodes again,10194086,closed,0,,,2,2020-10-19T21:07:23Z,2021-10-18T14:06:27Z,2020-10-19T22:21:13Z,MEMBER,,0,pydata/xarray/pulls/4525," - [x] Closes #4521 - [x] Passes `isort . && black . && mypy . && flake8` That was fast - eccodes already fixed the issue.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4525/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 684430261,MDExOlB1bGxSZXF1ZXN0NDcyMzE4MzUw,4371,mention all ignored flake8 errors,10194086,closed,0,,,1,2020-08-24T07:17:03Z,2021-10-18T14:06:18Z,2020-08-24T10:45:05Z,MEMBER,,0,pydata/xarray/pulls/4371,"and put the comment on the same line ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4371/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 577830239,MDExOlB1bGxSZXF1ZXN0Mzg1NTIyOTEy,3849,update installation instruction,10194086,closed,0,,,6,2020-03-09T11:14:13Z,2021-10-18T14:06:16Z,2020-03-09T14:07:03Z,MEMBER,,0,pydata/xarray/pulls/3849," - [x] Closes #3756 - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3849/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 572269093,MDExOlB1bGxSZXF1ZXN0MzgxMDAyMTU2,3805,un-xfail tests that append to netCDF files with scipy,10194086,closed,0,,,3,2020-02-27T18:23:56Z,2021-10-18T14:06:14Z,2020-03-09T07:18:07Z,MEMBER,,0,pydata/xarray/pulls/3805," - [x] Closes #2019 - [ ] Tests added - [x] Passes `isort -rc . && black . && mypy . && flake8` - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API - [x] reverts #2021 Let's see if this passes....","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3805/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 539059754,MDExOlB1bGxSZXF1ZXN0MzU0MDk5Mzkz,3635,Fix/quantile wrong errmsg,10194086,closed,0,,,2,2019-12-17T13:16:40Z,2021-10-18T14:06:13Z,2019-12-17T13:50:06Z,MEMBER,,0,pydata/xarray/pulls/3635," - [x] Closes #3634 - [x] Tests added - [x] Passes `black . && mypy . && flake8` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API `np.nanquantile` was added in numpy 1.15.0, the current minimum requirement for numpy is 1.14.0, therefore we have to test this ourselves. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3635/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 928539812,MDExOlB1bGxSZXF1ZXN0Njc2NTI5NjQ4,5522,typing for numpy 1.21,10194086,closed,0,,,2,2021-06-23T18:40:28Z,2021-10-18T14:05:47Z,2021-06-24T08:58:07Z,MEMBER,,0,pydata/xarray/pulls/5522," - [x] Closes #5517 - [x] Passes `pre-commit run --all-files` The minimal typing for numpy 1.21. As always I am by no means a typing specialist. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5522/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 307783090,MDU6SXNzdWUzMDc3ODMwOTA=,2007,rolling: allow control over padding,10194086,open,0,,,20,2018-03-22T19:27:07Z,2021-07-14T19:10:47Z,,MEMBER,,,,"#### Code Sample, a copy-pastable example if possible ```python import numpy as np import xarray as xr x = np.arange(1, 366) y = np.random.randn(365) ds = xr.DataArray(y, dims=dict(dayofyear=x)) ds.rolling(center=True, dayofyear=31).mean() ``` #### Problem description `rolling` cannot directly handle periodic boundary conditions (lon, dayofyear, ...), but could be very helpful to e.g. calculate climate indices. Also I cannot really think of an easy way to append the first elements to the end of the dataset and then calculate rolling. Is there a way to do this? Should xarray support this feature? This might also belong to SO... ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2007/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 788534915,MDU6SXNzdWU3ODg1MzQ5MTU=,4824,combine_by_coords can succed when it shouldn't,10194086,open,0,,,15,2021-01-18T20:39:29Z,2021-07-08T17:44:38Z,,MEMBER,,,,"**What happened**: `combine_by_coords` can succeed when it should not - depending on the name of the dimensions (which determines the order of operations in `combine_by_coords`). **What you expected to happen**: * I think it should throw an error in both cases. **Minimal Complete Verifiable Example**: ```python import numpy as np import xarray as xr data = np.arange(5).reshape(1, 5) x = np.arange(5) x_name = ""lat"" da0 = xr.DataArray(data, dims=(""t"", x_name), coords={""t"": [1], x_name: x}).to_dataset(name=""a"") x = x + 1e-6 da1 = xr.DataArray(data, dims=(""t"", x_name), coords={""t"": [2], x_name: x}).to_dataset(name=""a"") ds = xr.combine_by_coords((da0, da1)) ds ``` returns: ```python Dimensions: (lat: 10, t: 2) Coordinates: * lat (lat) float64 0.0 1e-06 1.0 1.0 2.0 2.0 3.0 3.0 4.0 4.0 * t (t) int64 1 2 Data variables: a (t, lat) float64 0.0 nan 1.0 nan 2.0 nan ... 2.0 nan 3.0 nan 4.0 ``` Thus lat is interlaced - it don't think `combine_by_coords` should do this. If you set ```python x_name = ""lat"" ``` and run the example again, it returns: ```python-traceback ValueError: Resulting object does not have monotonic global indexes along dimension x ``` **Anything else we need to know?**: * this is vaguely related to #4077 but I think it is separate * `combine_by_coords` concatenates over all dimensions where the coords are different - therefore `compat=""override""` doesn't actually do anything? Or does it? https://github.com/pydata/xarray/blob/ba42c08af9afbd9e79d47bda404bf4a92a7314a0/xarray/core/combine.py#L69 cc @dcherian @TomNicholas **Environment**:
    Output of xr.show_versions()
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4824/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 773750763,MDU6SXNzdWU3NzM3NTA3NjM=,4727,xr.testing.assert_equal does not test for dtype,10194086,open,0,,,5,2020-12-23T13:14:41Z,2021-07-04T04:08:51Z,,MEMBER,,,,"In #4622 @toddrjen points out that `xr.testing.assert_equal` does not test for the `dtype`, only for the value. Therefore the following does not raise an error: ```python import numpy as np import xarray as xr import pandas as pd xr.testing.assert_equal( xr.DataArray(np.array(1, dtype=int)), xr.DataArray(np.array(1, dtype=float)) ) xr.testing.assert_equal( xr.DataArray(np.array(1, dtype=int)), xr.DataArray(np.array(1, dtype=object)) ) xr.testing.assert_equal( xr.DataArray(np.array(""a"", dtype=str)), xr.DataArray(np.array(""a"", dtype=object)) ) ``` This comes back to numpy, i.e. the following is True: ```python np.array(1, dtype=int) == np.array(1, dtype=float) ``` Depending on the situation one or the other is desirable or not. Thus, I would suggest to add a `check_dtype` argument to `xr.testing.assert_equal` and also to `DataArray.equals` (and `Dataset` and `Variable` and `identical`). I have not seen such an option in numpy, but pandas has it (e.g. `pd.testing.assert_series_equal(left, right, check_dtype=True, ...) `. I would _not_ change `__eq__`. * Thoughts? * What should the default be? We could try `True` first and see how many failures this creates? * What to do with coords and indexes? `pd.testing.assert_series_equal` has a `check_index_type` keyword. Probably we need `check_coords_type` as well? This makes the whole thing much more complicated... Also #4543 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4727/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 559217441,MDU6SXNzdWU1NTkyMTc0NDE=,3744,Contour with vmin/ vmax differs from matplotlib,10194086,open,0,,,0,2020-02-03T17:11:24Z,2021-07-04T02:03:02Z,,MEMBER,,,,"#### MCVE Code Sample ```python import numpy as np import xarray as xr import matplotlib as mpl import matplotlib.pyplot as plt data = xr.DataArray(np.arange(24).reshape(4, 6)) data.plot.contour(vmax=10, add_colorbar=True) ``` ![contour_xarray](https://user-images.githubusercontent.com/10194086/73672575-6d952980-46ad-11ea-8b3f-c78967c4776e.png) #### Expected Output ```python h = plt.contour(data.values, vmax=10) plt.colorbar(h) ``` ![contour_matplotlib](https://user-images.githubusercontent.com/10194086/73672722-adf4a780-46ad-11ea-8a44-4f5660ffe95c.png) #### Problem Description A `contour(vmax=vmax)` plot differs between xarray and matplotlib. I *think* the problem is here: https://github.com/pydata/xarray/blob/95e4f6c7a636878c94b892ee8d49866823d0748f/xarray/plot/utils.py#L265 xarray calculates the levels from `vmax` while matplotlib (probably) calculates the `levels` from `data.max()` and uses `vmax` only for the `norm`. For `contourf` and `pcolormesh` this is not so relevant as the capped values are then drawn with the `over` color. However, there may also be a good reason for this behavior. #### Output of ``xr.show_versions()``
    INSTALLED VERSIONS ------------------ commit: 4c96d53e6caa78d56b785f4edee49bbd4037a82f python: 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:33:48) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.12.14-lp151.28.36-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_GB.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.5 libnetcdf: 4.6.2 xarray: 999 (master) pandas: 0.25.3 numpy: 1.17.3 scipy: 1.4.1 netCDF4: 1.5.1.2 pydap: installed h5netcdf: 0.7.4 h5py: 2.10.0 Nio: 1.5.5 zarr: 2.4.0 cftime: 1.0.4.2 nc_time_axis: 1.2.0 PseudoNetCDF: installed rasterio: 1.1.0 cfgrib: 0.9.7.6 iris: 2.2.0 bottleneck: 1.3.1 dask: 2.9.2 distributed: 2.9.2 matplotlib: 3.1.2 cartopy: 0.17.0 seaborn: 0.9.0 numbagg: installed setuptools: 45.0.0.post20200113 pip: 19.3.1 conda: None pytest: 5.3.3 IPython: 7.11.1 sphinx: None
    ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3744/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 587048587,MDU6SXNzdWU1ODcwNDg1ODc=,3883,weighted operations: performance optimisations,10194086,open,0,,,3,2020-03-24T15:31:54Z,2021-07-04T02:01:28Z,,MEMBER,,,,"There was a discussion on the performance of the weighted mean/ sum in terms of memory footprint but also speed, and there may indeed be some things that can be optimized. See the [posts at the end of the PR](https://github.com/pydata/xarray/pull/2922#issuecomment-601496897). However, the optimal implementation will probably depend on the use case and some profiling will be required. I'll just open an issue to keep track of this. @seth-p ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3883/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 235542564,MDExOlB1bGxSZXF1ZXN0MTI1MzU1MTI5,1451,inconsistent time.units fmt in encode_cf_datetime,10194086,closed,0,,,7,2017-06-13T12:49:31Z,2021-06-24T08:45:18Z,2021-06-23T16:14:27Z,MEMBER,,0,pydata/xarray/pulls/1451,"- do not change user-specified units - always format infered units as 'YYYY-mmmm-ddTHH:MM:SS' This is my naïve approach. - [ ] Closes #1449 - [ ] Tests added / passed - [ ] Passes ``git diff upstream/master | flake8 --diff`` - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1451/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 913958248,MDExOlB1bGxSZXF1ZXN0NjYzOTE2NDQw,5451,Silence some test warnings,10194086,closed,0,,,1,2021-06-07T21:12:50Z,2021-06-09T17:55:48Z,2021-06-09T17:27:21Z,MEMBER,,0,pydata/xarray/pulls/5451," Silences a number of warnings that accumulated in our test suite (c.f. #3266). The changes are mostly unrelated but small. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5451/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 913916040,MDExOlB1bGxSZXF1ZXN0NjYzODgwMjI1,5450,plt.gca() no longer accepts kwargs,10194086,closed,0,,,0,2021-06-07T20:10:57Z,2021-06-09T17:27:02Z,2021-06-09T17:26:58Z,MEMBER,,0,pydata/xarray/pulls/5450,"matplotlib warns: `Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().` This only uses `plt.gca()` if there are active axes, else it calls `plt.axes(**kwargs)`. Note that this can silently ignore some arguments. However, that this is already the case. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5450/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull