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| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1936840711 | PR_kwDOAMm_X85cdvXs | 8294 | Use shape and dtype as typevars in NamedArray | Illviljan 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.
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 |
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xarray 13221727 | pull |
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