pull_requests: 1573847243
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| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1573847243 | PR_kwDOAMm_X85dzwDL | 8376 | closed | 0 | Add chunkedduckarray to _typing | 14371165 | Add more chunkedarray typing options. Also clean up some ideas that didn't work out. Using TypeVar for arrays for example has turned out to not work that great because of the very common dtype changes. If you want to check if an ArrayLike is a chunked array: ```python if isinstance(data, _chunkedarrayfunction_or_api): data.chunk() ``` However try to rely on mypy in private functions over isinstance checks for better performance: ```python def _do_compute(data: chunkedduckarray[Any, _DType]) -> duckarray[Any, _DType]: return data.compute() ``` | 2023-10-25T23:09:46Z | 2023-10-26T19:10:41Z | 2023-10-26T01:13:54Z | 2023-10-26T01:13:54Z | 043b3dc36e3c2a4b8928ddd559c4f7291d563099 | 0 | ee089807176f3ff497efd9c35a4aa0d6cc0200d5 | 70c4ee73a7524526d58b8394d449d010720f205f | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/8376 |
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