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 2161133346,PR_kwDOAMm_X85oSZw7,8797,tokenize() should ignore difference between None and {} attrs,6213168,closed,0,6213168,,1,2024-02-29T12:22:24Z,2024-03-01T11:15:30Z,2024-03-01T03:29:51Z,MEMBER,,0,pydata/xarray/pulls/8797,- Closes #8788,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8797/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2088095900,PR_kwDOAMm_X85kaiOH,8618,Re-enable mypy checks for parse_dims unit tests,6213168,closed,0,6213168,,1,2024-01-18T11:32:28Z,2024-01-19T15:49:33Z,2024-01-18T15:34:23Z,MEMBER,,0,pydata/xarray/pulls/8618,"As per https://github.com/pydata/xarray/pull/8606#discussion_r1452680454 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8618/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2079054085,PR_kwDOAMm_X85j77Os,8606,Clean up Dims type annotation,6213168,closed,0,6213168,,1,2024-01-12T15:05:40Z,2024-01-18T18:14:15Z,2024-01-16T10:26:08Z,MEMBER,,0,pydata/xarray/pulls/8606,,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8606/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 671216158,MDExOlB1bGxSZXF1ZXN0NDYxNDM4MDIz,4297,Lazily load resource files,6213168,closed,0,6213168,,4,2020-08-01T21:31:36Z,2020-09-22T05:32:38Z,2020-08-02T07:05:15Z,MEMBER,,0,pydata/xarray/pulls/4297,"- Marginal speed-up and RAM footprint reduction when not running in Jupyter Notebook - Closes #4294","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4297/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 671108068,MDExOlB1bGxSZXF1ZXN0NDYxMzM1NDAx,4296,Increase support window of all dependencies,6213168,closed,0,6213168,,7,2020-08-01T18:55:54Z,2020-08-14T09:52:46Z,2020-08-14T09:52:42Z,MEMBER,,0,pydata/xarray/pulls/4296,"Closes #4295 Increase width of the sliding window for minimum supported version: - setuptools from 6 months sliding window to hardcoded >= 38.4, and to 42 months sliding window starting from July 2021 - dask and distributed from 6 months sliding window to hardcoded >= 2.9, and to 12 months sliding window starting from January 2021 - all other libraries from 6 months to 12 months sliding window","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4296/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 521842949,MDExOlB1bGxSZXF1ZXN0MzQwMTQ1OTg0,3515,Recursive tokenization,6213168,closed,0,6213168,,1,2019-11-12T22:35:13Z,2019-11-13T00:54:32Z,2019-11-13T00:53:27Z,MEMBER,,0,pydata/xarray/pulls/3515,"After misreading the dask documentation , I was under the impression that the output of ``__dask_tokenize__`` would be recursively parsed, like it happens for ``__getstate__`` or ``__reduce__``. That's not the case - the output of ``__dask_tokenize__`` is just fed into a str() function so it has to be made explicitly recursive!","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3515/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 503163130,MDExOlB1bGxSZXF1ZXN0MzI1MDc2MzQ5,3375,Speed up isel and __getitem__,6213168,closed,0,6213168,,5,2019-10-06T21:27:42Z,2019-10-10T09:21:56Z,2019-10-09T18:01:30Z,MEMBER,,0,pydata/xarray/pulls/3375,"First iterative improvement for #2799. Speed up Dataset.isel up to 33% and DataArray.isel up to 25% (when there are no indices and the numpy array is small). 15% speedup when there are indices. Benchmarks can be found in #2799.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3375/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 500582648,MDExOlB1bGxSZXF1ZXN0MzIzMDIwOTY1,3358,Rolling minimum dependency versions policy,6213168,closed,0,6213168,,24,2019-09-30T23:50:39Z,2019-10-09T02:02:29Z,2019-10-08T21:23:47Z,MEMBER,,0,pydata/xarray/pulls/3358,"Closes #3222 Closes #3293 - Drop support for Python 3.5 - Upgrade numpy to 1.14 (24 months old) - Upgrade pandas to 0.24 (12 months old) - Downgrade scipy to 1.0 (policy allows for 1.2, but it breaks numpy=1.14) - Downgrade dask to 1.2 (6 months old) - Other upgrades/downgrades to comply with the policy - CI tool to verify that the minimum dependencies requirements in CI are compliant with the policy - Overhaul CI environment for readthedocs Out of scope: - Purge away all OrderedDict's","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3358/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 479359010,MDExOlB1bGxSZXF1ZXN0MzA2MjczNTY3,3202,chunk sparse arrays,6213168,closed,0,6213168,,4,2019-08-11T11:19:16Z,2019-08-12T21:02:31Z,2019-08-12T21:02:25Z,MEMBER,,0,pydata/xarray/pulls/3202,"Closes #3191 @shoyer I completely disabled wrapping in ImplicitToExplicitIndexingAdapter for sparse arrays, cupy arrays, etc. I'm not sure if it's desirable; the chief problem is that I don't think I understand the purpose of ImplicitToExplicitIndexingAdapter to begin with... some enlightenment would be appreciated.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3202/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull