10000 MAINT: simplifying annotations for np.core.from_numeric by BvB93 · Pull Request #16556 · numpy/numpy · GitHub
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MAINT: simplifying annotations for np.core.from_numeric #16556

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merged 5 commits into from
Jun 10, 2020
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MAINT: simplifying annotations for np.core.from_numeric #16556

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09c2204
Simplified annotations for functions requiring >=1D ArrayLike objects
Jun 9, 2020
481fdbe
Add the mypy cache to .gitgnore
Jun 9, 2020
1de9a5c
Simplified annotations for functions requiring >=1D ArrayLike objects
Jun 9, 2020
1862755
Moved .mypy_cache/ to the `Editor` section
Jun 9, 2020
0f7f6a9
Fixed a number of typing-related tests
Jun 10, 2020
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Simplified annotations for functions requiring >=1D ArrayLike objects 
* Affects a set of <20 functions from ``np.core.fromnumeric``.
* Based on feedback from numpy/numpy-stubs#71.
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Bas van Beek committed Jun 9, 2020
commit 09c2204e482b8573fbe2e8c25cef800b2df6393d
50 changes: 15 additions & 35 deletions numpy/__init__.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -936,21 +936,18 @@ def reshape(a: ArrayLike, newshape: _ShapeLike, order: _Order = ...) -> ndarray:
@overload
def choose(
a: _ScalarIntOrBool,
choices: Union[Sequence[ArrayLike], ndarray],
choices: ArrayLike,
out: Optional[ndarray] = ...,
mode: _Mode = ...,
) -> _ScalarIntOrBool: ...
@overload
def choose(
a: _IntOrBool,
choices: Union[Sequence[ArrayLike], ndarray],
out: Optional[ndarray] = ...,
mode: _Mode = ...,
a: _IntOrBool, choices: ArrayLike, out: Optional[ndarray] = ..., mode: _Mode = ...
) -> Union[integer, bool_]: ...
@overload
def choose(
a: _ArrayLikeIntOrBool,
choices: Union[Sequence[ArrayLike], ndarray],
choices: ArrayLike,
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Suggested change
choices: ArrayLike,
choices: Sequence[ArrayLike],

I think it's important to emphasize that this input is not an array, as it means shapes like (0, 3) are not handled sensibly.

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Same for the other overload

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The tricky part is that, without proper shape support, expressing this will be either very difficult and/or verbose.
For example even Sequence[ArrayLike] does not include the likes of np.ndarray or pd.DataFrane, both of which are (strictly speaking) not proper sequences.

out: Optional[ndarray] = ...,
mode: _Mode = ...,
) -> ndarray: ...
Expand All @@ -960,9 +957,7 @@ def repeat(
def put(
a: ndarray, ind: _ArrayLikeIntOrBool, v: ArrayLike, mode: _Mode = ...
) -> None: ...
def swapaxes(
a: Union[Sequence[ArrayLike], ndarray], axis1: int, axis2: int
) -> ndarray: ...
def swapaxes(a: ArrayLike, axis1: int, axis2: int) -> ndarray: ...
def transpose(
a: ArrayLike, axes: Union[None, Sequence[int], ndarray] = ...
) -> ndarray: ...
Expand Down Expand Up @@ -998,51 +993,39 @@ def argpartition(
order: Union[None, str, Sequence[str]] = ...,
) -> ndarray: ...
def sort(
a: Union[Sequence[ArrayLike], ndarray],
a: ArrayLike,
axis: Optional[int] = ...,
kind: Optional[_SortKind] = ...,
order: Union[None, str, Sequence[str]] = ...,
) -> ndarray: ...
def argsort(
a: Union[Sequence[ArrayLike], ndarray],
a: ArrayLike,
axis: Optional[int] = ...,
kind: Optional[_SortKind] = ...,
order: Union[None, str, Sequence[str]] = ...,
) -> ndarray: ...
@overload
def argmax(
a: Union[Sequence[ArrayLike], ndarray],
axis: None = ...,
out: Optional[ndarray] = ...,
) -> integer: ...
def argmax(a: ArrayLike, axis: None = ..., out: Optional[ndarray] = ...) -> integer: ...
@overload
def argmax(
a: Union[Sequence[ArrayLike], ndarray],
axis: int = ...,
out: Optional[ndarray] = ...,
a: ArrayLike, axis: int = ..., out: Optional[ndarray] = ...
) -> Union[integer, ndarray]: ...
@overload
def argmin(
a: Union[Sequence[ArrayLike], ndarray],
axis: None = ...,
out: Optional[ndarray] = ...,
) -> integer: ...
def argmin(a: ArrayLike, axis: None = ..., out: Optional[ndarray] = ...) -> integer: ...
@overload
def argmin(
a: Union[Sequence[ArrayLike], ndarray],
axis: int = ...,
out: Optional[ndarray] = ...,
a: ArrayLike, axis: int = ..., out: Optional[ndarray] = ...
) -> Union[integer, ndarray]: ...
@overload
def searchsorted(
a: Union[Sequence[ArrayLike], ndarray],
a: ArrayLike,
v: _Scalar,
side: _Side = ...,
sorter: Union[None, Sequence[_IntOrBool], ndarray] = ..., # 1D int array
) -> integer: ...
@overload
def searchsorted(
a: Union[Sequence[ArrayLike], ndarray],
a: ArrayLike,
v: ArrayLike,
side: _Side = ...,
sorter: Union[None, Sequence[_IntOrBool], ndarray] = ..., # 1D int array
Expand All @@ -1053,13 +1036,10 @@ def squeeze(a: _ScalarGeneric, axis: Optional[_ShapeLike] = ...) -> _ScalarGener
@overload
def squeeze(a: ArrayLike, axis: Optional[_ShapeLike] = ...) -> ndarray: ...
def diagonal(
a: Union[Sequence[Sequence[ArrayLike]], ndarray], # >= 2D array
offset: int = ...,
axis1: int = ...,
axis2: int = ...,
a: ArrayLike, offset: int = ..., axis1: int = ..., axis2: int = ... # >= 2D array
) -> ndarray: ...
def trace(
a: Union[Sequence[Sequence[ArrayLike]], ndarray], # >= 2D array
a: ArrayLike, # >= 2D array
offset: int = ...,
axis1: int = ...,
axis2: int = ...,
Expand All @@ -1070,7 +1050,7 @@ def ravel(a: ArrayLike, order: _Order = ...) -> ndarray: ...
def nonzero(a: ArrayLike) -> Tuple[ndarray, ...]: ...
def shape(a: ArrayLike) -> _Shape: ...
def compress(
condition: Union[Sequence[_Bool], ndarray], # 1D bool array
condition: ArrayLike, # 1D bool array
a: ArrayLike,
axis: Optional[int] = ...,
out: Optional[ndarray] = ...,
Expand Down
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