golden hour

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/lib

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

Edit: arrayterator.pyi

from collections.abc import Generator
from typing import (
    Any,
    TypeVar,
    Union,
    overload,
)

from numpy import ndarray, dtype, generic
from numpy._typing import DTypeLike

# TODO: Set a shape bound once we've got proper shape support
_Shape = TypeVar("_Shape", bound=Any)
_DType = TypeVar("_DType", bound=dtype[Any])
_ScalarType = TypeVar("_ScalarType", bound=generic)

_Index = Union[
    Union[ellipsis, int, slice],
    tuple[Union[ellipsis, int, slice], ...],
]

__all__: list[str]

# NOTE: In reality `Arrayterator` does not actually inherit from `ndarray`,
# but its ``__getattr__` method does wrap around the former and thus has
# access to all its methods

class Arrayterator(ndarray[_Shape, _DType]):
    var: ndarray[_Shape, _DType]  # type: ignore[assignment]
    buf_size: None | int
    start: list[int]
    stop: list[int]
    step: list[int]

@property  # type: ignore[misc]
    def shape(self) -> tuple[int, ...]: ...
    @property
    def flat(  # type: ignore[override]
        self: ndarray[Any, dtype[_ScalarType]]
    ) -> Generator[_ScalarType, None, None]: ...
    def __init__(
        self, var: ndarray[_Shape, _DType], buf_size: None | int = ...
    ) -> None: ...
    @overload
    def __array__(self, dtype: None = ...) -> ndarray[Any, _DType]: ...
    @overload
    def __array__(self, dtype: DTypeLike) -> ndarray[Any, dtype[Any]]: ...
    def __getitem__(self, index: _Index) -> Arrayterator[Any, _DType]: ...
    def __iter__(self) -> Generator[ndarray[Any, _DType], None, None]: ...