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 1474717029,PR_kwDOAMm_X85EPeqM,7353,Add python 3.11 to CI,14371165,closed,0,,,9,2022-12-04T11:12:01Z,2024-03-13T21:43:10Z,2023-05-28T09:58:40Z,MEMBER,,1,pydata/xarray/pulls/7353,"Waiting on: - https://github.com/numba/numba/issues/8304 - https://github.com/numba/numba/issues/8841 - https://github.com/zarr-developers/numcodecs/issues/377 - https://github.com/Unidata/netcdf4-python/issues/1204 - https://github.com/h5py/h5py/issues/2146 - [ ] Closes #7316 - [ ] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` Feel free to push to this PR if you want.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7353/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1761952309,PR_kwDOAMm_X85TQlL1,7925,Remove hue_style from plot1d docstring,14371165,closed,0,,,9,2023-06-17T18:33:11Z,2024-03-13T21:40:43Z,2023-07-13T23:17:48Z,MEMBER,,0,pydata/xarray/pulls/7925," - [x] Closes #7907 - [x] Closes #7908 - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7925/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1936840711,PR_kwDOAMm_X85cdvXs,8294,Use shape and dtype as typevars in NamedArray,14371165,closed,0,,,9,2023-10-11T05:08:32Z,2023-12-12T20:41:29Z,2023-10-18T06:22:52Z,MEMBER,,0,pydata/xarray/pulls/8294,"Using a different TypeVar strategy compared to #8281. The idea here is to typevar shape and dtype instead, just like numpy does. Previously I tried to use the _data array as the TypeVar but that causes all kinds of issues since TypeVar is usually invariant and can't be updated to a new type. Since the dtype changes very frequently when doing array operations it quickly gets difficult to pass along the correct typing. * This PR adds a from_array function. The intention is to use that function to create NamedArrays when you are passing around ArrayLikes. The init for NamedArray will now just assume the input data is correct. At runtime at least, mypy will catch any non-supported array types. There's some precedent to this: * numpy.array_api.Array forces to use xp.asarray. * [Cubed](https://github.com/tomwhite/cubed/blob/main/cubed/array_api/array_object.py) assumes the inputs are correct. Has a xp.asarray and a from_array function. * The ugly `fastpath` argument is therefore not needed. * Adds a bunch of type hint classes, `duckarray[ShapeType, DType]` (corresponding to `np.ndarray`) or `DuckArray[ScalarType]` (corresponding to `np.typing.NDArray`) are the recommended ones. * It's better to use these kinds of classes over creating `is_duck_array` functions with typeguards because `isinstance` also works on the `else` clause. * This PR adds some array_api functions, the idea here is that NamedArray could also be array_api compliant. - [x] Tests added - [x] Closes #8291 References: https://github.com/tomwhite/cubed/blob/ea885193dd37d27917a24878b51bb086aaef5fb1/cubed/core/ops.py#L34 https://stackoverflow.com/questions/74633074/how-to-type-hint-a-generic-numpy-array https://numpy.org/doc/stable/reference/arrays.scalars.html#scalars https://github.com/numpy/numpy/blob/040ed2dc9847265c581a342301dd87d2b518a3c2/numpy/__init__.pyi#L1423 https://github.com/numpy/numpy/blob/040ed2dc9847265c581a342301dd87d2b518a3c2/numpy/_typing/_array_like.py#L32 https://stackoverflow.com/questions/69186176/determine-if-subclass-has-a-base-classs-method-implemented-in-python","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8294/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1020353782,PR_kwDOAMm_X84s6KU4,5844,Add python 3.10 to CI,14371165,closed,0,,,9,2021-10-07T18:49:43Z,2022-08-12T09:05:25Z,2022-01-21T17:06:43Z,MEMBER,,0,pydata/xarray/pulls/5844," Waiting on * https://github.com/ContinuumIO/anaconda-issues/issues/12669 * https://github.com/conda/conda/pull/10970 * https://github.com/conda-forge/python-feedstock/pull/511 * https://github.com/conda-forge/numba-feedstock/pull/86 * https://github.com/pydap/pydap/pull/210 - [ ] Closes #xxxx - [ ] Tests added - [ ] Passes `pre-commit run --all-files` - [ ] 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/5844/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 823955593,MDExOlB1bGxSZXF1ZXN0NTg2MjgwNjEw,5008,Allow dataset interpolation with different datatypes,14371165,closed,0,,,9,2021-03-07T16:21:37Z,2021-05-25T12:57:30Z,2021-05-13T15:28:16Z,MEMBER,,0,pydata/xarray/pulls/5008," Allow different datatypes (in particular booleans) to be interpolated instead of dropping them. - [x] Requires #4740. - [x] Closes #4761 - [x] Tests added - [x] Passes `pre-commit run --all-files`","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5008/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 892421264,MDExOlB1bGxSZXF1ZXN0NjQ1MTI4NjQ4,5315,Use _unstack_once for valid dask and sparse versions,14371165,closed,0,,,9,2021-05-15T11:42:57Z,2021-05-18T18:13:50Z,2021-05-17T22:49:18Z,MEMBER,,0,pydata/xarray/pulls/5315," - [x] Requires #5314 - [x] Passes `pre-commit run --all-files` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5315/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 679575175,MDU6SXNzdWU2Nzk1NzUxNzU=,4345,Improve Dataset documentation,14371165,closed,0,,,9,2020-08-15T13:27:33Z,2020-10-27T19:47:51Z,2020-10-27T19:47:51Z,MEMBER,,,,"**Is your feature request related to a problem? Please describe.** As a new user I find it difficult to get a new dataset initialized because the necessary parameters are not shown in the docstring. I have to google ""xarray dataset"" to get to http://xarray.pydata.org/en/stable/generated/xarray.Dataset.html to figure it out. In the figure below xarray.Dataset does not show the necessary parameters in the help pane: ![image](https://user-images.githubusercontent.com/14371165/90313058-aab66000-df09-11ea-9f3a-d2d3f2698b66.png) Compare to pandas.DataFrame that includes it: ![image](https://user-images.githubusercontent.com/14371165/90313083-e94c1a80-df09-11ea-8013-a7ffe90ab4d8.png) **Describe the solution you'd like** Looking at https://github.com/pydata/xarray/blob/master/xarray/core/dataset.py#L428 the `xr.Dataset.__init__.__doc__` does contain the necessary parameters so the suggestion is to simply move or copy that information up one level to` xr.Dataset.__doc__` For reference pandas does not use a docstring for the __init__ method: https://github.com/pandas-dev/pandas/blob/v1.1.0/pandas/core/frame.py#L339-L9257 The pandas docs also includes a few simple copy/pasteable examples on how to initialize. So a xarray example would be: ```python >>> import numpy as np >>> import xarray as xr >>> x = np.arange(4) >>> y = 2*x >>> ds = xr.Dataset({'y': (['x'], y)}, ... coords={'x': x}) >>> print(ds) Dimensions: (x: 4) Coordinates: * x (x) int32 0 1 2 3 Data variables: y (x) int32 0 2 4 6 ``` Or take some examples from http://xarray.pydata.org/en/stable/quick-overview.html#datasets or http://xarray.pydata.org/en/stable/data-structures.html#dataset although I found those a little bit confusing as they were dependent on previous results or rather complex with many dimensions. **Environment**:
Output of xr.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)] python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel byteorder: little LC_ALL: None LANG: en LOCALE: None.None libhdf5: 1.10.4 libnetcdf: None xarray: 0.15.0 pandas: 1.0.3 numpy: 1.18.1 scipy: 1.4.1 netCDF4: None pydap: None h5netcdf: None h5py: 2.10.0 Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2.14.0 distributed: 2.22.0 matplotlib: 3.1.3 cartopy: None seaborn: 0.10.0 numbagg: None setuptools: 49.2.1.post20200807 pip: 20.2.1 conda: 4.8.3 pytest: 6.0.1 IPython: 7.17.0 sphinx: 3.2.0 C:\ProgramData\Anaconda3\lib\site-packages\setuptools\distutils_patch.py:26: UserWarning: Distutils was imported before Setuptools. This usage is discouraged and may exhibit undesirable behaviors or errors. Please use Setuptools' objects directly or at least import Setuptools first. ""Distutils was imported before Setuptools. This usage is discouraged ""
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