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jorenham merged 1 commit into from
Aug 18, 2025
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ENH: Extend numpy.pad to handle pad_width dictionary argument. #29273

jorenham merged 1 commit into from
Aug 18, 2025

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@carlosgmartin carlosgmartin commented Jun 25, 2025

Fixes #29268.

@carlosgmartin carlosgmartin force-pushed the numpy_pad_dict branch 5 times, most recently from 7f3f925 to 2e32e52 Compare June 25, 2025 23:29
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jorenham
jorenham reviewed Jun 26, 2025
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This seems pretty useful to me. And I think that using a dict to represent a sparse sequence makes sense.

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jorenham reviewed Jun 26, 2025
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github-actions bot commented Jun 26, 2025

Diff from mypy_primer, showing the effect of this PR on type check results on a corpus of open source code:

colour (https://github.com/colour-science/colour)
- colour/io/luts/lut.py:1378: note:     def [_ScalarT: generic[Any]] pad(array: _SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int], mode: Literal['constant', 'edge', 'linear_ramp', 'maximum', 'mean', 'median', 'minimum', 'reflect', 'symmetric', 'wrap', 'empty'] = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]
+ colour/io/luts/lut.py:1378: note:     def [_ScalarT: generic[Any]] pad(array: _SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'edge', 'linear_ramp', 'maximum', 'mean', 'median', 'minimum', 'reflect', 'symmetric', 'wrap', 'empty'] = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]
- colour/io/luts/lut.py:1378: note:     def pad(array: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int], mode: Literal['constant', 'edge', 'linear_ramp', 'maximum', 'mean', 'median', 'minimum', 'reflect', 'symmetric', 'wrap', 'empty'] = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[Any, ...], dtype[Any]]
+ colour/io/luts/lut.py:1378: note:     def pad(array: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: Literal['constant', 'edge', 'linear_ramp', 'maximum', 'mean', 'median', 'minimum', 'reflect', 'symmetric', 'wrap', 'empty'] = ..., *, stat_length: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | None = ..., constant_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., end_values: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] = ..., reflect_type: Literal['odd', 'even'] = ...) -> ndarray[tuple[Any, ...], dtype[Any]]
- colour/io/luts/lut.py:1378: note:     def [_ScalarT: generic[Any]] pad(array: _SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int], mode: _ModeFunc, **kwargs: Any) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]
+ colour/io/luts/lut.py:1378: note:     def [_ScalarT: generic[Any]] pad(array: _SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: _ModeFunc, **kwargs: Any) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]
- colour/io/luts/lut.py:1378: note:     def pad(array: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int], mode: _ModeFunc, **kwargs: Any) -> ndarray[tuple[Any, ...], dtype[Any]]
+ colour/io/luts/lut.py:1378: note:     def pad(array: Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], pad_width: _SupportsArray[dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[integer[Any]]]] | int | _NestedSequence[int] | dict[int, int] | dict[int, tuple[int, int]] | dict[int, int | tuple[int, int]], mode: _ModeFunc, **kwargs: Any) -> ndarray[tuple[Any, ...], dtype[Any]]

@carlosgmartin carlosgmartin requested a review from mattip June 26, 2025 18:03
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carlosgmartin commented Aug 17, 2025

@jorenham @mattip Just wondering, is there anything else you'd like me to do for this PR?

@jorenham jorenham merged commit e327be0 into numpy:main Aug 18, 2025
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jorenham commented Aug 18, 2025

All good :) Thanks Carlos!

@carlosgmartin carlosgmartin deleted the numpy_pad_dict branch August 18, 2025 03:21
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ENH: More user-friendly way to pad a specific axis

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