🏷️ stub lib.user_array and lib._user_array_impl

src/numpy-stubs/lib/_user_array_impl.pyi

@@ -0,0 +1,219 @@
+from _typeshed import Incomplete
+from types import EllipsisType
+from typing import Any, Generic, SupportsIndex, TypeAlias, TypeVar, overload
+from typing_extensions import Self, deprecated, override
+
+import numpy as np
+import numpy.typing as npt
+from numpy._typing import _ArrayLike, _ArrayLikeBool_co, _ArrayLikeInt_co, _DTypeLike
+
+###
+
+_ScalarT = TypeVar("_ScalarT", bound=np.generic)
+_ShapeT = TypeVar("_ShapeT", bound=tuple[int, ...])
+_ShapeT_co = TypeVar("_ShapeT_co", bound=tuple[int, ...], default=Any, covariant=True)
+_DTypeT = TypeVar("_DTypeT", bound=np.dtype[Any])
+_DTypeT_co = TypeVar("_DTypeT_co", bound=np.dtype[Any], default=np.dtype[Any], covariant=True)
+
+_BoolArrayT = TypeVar("_BoolArrayT", bound=container[Any, np.dtype[np.bool]])
+_IntegralArrayT = TypeVar("_IntegralArrayT", bound=container[Any, np.dtype[np.bool | np.integer | np.object_]])
+_RealContainerT = TypeVar(
+    "_RealContainerT",
+    bound=container[Any, np.dtype[np.bool | np.integer | np.floating | np.timedelta64 | np.object_]],
+)
+_NumericContainerT = TypeVar("_NumericContainerT", bound=container[Any, np.dtype[np.number | np.timedelta64 | np.object_]])
+
+_ArrayInt_co: TypeAlias = npt.NDArray[np.integer | np.bool]
+
+_ToIndexSlice: TypeAlias = slice | EllipsisType | _ArrayInt_co | None
+_ToIndexSlices: TypeAlias = _ToIndexSlice | tuple[_ToIndexSlice, ...]
+_ToIndex: TypeAlias = SupportsIndex | _ToIndexSlice
+_ToIndices: TypeAlias = _ToIndex | tuple[_ToIndex, ...]
+
+###
+
+class container(Generic[_ShapeT_co, _DTypeT_co]):
+    array: np.ndarray[_ShapeT_co, _DTypeT_co]
+
+    @overload
+    def __init__(
+        self,
+        /,
+        data: container[_ShapeT_co, _DTypeT_co] | np.ndarray[_ShapeT_co, _DTypeT_co],
+        dtype: None = None,
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: container[Any, np.dtype[_ScalarT]],
+        /,
+        data: _ArrayLike[_ScalarT],
+        dtype: None = None,
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(
+        self: container[Any, np.dtype[_ScalarT]],
+        /,
+        data: npt.ArrayLike,
+        dtype: _DTypeLike[_ScalarT],
+        copy: bool = True,
+    ) -> None: ...
+    @overload
+    def __init__(self, /, data: npt.ArrayLike, dtype: npt.DTypeLike | None = None, copy: bool = True) -> None: ...
+
+    #
+    def __complex__(self, /) -> complex: ...
+    def __float__(self, /) -> float: ...
+    def __int__(self, /) -> int: ...
+    def __hex__(self, /) -> str: ...
+    def __oct__(self, /) -> str: ...
+
+    #
+    @override
+    def __eq__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+    @override
+    def __ne__(self, other: object, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
+
+    #
+    def __lt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __le__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __gt__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+    def __ge__(self, other: npt.ArrayLike, /) -> container[_ShapeT_co, np.dtype[np.bool]]: ...
+
+    #
+    def __len__(self, /) -> int: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __getitem__(self, key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> container[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, key: _ToIndexSlices, /) -> container[Any, _DTypeT_co]: ...
+    @overload
+    def __getitem__(self, key: _ToIndices, /) -> Any: ...
+    @overload
+    def __getitem__(self: container[Any, np.dtype[np.void]], key: list[str], /) -> container[_ShapeT_co, np.dtype[np.void]]: ...
+    @overload
+    def __getitem__(self: container[Any, np.dtype[np.void]], key: str, /) -> container[_ShapeT_co, np.dtype[Any]]: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __setitem__(self, index: _ToIndices, value: object, /) -> None: ...
+    @overload
+    def __setitem__(self: container[Any, np.dtype[np.void]], key: str | list[str], value: object, /) -> None: ...
+
+    # keep in sync with np.ndarray
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex64]], /) -> container[_ShapeT, np.dtype[np.float32]]: ...  # type: ignore[overload-overlap]
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex128]], /) -> container[_ShapeT, np.dtype[np.float64]]: ...
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex192]], /) -> container[_ShapeT, np.dtype[np.float96]]: ...
+    @overload
+    def __abs__(self: container[_ShapeT, np.dtype[np.complex256]], /) -> container[_ShapeT, np.dtype[np.float128]]: ...
+    @overload
+    def __abs__(self: _RealContainerT, /) -> _RealContainerT: ...
+
+    #
+    def __neg__(self: _NumericContainerT, /) -> _NumericContainerT: ...  # noqa: PYI019
+    def __pos__(self: _NumericContainerT, /) -> _NumericContainerT: ...  # noqa: PYI019
+    def __invert__(self: _IntegralArrayT, /) -> _IntegralArrayT: ...  # noqa: PYI019
+
+    # TODO(jorenham): complete these binary ops
+
+    #
+    def __add__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __radd__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __iadd__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __sub__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rsub__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __isub__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __mul__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rmul__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __imul__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __div__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rdiv__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __idiv__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __mod__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rmod__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __imod__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __divmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ...
+    def __rdivmod__(self, other: npt.ArrayLike, /) -> tuple[Incomplete, Incomplete]: ...
+
+    #
+    def __pow__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __rpow__(self, other: npt.ArrayLike, /) -> Incomplete: ...
+    def __ipow__(self, other: npt.ArrayLike, /) -> Self: ...
+
+    #
+    def __lshift__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.integer]]: ...
+    def __rlshift__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.integer]]: ...
+    def __ilshift__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    def __rshift__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.integer]]: ...
+    def __rrshift__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.integer]]: ...
+    def __irshift__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __and__(self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /) -> container[Any, np.dtype[np.bool]]: ...
+    @overload
+    def __and__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.bool | np.integer]]: ...
+    __rand__ = __and__
+    @overload
+    def __iand__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __iand__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __xor__(self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /) -> container[Any, np.dtype[np.bool]]: ...
+    @overload
+    def __xor__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.bool | np.integer]]: ...
+    __rxor__ = __xor__
+    @overload
+    def __ixor__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __ixor__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __or__(self: container[Any, np.dtype[np.bool]], other: _ArrayLikeBool_co, /) -> container[Any, np.dtype[np.bool]]: ...
+    @overload
+    def __or__(self, other: _ArrayLikeInt_co, /) -> container[Any, np.dtype[np.bool | np.integer]]: ...
+    __ror__ = __or__
+    @overload
+    def __ior__(self: _BoolArrayT, other: _ArrayLikeBool_co, /) -> _BoolArrayT: ...
+    @overload
+    def __ior__(self, other: _ArrayLikeInt_co, /) -> Self: ...
+
+    #
+    @overload
+    def __array__(self, /, t: None = None) -> np.ndarray[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __array__(self, /, t: _DTypeT) -> np.ndarray[_ShapeT_co, _DTypeT]: ...
+
+    #
+    @overload
+    def __array_wrap__(self, arg0: npt.ArrayLike, /) -> container[_ShapeT_co, _DTypeT_co]: ...
+    @overload
+    def __array_wrap__(self, a: np.ndarray[_ShapeT, _DTypeT], c: Any = ..., s: Any = ..., /) -> container[_ShapeT, _DTypeT]: ...
+
+    #
+    def copy(self, /) -> Self: ...
+    @deprecated("tostring() is deprecated. Use tobytes() instead.")
+    def tostring(self, /) -> bytes: ...
+    def tobytes(self, /) -> bytes: ...
+    def byteswap(self, /) -> Self: ...
+    def astype(self, /, typecode: _DTypeLike[_ScalarT]) -> container[_ShapeT_co, np.dtype[_ScalarT]]: ...

src/numpy-stubs/lib/user_array.pyi

@@ -0,0 +1 @@
+from ._user_array_impl import container as container

test/runtime/accept/lib_user_array.py

@@ -0,0 +1,22 @@
+"""Base on the `if __name__ == "__main__"` test code in `lib/_user_array_impl.py`."""
+
+from __future__ import annotations
+
+import numpy as np
+from numpy.lib.user_array import container
+
+N = 10_000
+W = H = int(N**0.5)
+
+a: np.ndarray[tuple[int, int], np.dtype[np.int32]]
+ua: container[tuple[int, int], np.dtype[np.int32]]
+
+a = np.arange(N, dtype=np.int32).reshape(W, H)
+ua = container(a)
+
+ua_small: container[tuple[int, int], np.dtype[np.int32]] = ua[:3, :5]
+ua_small[0, 0] = 10
+
+ua_bool: container[tuple[int, int], np.dtype[np.bool]] = ua_small > 1
+
+# shape: tuple[int, int] = np.shape(ua)