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 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 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"""" 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 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 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 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 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 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 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 913830070,MDExOlB1bGxSZXF1ZXN0NjYzODA1MDQy,5449,fix dask meta and output_dtypes error,10194086,closed,0,,,8,2021-06-07T18:25:20Z,2021-06-08T07:51:50Z,2021-06-07T21:05:24Z,MEMBER,,0,pydata/xarray/pulls/5449," - [x] Closes #5444 This was changed in dask/dask#7669. Looks like they did not deprecate this behavior (i.e. passing both `meta` and `output_dtypes`). I'd suggest to follow dask's example here and not add a deprecation cycle. Thoughts? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5449/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 834641104,MDU6SXNzdWU4MzQ2NDExMDQ=,5053,ImportError: module 'xarray.backends.*' has no attribute '*_backend',10194086,closed,0,,,3,2021-03-18T10:44:33Z,2021-04-25T16:23:20Z,2021-04-25T16:23:19Z,MEMBER,,,,"**What happened**: I could not open the test dataset on master. It's a bit strange that this is not picked up by the tests, so probably something to do with the environment I have (I just updated all packages). @alexamici @aurghs does that tell you anything? I can also try to figure it out. **Minimal Complete Verifiable Example**: calling `open_dataset` with `""""` is enough to trigger the error: ```python import xarray as xr air = xr.open_dataset("""") ``` **Anything else we need to know?**: And the traceback:
    ```python-traceback --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) ~/conda/envs/xarray_dev/lib/python3.8/site-packages/pkg_resources/__init__.py in resolve(self) 2479 try: -> 2480 return functools.reduce(getattr, self.attrs, module) 2481 except AttributeError as exc: AttributeError: module 'xarray.backends.cfgrib_' has no attribute 'cfgrib_backend' The above exception was the direct cause of the following exception: ImportError Traceback (most recent call last) in ----> 1 air = xr.tutorial.open_dataset(""air_temperature"") ~/code/xarray/xarray/tutorial.py in open_dataset(name, cache, cache_dir, github_url, branch, **kws) 93 raise OSError(msg) 94 ---> 95 ds = _open_dataset(localfile, **kws) 96 97 if not cache: ~/code/xarray/xarray/backends/api.py in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs) 491 492 if engine is None: --> 493 engine = plugins.guess_engine(filename_or_obj) 494 495 backend = plugins.get_backend(engine) ~/code/xarray/xarray/backends/plugins.py in guess_engine(store_spec) 99 100 def guess_engine(store_spec): --> 101 engines = list_engines() 102 103 for engine, backend in engines.items(): ~/code/xarray/xarray/backends/plugins.py in list_engines() 95 def list_engines(): 96 pkg_entrypoints = pkg_resources.iter_entry_points(""xarray.backends"") ---> 97 return build_engines(pkg_entrypoints) 98 99 ~/code/xarray/xarray/backends/plugins.py in build_engines(pkg_entrypoints) 82 backend_entrypoints = BACKEND_ENTRYPOINTS.copy() 83 pkg_entrypoints = remove_duplicates(pkg_entrypoints) ---> 84 external_backend_entrypoints = backends_dict_from_pkg(pkg_entrypoints) 85 backend_entrypoints.update(external_backend_entrypoints) 86 backend_entrypoints = sort_backends(backend_entrypoints) ~/code/xarray/xarray/backends/plugins.py in backends_dict_from_pkg(pkg_entrypoints) 56 for pkg_ep in pkg_entrypoints: 57 name = pkg_ep.name ---> 58 backend = pkg_ep.load() 59 backend_entrypoints[name] = backend 60 return backend_entrypoints ~/conda/envs/xarray_dev/lib/python3.8/site-packages/pkg_resources/__init__.py in load(self, require, *args, **kwargs) 2470 if require: 2471 self.require(*args, **kwargs) -> 2472 return self.resolve() 2473 2474 def resolve(self): ~/conda/envs/xarray_dev/lib/python3.8/site-packages/pkg_resources/__init__.py in resolve(self) 2480 return functools.reduce(getattr, self.attrs, module) 2481 except AttributeError as exc: -> 2482 raise ImportError(str(exc)) from exc 2483 2484 def require(self, env=None, installer=None): ImportError: module 'xarray.backends.cfgrib_' has no attribute 'cfgrib_backend' ```
    **Environment**:
    Output of xr.show_versions() ``` INSTALLED VERSIONS ------------------ commit: a6f51c680f4e4c3ed5101b9c1111f0b94d28a781 python: 3.8.6 | packaged by conda-forge | (default, Jan 25 2021, 23:21:18) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.4.0-67-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.2.dev111+g0d93c4f9.d20201219 pandas: 1.2.3 numpy: 1.20.1 scipy: 1.6.1 netCDF4: 1.5.6 pydap: installed h5netcdf: 0.10.0 h5py: 3.1.0 Nio: None zarr: 2.6.1 cftime: 1.4.1 nc_time_axis: 1.2.0 PseudoNetCDF: installed rasterio: 1.2.1 cfgrib: 0.9.8.5 iris: 2.4.0 bottleneck: 1.3.2 dask: 2021.03.0 distributed: 2021.03.0 matplotlib: 3.3.4 cartopy: 0.18.0 seaborn: 0.11.1 numbagg: installed pint: 0.16.1 setuptools: 49.6.0.post20210108 pip: 21.0.1 conda: None pytest: 6.2.2 IPython: 7.21.0 sphinx: None ```
    and my conda list:
    ``` # packages in environment at /home/mathause/conda/envs/xarray_dev: # # Name Version Build Channel _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 1_gnu conda-forge affine 2.3.0 py_0 conda-forge antlr-python-runtime 4.7.2 py38h578d9bd_1002 conda-forge apipkg 1.5 py_0 conda-forge appdirs 1.4.4 pyh9f0ad1d_0 conda-forge asciitree 0.3.3 py_2 conda-forge attrs 20.3.0 pyhd3deb0d_0 conda-forge backcall 0.2.0 pyh9f0ad1d_0 conda-forge backports 1.0 py_2 conda-forge backports.functools_lru_cache 1.6.1 py_0 conda-forge beautifulsoup4 4.9.3 pyhb0f4dca_0 conda-forge black 20.8b1 py_1 conda-forge bokeh 2.3.0 py38h578d9bd_0 conda-forge boost-cpp 1.72.0 h9d3c048_4 conda-forge boto3 1.17.30 pyhd8ed1ab_0 conda-forge botocore 1.20.30 pyhd8ed1ab_0 conda-forge bottleneck 1.3.2 py38h5c078b8_3 conda-forge brotlipy 0.7.0 py38h497a2fe_1001 conda-forge bzip2 1.0.8 h7f98852_4 conda-forge c-ares 1.17.1 h7f98852_1 conda-forge ca-certificates 2020.12.5 ha878542_0 conda-forge cached-property 1.5.2 hd8ed1ab_1 conda-forge cached_property 1.5.2 pyha770c72_1 conda-forge cairo 1.16.0 h7979940_1007 conda-forge cartopy 0.18.0 py38hab71064_13 conda-forge cdat_info 8.2.1 pyh9f0ad1d_1 conda-forge cdms2 3.1.5 pypi_0 pypi cdtime 3.1.4 py38h49bcaf2_2 conda-forge certifi 2020.12.5 py38h578d9bd_1 conda-forge cf-units 2.1.4 py38hab2c0dc_2 conda-forge cffi 1.14.5 py38ha65f79e_0 conda-forge cfgrib 0.9.8.5 pyhd8ed1ab_0 conda-forge cfgv 3.2.0 py_0 conda-forge cfitsio 3.470 hb418390_7 conda-forge cftime 1.4.1 py38h5c078b8_0 conda-forge chardet 4.0.0 py38h578d9bd_1 conda-forge click 7.1.2 pyh9f0ad1d_0 conda-forge click-plugins 1.1.1 py_0 conda-forge cligj 0.7.1 pyhd8ed1ab_0 conda-forge cloudpickle 1.6.0 py_0 conda-forge coverage 5.5 py38h497a2fe_0 conda-forge coveralls 3.0.1 pyhd8ed1ab_0 conda-forge cryptography 3.4.6 py38ha5dfef3_0 conda-forge curl 7.75.0 h979ede3_0 conda-forge cycler 0.10.0 py_2 conda-forge cytoolz 0.11.0 py38h497a2fe_3 conda-forge dask 2021.3.0 pyhd8ed1ab_0 conda-forge dask-core 2021.3.0 pyhd8ed1ab_0 conda-forge dataclasses 0.8 pyhc8e2a94_1 conda-forge dbus 1.13.6 hfdff14a_1 conda-forge decorator 4.4.2 py_0 conda-forge distarray 2.12.2 py_1 conda-forge distlib 0.3.1 pyh9f0ad1d_0 conda-forge distributed 2021.3.0 py38h578d9bd_0 conda-forge docopt 0.6.2 py_1 conda-forge eccodes 2.20.0 ha0e6eb6_0 conda-forge editdistance 0.5.3 py38h709712a_3 conda-forge esmf 8.0.1 mpi_mpich_h3cbecb6_102 conda-forge esmpy 8.0.1 mpi_mpich_py38h6f0bf2d_102 conda-forge execnet 1.8.0 pyh44b312d_0 conda-forge expat 2.2.10 h9c3ff4c_0 conda-forge fasteners 0.14.1 py_3 conda-forge filelock 3.0.12 pyh9f0ad1d_0 conda-forge flake8 3.9.0 pyhd8ed1ab_0 conda-forge fontconfig 2.13.1 hba837de_1004 conda-forge freetype 2.10.4 h0708190_1 conda-forge freexl 1.0.6 h7f98852_0 conda-forge fsspec 0.8.7 pyhd8ed1ab_0 conda-forge future 0.18.2 py38h578d9bd_3 conda-forge g2clib 1.6.0 hf3f1b0b_9 conda-forge geos 3.9.1 h9c3ff4c_2 conda-forge geotiff 1.6.0 h11d48b3_4 conda-forge gettext 0.19.8.1 h0b5b191_1005 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0.18.0 py38h578d9bd_2 conda-forge jinja2 2.11.3 pyh44b312d_0 conda-forge jmespath 0.10.0 pyh9f0ad1d_0 conda-forge jpeg 9d h516909a_0 conda-forge json-c 0.15 h98cffda_0 conda-forge jsonschema 3.2.0 py38h32f6830_1 conda-forge jupyter_core 4.7.1 py38h578d9bd_0 conda-forge kealib 1.4.14 hcc255d8_2 conda-forge kiwisolver 1.3.1 py38h1fd1430_1 conda-forge krb5 1.17.2 h926e7f8_0 conda-forge lazy-object-proxy 1.5.2 py38h497a2fe_1 conda-forge lcms2 2.12 hddcbb42_0 conda-forge ld_impl_linux-64 2.35.1 hea4e1c9_2 conda-forge libaec 1.0.4 he1b5a44_1 conda-forge libblas 3.8.0 17_openblas conda-forge libcblas 3.8.0 17_openblas conda-forge libcdms 3.1.2 h981a4fd_113 conda-forge libcf 1.0.3 py38h88b7cc0_109 conda-forge libclang 11.1.0 default_ha53f305_0 conda-forge libcst 0.3.17 py38h578d9bd_0 conda-forge libcurl 7.75.0 hc4aaa36_0 conda-forge libdap4 3.20.6 hd7c4107_1 conda-forge libdrs 3.1.2 h7918d09_113 conda-forge libdrs_f 3.1.2 h5026c31_111 conda-forge libedit 3.1.20191231 he28a2e2_2 conda-forge libev 4.33 h516909a_1 conda-forge libevent 2.1.10 hcdb4288_3 conda-forge libffi 3.3 h58526e2_2 conda-forge libgcc-ng 9.3.0 h2828fa1_18 conda-forge libgdal 3.2.1 h38ff51b_7 conda-forge libgfortran-ng 9.3.0 hff62375_18 conda-forge libgfortran5 9.3.0 hff62375_18 conda-forge libglib 2.66.7 h3e27bee_1 conda-forge libgomp 9.3.0 h2828fa1_18 conda-forge libiconv 1.16 h516909a_0 conda-forge libkml 1.3.0 hd79254b_1012 conda-forge liblapack 3.8.0 17_openblas conda-forge libllvm10 10.0.1 he513fc3_3 conda-forge libllvm11 11.1.0 hf817b99_0 conda-forge libnetcdf 4.7.4 mpi_mpich_hdef422e_7 conda-forge libnghttp2 1.43.0 h812cca2_0 conda-forge libopenblas 0.3.10 pthreads_h4812303_5 conda-forge libpng 1.6.37 hed695b0_2 conda-forge libpq 13.1 hfd2b0eb_2 conda-forge librttopo 1.1.0 h1185371_6 conda-forge libspatialite 5.0.1 he52d314_3 conda-forge libssh2 1.9.0 ha56f1ee_6 conda-forge libstdcxx-ng 9.3.0 h6de172a_18 conda-forge libtiff 4.2.0 hdc55705_0 conda-forge libuuid 2.32.1 h14c3975_1000 conda-forge libwebp-base 1.2.0 h7f98852_2 conda-forge libxcb 1.13 h7f98852_1003 conda-forge libxkbcommon 1.0.3 he3ba5ed_0 conda-forge libxml2 2.9.10 h72842e0_3 conda-forge libxslt 1.1.33 h15afd5d_2 conda-forge line_profiler 3.1.0 py38h82cb98a_1 conda-forge llvmlite 0.36.0 py38h4630a5e_0 conda-forge locket 0.2.0 py_2 conda-forge lxml 4.6.2 py38hf1fe3a4_1 conda-forge lz4-c 1.9.3 h9c3ff4c_0 conda-forge markupsafe 1.1.1 py38h497a2fe_3 conda-forge matplotlib 3.3.4 py38h578d9bd_0 conda-forge matplotlib-base 3.3.4 py38h0efea84_0 conda-forge mccabe 0.6.1 py_1 conda-forge mechanicalsoup 1.0.0 pyhd8ed1ab_0 conda-forge monkeytype 20.5.0 pyh516909a_0 conda-forge monotonic 1.5 py_0 conda-forge more-itertools 8.7.0 pyhd8ed1ab_0 conda-forge mpi 1.0 mpich conda-forge mpi4py 3.0.3 py38he865349_5 conda-forge mpich 3.4.1 h846660c_104 conda-forge msgpack-python 1.0.2 py38h1fd1430_1 conda-forge mypy 0.812 pyhd8ed1ab_0 conda-forge mypy_extensions 0.4.3 py38h578d9bd_3 conda-forge mysql-common 8.0.23 ha770c72_1 conda-forge mysql-libs 8.0.23 h935591d_1 conda-forge nbformat 5.1.2 pyhd8ed1ab_1 conda-forge nc-time-axis 1.2.0 py_1 conda-forge ncurses 6.2 h58526e2_4 conda-forge netcdf-fortran 4.5.3 mpi_mpich_h7ad8bfe_1 conda-forge netcdf4 1.5.6 nompi_py38h1cdf482_100 conda-forge nodeenv 1.5.0 pyh9f0ad1d_0 conda-forge nspr 4.30 h9c3ff4c_0 conda-forge nss 3.62 hb5efdd6_0 conda-forge numba 0.53.0 py38h5e62926_1 conda-forge numbagg 0.1 pypi_0 pypi numcodecs 0.7.3 py38h709712a_0 conda-forge numpy 1.20.1 py38h18fd61f_0 conda-forge olefile 0.46 pyh9f0ad1d_1 conda-forge openblas 0.3.10 pthreads_h04b7a96_5 conda-forge openjpeg 2.4.0 hf7af979_0 conda-forge openssl 1.1.1j h7f98852_0 conda-forge packaging 20.9 pyh44b312d_0 conda-forge pandas 1.2.3 py38h51da96c_0 conda-forge parso 0.8.1 pyhd8ed1ab_0 conda-forge partd 1.1.0 py_0 conda-forge pathspec 0.8.1 pyhd3deb0d_0 conda-forge patsy 0.5.1 py_0 conda-forge pcre 8.44 he1b5a44_0 conda-forge pexpect 4.8.0 py38h32f6830_1 conda-forge pickleshare 0.7.5 py38h32f6830_1002 conda-forge pillow 8.1.2 py38ha0e1e83_0 conda-forge pint 0.16.1 py_0 conda-forge pip 21.0.1 pyhd8ed1ab_0 conda-forge pixman 0.40.0 h36c2ea0_0 conda-forge pluggy 0.13.1 py38h578d9bd_4 conda-forge poppler 0.89.0 h2de54a5_5 conda-forge poppler-data 0.4.10 0 conda-forge postgresql 13.1 h6303168_2 conda-forge pre-commit 2.11.1 py38h578d9bd_0 conda-forge proj 7.2.0 h277dcde_2 conda-forge prompt-toolkit 3.0.17 pyha770c72_0 conda-forge pseudonetcdf 3.1.0 py_1 conda-forge psutil 5.8.0 py38h497a2fe_1 conda-forge pthread-stubs 0.4 h36c2ea0_1001 conda-forge ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge py 1.10.0 pyhd3deb0d_0 conda-forge pycodestyle 2.7.0 pyhd8ed1ab_0 conda-forge pycparser 2.20 pyh9f0ad1d_2 conda-forge pydap 3.2.2 py38_1000 conda-forge pyflakes 2.3.0 pyhd8ed1ab_0 conda-forge pygments 2.8.1 pyhd8ed1ab_0 conda-forge pyke 1.1.1 py38h578d9bd_1003 conda-forge pyopenssl 20.0.1 pyhd8ed1ab_0 conda-forge pyparsing 2.4.7 pyh9f0ad1d_0 conda-forge pyqt 5.12.3 py38h578d9bd_7 conda-forge pyqt-impl 5.12.3 py38h7400c14_7 conda-forge pyqt5-sip 4.19.18 py38h709712a_7 conda-forge pyqtchart 5.12 py38h7400c14_7 conda-forge pyqtwebengine 5.12.1 py38h7400c14_7 conda-forge pyrsistent 0.17.3 py38h497a2fe_2 conda-forge pyshp 2.1.3 pyh44b312d_0 conda-forge pysocks 1.7.1 py38h578d9bd_3 conda-forge pytest 6.2.2 py38h578d9bd_0 conda-forge pytest-cov 2.11.1 pyh44b312d_0 conda-forge pytest-env 0.6.2 py_0 conda-forge pytest-forked 1.3.0 pyhd3deb0d_0 conda-forge pytest-profiling 1.7.0 py_1 conda-forge pytest-xdist 2.2.1 pyhd8ed1ab_0 conda-forge python 3.8.6 hffdb5ce_5_cpython conda-forge python-dateutil 2.8.1 py_0 conda-forge python-xxhash 2.0.0 py38h497a2fe_1 conda-forge python_abi 3.8 1_cp38 conda-forge pytz 2021.1 pyhd8ed1ab_0 conda-forge pyyaml 5.4.1 py38h497a2fe_0 conda-forge qt 5.12.9 hda022c4_4 conda-forge rasterio 1.2.1 py38h57accd2_2 conda-forge readline 8.0 he28a2e2_2 conda-forge regex 2020.11.13 py38h497a2fe_1 conda-forge regrid2 3.1.5 pypi_0 pypi requests 2.25.1 pyhd3deb0d_0 conda-forge s3transfer 0.3.4 pyhd8ed1ab_0 conda-forge scipy 1.6.1 py38hb2138dd_0 conda-forge seaborn 0.11.1 ha770c72_0 conda-forge seaborn-base 0.11.1 pyhd8ed1ab_1 conda-forge setuptools 49.6.0 py38h578d9bd_3 conda-forge shapely 1.7.1 py38h4fc1155_4 conda-forge six 1.15.0 pyh9f0ad1d_0 conda-forge snuggs 1.4.7 py_0 conda-forge sortedcontainers 2.3.0 pyhd8ed1ab_0 conda-forge soupsieve 2.0.1 py38h32f6830_0 conda-forge sparse 0.11.2 py_0 conda-forge sqlite 3.34.0 h74cdb3f_0 conda-forge statsmodels 0.12.2 py38h5c078b8_0 conda-forge tblib 1.6.0 py_0 conda-forge tiledb 2.2.5 h91fcb0e_0 conda-forge tk 8.6.10 hed695b0_1 conda-forge toml 0.10.2 pyhd8ed1ab_0 conda-forge toolz 0.11.1 py_0 conda-forge tornado 6.1 py38h497a2fe_1 conda-forge traitlets 5.0.5 py_0 conda-forge typed-ast 1.4.2 py38h497a2fe_0 conda-forge typing_extensions 3.7.4.3 py_0 conda-forge typing_inspect 0.6.0 pyh9f0ad1d_0 conda-forge tzcode 2021a h7f98852_1 conda-forge tzdata 2021a he74cb21_0 conda-forge udunits2 2.2.27.27 h360fe7b_0 conda-forge urllib3 1.26.4 pyhd8ed1ab_0 conda-forge virtualenv 20.4.3 py38h578d9bd_0 conda-forge wcwidth 0.2.5 pyh9f0ad1d_2 conda-forge webob 1.8.6 py_0 conda-forge wheel 0.36.2 pyhd3deb0d_0 conda-forge xarray 0.16.2.dev111+g0d93c4f9.d20201219 dev_0 xerces-c 3.2.3 h9d8b166_2 conda-forge xorg-kbproto 1.0.7 h14c3975_1002 conda-forge xorg-libice 1.0.10 h516909a_0 conda-forge xorg-libsm 1.2.3 hd9c2040_1000 conda-forge xorg-libx11 1.7.0 h36c2ea0_0 conda-forge xorg-libxau 1.0.9 h14c3975_0 conda-forge xorg-libxdmcp 1.1.3 h516909a_0 conda-forge xorg-libxext 1.3.4 h7f98852_1 conda-forge xorg-libxrender 0.9.10 h7f98852_1003 conda-forge xorg-renderproto 0.11.1 h14c3975_1002 conda-forge xorg-xextproto 7.3.0 h14c3975_1002 conda-forge xorg-xproto 7.0.31 h14c3975_1007 conda-forge xxhash 0.8.0 h7f98852_3 conda-forge xz 5.2.5 h516909a_1 conda-forge yaml 0.2.5 h516909a_0 conda-forge zarr 2.6.1 pyhd8ed1ab_0 conda-forge zict 2.0.0 py_0 conda-forge zipp 3.4.1 pyhd8ed1ab_0 conda-forge zlib 1.2.11 h516909a_1010 conda-forge zstd 1.4.9 ha95c52a_0 conda-forge ```
    --- edit: added the traceback","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5053/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 771482993,MDExOlB1bGxSZXF1ZXN0NTQyOTk3MjQx,4716,.coveragerc omit: wildcards,10194086,closed,0,,,2,2020-12-20T00:26:59Z,2021-04-19T20:34:07Z,2020-12-20T00:48:43Z,MEMBER,,0,pydata/xarray/pulls/4716," - [x] Closes #4693 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4716/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 845248555,MDExOlB1bGxSZXF1ZXN0NjA0NDI2MTYx,5096,type: ignore - use error codes,10194086,closed,0,,,2,2021-03-30T20:53:50Z,2021-04-01T10:23:56Z,2021-04-01T10:23:53Z,MEMBER,,0,pydata/xarray/pulls/5096," - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` Adds error codes to all `# type: ignore` comments. mypy should raise if a different type of error is encountered. Also enable showing the error code for typing errors. See: [mypy: displaying-error-codes](https://mypy.readthedocs.io/en/stable/error_codes.html#displaying-error-codes). Also remove some `# type: ignore` that are no longer necessary.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5096/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 843217462,MDExOlB1bGxSZXF1ZXN0NjAyNjMyMjgw,5090,ensure combine_by_coords raises on different types,10194086,closed,0,,,3,2021-03-29T10:13:34Z,2021-03-31T15:53:23Z,2021-03-31T13:36:44Z,MEMBER,,0,pydata/xarray/pulls/5090," - [x] Part of #5077 - [x] Tests added - [x] Passes `pre-commit run --all-files` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5090/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 308039063,MDExOlB1bGxSZXF1ZXN0MTc3MDc3MTU5,2011,rolling: periodic,10194086,closed,0,,,9,2018-03-23T13:57:25Z,2021-03-30T15:08:22Z,2021-03-30T15:08:18Z,MEMBER,,0,pydata/xarray/pulls/2011," - [x] Closes #2007 - [ ] Tests added (for all bug fixes or enhancements) - [ ] Tests passed (for all non-documentation changes) - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API --- Ok, this was easier to do than initially thought, we can use `np.pad(a, pads, mode='wrap')` in `nputils.rolling_window`. However, I'm not sure if that is enough already*. I added an initial test, but could use some pointers where else you want this to be tested. Questions: * is `fill_value='periodic'` a good api? * should the `fill_value` keyvalue be ported to `rolling`? * should this also be mentioned in the docs for `rolling` (I only learned about `rolling.construct` yesterday) --- *`rolling` is present in`core/dataset.py`, `core/dataarray.py`, `core/variable.py`, `core/rolling.py`, `core/dask_array_ops.py`, `core/nputils.py`, `core/ops.py`, `core/common.py`, `core/missing.py`, and `core/duck_array_ops.py` that can be a bit daunting... ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2011/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 819884612,MDExOlB1bGxSZXF1ZXN0NTgyOTE5ODUy,4982,pin netCDF4=1.5.3 in min-all-deps,10194086,closed,0,,,1,2021-03-02T10:36:18Z,2021-03-08T09:10:20Z,2021-03-08T00:20:38Z,MEMBER,,0,pydata/xarray/pulls/4982," - [x] Closes #4970 The clean thing here would be to update `min_deps_check.py` so it works properly for this case. I am not sure it's really worth it.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4982/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 817951965,MDU6SXNzdWU4MTc5NTE5NjU=,4970,minimum version and non-semantic versioning (netCDF4),10194086,closed,0,,,1,2021-02-27T15:33:48Z,2021-03-08T00:20:38Z,2021-03-08T00:20:38Z,MEMBER,,,,"We currently pin netCDF4 to [version 1.5](https://github.com/pydata/xarray/blob/48378c4b11c5c2672ff91396d4284743165b4fbe/ci/requirements/py37-min-all-deps.yml#L28). However, I think netCDF4 does not really follow semantic versioning, e.g. python 2 support was dropped in version 1.5.6. So they may actually be doing something like `1.major.minor[.patch]` - I asked about their versioning scheme in Unidata/netcdf4-python#1090. So I wonder if we would need to pin netCDF to version to version 1.5.4.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4970/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 814813503,MDExOlB1bGxSZXF1ZXN0NTc4NzQwMzM2,4946,Upstream CI: limit runtime,10194086,closed,0,,,5,2021-02-23T20:40:34Z,2021-02-24T14:37:04Z,2021-02-23T22:37:07Z,MEMBER,,0,pydata/xarray/pulls/4946," - xref #4945 Try to limit the time of ""CI Upstream"" to avoid a silent failure.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4946/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 814806676,MDU6SXNzdWU4MTQ4MDY2NzY=,4945,Upstream CI failing silently,10194086,closed,0,,,1,2021-02-23T20:30:29Z,2021-02-24T08:14:00Z,2021-02-24T08:14:00Z,MEMBER,,,,"The last 5 days our Upstream CI failed silently with a timeout after 6h: https://github.com/pydata/xarray/actions/workflows/upstream-dev-ci.yaml?query=branch%3Amaster+event%3Aschedule This was probably caused by #4934. As mentioned in dask/dask#4934 this is probably dask/dask#6738 which was merged 5 days ago.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4945/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 803049855,MDExOlB1bGxSZXF1ZXN0NTY5MDQ0NzMy,4878,typing for numpy 1.20,10194086,closed,0,,,2,2021-02-07T20:32:27Z,2021-02-23T20:52:50Z,2021-02-23T20:52:47Z,MEMBER,,0,pydata/xarray/pulls/4878,"numpy v1.20.0 introduced type hints which leads to some mypy errors in xarray. This is the minimum set of changes to make mypy happy again. I tried to avoid `#type: ignore` and `Any` but in some instances I think it was not worth it. I am sure there is much more fun to be had with numpy typing ;-) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4878/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 812214755,MDExOlB1bGxSZXF1ZXN0NTc2NjE2MzM1,4929,CI: run mypy in full env,10194086,closed,0,,,3,2021-02-19T17:47:28Z,2021-02-22T16:42:09Z,2021-02-22T16:33:51Z,MEMBER,,0,pydata/xarray/pulls/4929," - [x] Closes #4881 - [x] Tests added - [x] Passes `pre-commit run --all-files` - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` I only added one run for py3.8 latest. To be entirely sure we could also check the typing `py37-min-all-deps` but it feels like overkill... --- Ok, looks good - the failure is expected - see #4878. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4929/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 803402841,MDU6SXNzdWU4MDM0MDI4NDE=,4881,check mypy at the end of some CI runs?,10194086,closed,0,,,2,2021-02-08T10:04:44Z,2021-02-22T16:33:50Z,2021-02-22T16:33:50Z,MEMBER,,,,"We currently run mypy in the `pre-commit hooks` CI. However, this is done in an environment where no dependencies are installed. Therefore we missed the errors that pop up when running mypy with numpy 1.20 installed. (Please correct my if I misunderstood this). Should we add a new step to our CI and run mypy? I think we should at least add this to `ubuntu-latest py3.8`. For more complete checks we could also go for ` ubuntu-latest py37-min-all-deps` and `upstream-dev`.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4881/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 811379942,MDExOlB1bGxSZXF1ZXN0NTc1OTE3NjYz,4923,[skip-ci] doc: fix pynio warning,10194086,closed,0,,,1,2021-02-18T19:09:00Z,2021-02-18T19:23:23Z,2021-02-18T19:23:20Z,MEMBER,,0,pydata/xarray/pulls/4923," Small doc fix, see http://xarray.pydata.org/en/stable/io.html#formats-supported-by-pynio (the `..note::` did not get picked up) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4923/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 739008382,MDU6SXNzdWU3MzkwMDgzODI=,4570,fix compatibility with h5py version 3 and unpin tests,10194086,closed,0,,,6,2020-11-09T13:00:01Z,2021-02-17T08:41:20Z,2021-02-17T08:41:20Z,MEMBER,,,,"h5py version 3.1 broke our tests. I pinned it to version 2.10 in #4569. We should therefore * fix the issues * unpin h5py again The failures could be related to a change how strings are read: https://docs.h5py.org/en/latest/strings.html I am not sure if this has to be fixed in xarray or in h5necdf. I'd be happy if someone else took this one. Failed tests:
    ``` FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_zero_dimensional_variable FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_write_store - As... FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_roundtrip_test_data FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_load - Assertion... FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_dataset_compute FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_roundtrip_object_dtype FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_roundtrip_string_data FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_orthogonal_indexing FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_vectorized_indexing FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_isel_dataarray FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_array_type_after_indexing FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_append_write - A... FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_append_overwrite_values FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_write_groups - A... FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_encoding_kwarg_vlen_string FAILED xarray/tests/test_backends.py::TestH5NetCDFData::test_compression_encoding FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_zero_dimensional_variable FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_write_store FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_roundtrip_test_data FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_load - Ass... FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_dataset_compute FAILED xarray/tests/test_backends.py::TestH5NetCDFFileObject::test_roundtrip_object_dtype FAILED xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_encoding_kwarg_vlen_string FAILED xarray/tests/test_backends.py::TestH5NetCDFViaDaskData::test_compression_encoding FAILED xarray/tests/test_distributed.py::test_dask_distributed_netcdf_roundtrip[h5netcdf-NETCDF4] FAILED xarray/tests/test_distributed.py::test_dask_distributed_read_netcdf_integration_test[h5netcdf-NETCDF4] ```
    **Example failure:** ```python traceback > assert_allclose(original, computed) E AssertionError: Left and right Dataset objects are not close E E Differing coordinates: E L * dim3 (dim3)