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File Content: `array_like.py`

from __future__ import annotations

from typing import Any

import numpy as np
from numpy._typing import ArrayLike, _SupportsArray

x1: ArrayLike = True
x2: ArrayLike = 5
x3: ArrayLike = 1.0
x4: ArrayLike = 1 + 1j
x5: ArrayLike = np.int8(1)
x6: ArrayLike = np.float64(1)
x7: ArrayLike = np.complex128(1)
x8: ArrayLike = np.array([1, 2, 3])
x9: ArrayLike = [1, 2, 3]
x10: ArrayLike = (1, 2, 3)
x11: ArrayLike = "foo"
x12: ArrayLike = memoryview(b'foo')


class A:
    def __array__(self, dtype: None | np.dtype[Any] = None) -> np.ndarray:
        return np.array([1, 2, 3])


x13: ArrayLike = A()

scalar: _SupportsArray = np.int64(1)
scalar.__array__()
array: _SupportsArray = np.array(1)
array.__array__()

a: _SupportsArray = A()
a.__array__()
a.__array__()

# Escape hatch for when you mean to make something like an object
# array.
object_array_scalar: Any = (i for i in range(10))
np.array(object_array_scalar)

Name	Size	Permission
__pycache__	---	0755
arithmetic.py	7455 bytes	0644
array_constructors.py	2419 bytes	0644
array_like.py	916 bytes	0644
arrayprint.py	766 bytes	0644
arrayterator.py	393 bytes	0644
bitwise_ops.py	970 bytes	0644
comparisons.py	2992 bytes	0644
dtype.py	1069 bytes	0644
einsumfunc.py	1370 bytes	0644
flatiter.py	174 bytes	0644
fromnumeric.py	3742 bytes	0644
index_tricks.py	1492 bytes	0644
lib_utils.py	420 bytes	0644
lib_version.py	299 bytes	0644
literal.py	1331 bytes	0644
mod.py	1578 bytes	0644
modules.py	595 bytes	0644
multiarray.py	1331 bytes	0644
ndarray_conversion.py	1626 bytes	0644
ndarray_misc.py	2715 bytes	0644
ndarray_shape_manipulation.py	640 bytes	0644
numeric.py	1490 bytes	0644
numerictypes.py	750 bytes	0644
random.py	61881 bytes	0644
scalars.py	3479 bytes	0644
simple.py	2676 bytes	0644
simple_py3.py	96 bytes	0644
ufunc_config.py	1120 bytes	0644
ufunclike.py	1039 bytes	0644
ufuncs.py	462 bytes	0644
warnings_and_errors.py	150 bytes	0644

File Content: array_like.py

File Content: `array_like.py`