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TYP: fix ndarray.tolist() and .item() for unknown dtype #28650

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Merged
merged 1 commit into from
Apr 4, 2025
Merged

TYP: fix ndarray.tolist() and .item() for unknown dtype #28650

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55 changes: 14 additions & 41 deletions 55 numpy/__init__.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -1093,35 +1093,11 @@ class _SupportsItem(Protocol[_T_co]):
class _SupportsDLPack(Protocol[_T_contra]):
def __dlpack__(self, /, *, stream: _T_contra | None = None) -> CapsuleType: ...

@type_check_only
class _HasShape(Protocol[_ShapeT_co]):
@property
def shape(self, /) -> _ShapeT_co: ...

@type_check_only
class _HasDType(Protocol[_T_co]):
@property
def dtype(self, /) -> _T_co: ...

@type_check_only
class _HasShapeAndSupportsItem(_HasShape[_ShapeT_co], _SupportsItem[_T_co], Protocol[_ShapeT_co, _T_co]): ...

# matches any `x` on `x.type.item() -> _T_co`, e.g. `dtype[np.int8]` gives `_T_co: int`
@type_check_only
class _HasTypeWithItem(Protocol[_T_co]):
@property
def type(self, /) -> type[_SupportsItem[_T_co]]: ...

# matches any `x` on `x.shape: _ShapeT_co` and `x.dtype.type.item() -> _T_co`,
# useful for capturing the item-type (`_T_co`) of the scalar-type of an array with
# specific shape (`_ShapeT_co`).
@type_check_only
class _HasShapeAndDTypeWithItem(Protocol[_ShapeT_co, _T_co]):
@property
def shape(self, /) -> _ShapeT_co: ...
@property
def dtype(self, /) -> _HasTypeWithItem[_T_co]: ...

@type_check_only
class _HasRealAndImag(Protocol[_RealT_co, _ImagT_co]):
@property
Expand Down Expand Up @@ -2204,29 +2180,26 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeT_co, _DType_co]):
@property
def flat(self) -> flatiter[Self]: ...

@overload # special casing for `StringDType`, which has no scalar type
def item(self: ndarray[Any, dtypes.StringDType], /) -> str: ...
@overload
def item(self: ndarray[Any, dtypes.StringDType], arg0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /) -> str: ...
@overload
def item(self: ndarray[Any, dtypes.StringDType], /, *args: SupportsIndex) -> str: ...
@overload # use the same output type as that of the underlying `generic`
def item(self: _HasShapeAndDTypeWithItem[Any, _T], /) -> _T: ...
@overload
def item(self: _HasShapeAndDTypeWithItem[Any, _T], arg0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /) -> _T: ...
@overload
def item(self: _HasShapeAndDTypeWithItem[Any, _T], /, *args: SupportsIndex) -> _T: ...
def item(self: NDArray[generic[_T]], i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> _T: ...
@overload # special casing for `StringDType`, which has no scalar type
def item(
self: ndarray[Any, dtypes.StringDType],
arg0: SupportsIndex | tuple[SupportsIndex, ...] = ...,
/,
*args: SupportsIndex,
) -> str: ...

@overload
def tolist(self: _HasShapeAndSupportsItem[tuple[()], _T], /) -> _T: ...
def tolist(self: ndarray[tuple[()], dtype[generic[_T]]], /) -> _T: ...
@overload
def tolist(self: _HasShapeAndSupportsItem[tuple[int], _T], /) -> list[_T]: ...
def tolist(self: ndarray[tuple[int], dtype[generic[_T]]], /) -> list[_T]: ...
@overload
def tolist(self: _HasShapeAndSupportsItem[tuple[int, int], _T], /) -> list[list[_T]]: ...
def tolist(self: ndarray[tuple[int, int], dtype[generic[_T]]], /) -> list[list[_T]]: ...
@overload
def tolist(self: _HasShapeAndSupportsItem[tuple[int, int, int], _T], /) -> list[list[list[_T]]]: ...
def tolist(self: ndarray[tuple[int, int, int], dtype[generic[_T]]], /) -> list[list[list[_T]]]: ...
@overload
def tolist(self: _HasShapeAndSupportsItem[Any, _T], /) -> _T | list[_T] | list[list[_T]] | list[list[list[Any]]]: ...
def tolist(self, /) -> Any: ...

@overload
def resize(self, new_shape: _ShapeLike, /, *, refcheck: builtins.bool = ...) -> None: ...
Expand Down Expand Up @@ -5379,7 +5352,7 @@ class matrix(ndarray[_2DShapeT_co, _DType_co]):
def ptp(self, axis: None | _ShapeLike = ..., out: _ArrayT = ...) -> _ArrayT: ...

def squeeze(self, axis: None | _ShapeLike = ...) -> matrix[_2D, _DType_co]: ...
def tolist(self: _SupportsItem[_T]) -> list[list[_T]]: ...
def tolist(self: matrix[Any, dtype[generic[_T]]]) -> list[list[_T]]: ... # pyright: ignore[reportIncompatibleMethodOverride]
def ravel(self, /, order: _OrderKACF = "C") -> matrix[tuple[L[1], int], _DType_co]: ... # pyright: ignore[reportIncompatibleMethodOverride]
def flatten(self, /, order: _OrderKACF = "C") -> matrix[tuple[L[1], int], _DType_co]: ... # pyright: ignore[reportIncompatibleMethodOverride]

Expand Down
11 changes: 9 additions & 2 deletions 11 numpy/typing/tests/data/reveal/ndarray_conversion.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -30,8 +30,15 @@ assert_type(b1_0d.tolist(), bool)
assert_type(u2_1d.tolist(), list[int])
assert_type(i4_2d.tolist(), list[list[int]])
assert_type(f8_3d.tolist(), list[list[list[float]]])
assert_type(cG_4d.tolist(), complex | list[complex] | list[list[complex]] | list[list[list[Any]]])
assert_type(i0_nd.tolist(), int | list[int] | list[list[int]] | list[list[list[Any]]])
assert_type(cG_4d.tolist(), Any)
assert_type(i0_nd.tolist(), Any)

# regression tests for numpy/numpy#27944
any_dtype: np.ndarray[Any, Any]
any_sctype: np.ndarray[Any, Any]
assert_type(any_dtype.tolist(), Any)
assert_type(any_sctype.tolist(), Any)


# itemset does not return a value
# tostring is pretty simple
Expand Down
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