Edit: 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)
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