feat: reduce np.ndarray #1462
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feat: reduce np.ndarray #1462
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| class CategoricalIndex(ExtensionIndex[S1], accessor.PandasDelegate): | ||
| codes: np.ndarray = ... | ||
| codes: npt.NDArray[Any] = ... |
cmp0xff
commented
Oct 31, 2025
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| class CategoricalIndex(ExtensionIndex[S1], accessor.PandasDelegate): | ||
| codes: np.ndarray = ... | ||
| codes: npt.NDArray[Any] = ... |
cmp0xff
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Dr-Irv
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Nov 4, 2025
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Dr-Irv
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A few main issues:
- I think we should be consistent in the stubs in using the
np_ndarray_xxxtypes that are now in_typing.pyi, rather thannpt.NDArray[np.integer], etc. I think it's better to use those types that we have in_typing.pyiso we can be consistent througout the stubs. pd.unique(someIndex)andIndex.unique()are a bit of a mess, because the behavior changes from 2.3 to 3.0. See the release notes: https://pandas.pydata.org/docs/dev/whatsnew/v3.0.0.html#other . So what we need to do here is return thenumpytypes as is done in 2.3, and put in a comment to switch to theIndextypes when 3.0 is released.- I don't think we should use
npt.NDArray[np.double]in the stubs. We always usenp.floating - There are places where we can be more precise on what are the allowed numpy array types as arguments.
I didn't necessarily pick up everything related to the main issues, and some of my comments are related to the 3 issues above.
cmp0xff
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Nov 9, 2025
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Dr-Irv
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Nov 10, 2025
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This is getting pretty close
…f10f24c48218f3268279ec5d33cc70#r2511081138
…f10f24c48218f3268279ec5d33cc70#r2510949482
Dr-Irv
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Nov 10, 2025
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Nov 11, 2025
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npt.NDArrayto benpt.NDArray[Any]