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ðŸ“ ..
ðŸ“„ __init__.py(2.7 KB)
ðŸ“„ __init__.pyi(5.46 KB)
ðŸ“ __pycache__
ðŸ“„ _datasource.py(22.1 KB)
ðŸ“„ _iotools.py(30.14 KB)
ðŸ“„ _version.py(4.74 KB)
ðŸ“„ _version.pyi(633 B)
ðŸ“„ arraypad.py(31.06 KB)
ðŸ“„ arraypad.pyi(1.69 KB)
ðŸ“„ arraysetops.py(32.87 KB)
ðŸ“„ arraysetops.pyi(8.14 KB)
ðŸ“„ arrayterator.py(6.9 KB)
ðŸ“„ arrayterator.pyi(1.5 KB)
ðŸ“„ format.py(33.95 KB)
ðŸ“„ format.pyi(748 B)
ðŸ“„ function_base.py(184.67 KB)
ðŸ“„ function_base.pyi(16.2 KB)
ðŸ“„ histograms.py(36.81 KB)
ðŸ“„ histograms.pyi(995 B)
ðŸ“„ index_tricks.py(30.61 KB)
ðŸ“„ index_tricks.pyi(4.15 KB)
ðŸ“„ mixins.py(6.91 KB)
ðŸ“„ mixins.pyi(3.04 KB)
ðŸ“„ nanfunctions.py(64.23 KB)
ðŸ“„ nanfunctions.pyi(606 B)
ðŸ“„ npyio.py(95.04 KB)
ðŸ“„ npyio.pyi(9.5 KB)
ðŸ“„ polynomial.py(43.1 KB)
ðŸ“„ polynomial.pyi(6.79 KB)
ðŸ“„ recfunctions.py(58.03 KB)
ðŸ“„ scimath.py(14.68 KB)
ðŸ“„ scimath.pyi(2.82 KB)
ðŸ“„ setup.py(405 B)
ðŸ“„ shape_base.py(38.03 KB)
ðŸ“„ shape_base.pyi(5.06 KB)
ðŸ“„ stride_tricks.py(17.49 KB)
ðŸ“„ stride_tricks.pyi(1.71 KB)
ðŸ“ tests
ðŸ“„ twodim_base.py(32.17 KB)
ðŸ“„ twodim_base.pyi(5.24 KB)
ðŸ“„ type_check.py(19.49 KB)
ðŸ“„ type_check.pyi(5.44 KB)
ðŸ“„ ufunclike.py(6.18 KB)
ðŸ“„ ufunclike.pyi(1.26 KB)
ðŸ“„ user_array.py(7.54 KB)
ðŸ“„ utils.py(36.92 KB)
ðŸ“„ utils.pyi(2.3 KB)

Editing: stride_tricks.pyi

from collections.abc import Iterable
from typing import Any, TypeVar, overload, SupportsIndex

from numpy import generic
from numpy._typing import (
    NDArray,
    ArrayLike,
    _ShapeLike,
    _Shape,
    _ArrayLike
)

_SCT = TypeVar("_SCT", bound=generic)

__all__: list[str]

class DummyArray:
    __array_interface__: dict[str, Any]
    base: None | NDArray[Any]
    def __init__(
        self,
        interface: dict[str, Any],
        base: None | NDArray[Any] = ...,
    ) -> None: ...

@overload
def as_strided(
    x: _ArrayLike[_SCT],
    shape: None | Iterable[int] = ...,
    strides: None | Iterable[int] = ...,
    subok: bool = ...,
    writeable: bool = ...,
) -> NDArray[_SCT]: ...
@overload
def as_strided(
    x: ArrayLike,
    shape: None | Iterable[int] = ...,
    strides: None | Iterable[int] = ...,
    subok: bool = ...,
    writeable: bool = ...,
) -> NDArray[Any]: ...

@overload
def sliding_window_view(
    x: _ArrayLike[_SCT],
    window_shape: int | Iterable[int],
    axis: None | SupportsIndex = ...,
    *,
    subok: bool = ...,
    writeable: bool = ...,
) -> NDArray[_SCT]: ...
@overload
def sliding_window_view(
    x: ArrayLike,
    window_shape: int | Iterable[int],
    axis: None | SupportsIndex = ...,
    *,
    subok: bool = ...,
    writeable: bool = ...,
) -> NDArray[Any]: ...

@overload
def broadcast_to(
    array: _ArrayLike[_SCT],
    shape: int | Iterable[int],
    subok: bool = ...,
) -> NDArray[_SCT]: ...
@overload
def broadcast_to(
    array: ArrayLike,
    shape: int | Iterable[int],
    subok: bool = ...,
) -> NDArray[Any]: ...

def broadcast_shapes(*args: _ShapeLike) -> _Shape: ...

def broadcast_arrays(
    *args: ArrayLike,
    subok: bool = ...,
) -> list[NDArray[Any]]: ...

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