Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/numpy/typing/tests/data/pass/array_like.py

@@ -0,0 +1,43 @@
+from __future__ import annotations
+
+from typing import Any
+
+import numpy as np
+from numpy._typing import NDArray, 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
+    ) -> NDArray[np.float64]:
+        return np.array([1.0, 2.0, 3.0])
+
+
+x13: ArrayLike = A()
+
+scalar: _SupportsArray[np.dtype[np.int64]] = np.int64(1)
+scalar.__array__()
+array: _SupportsArray[np.dtype[np.int_]] = np.array(1)
+array.__array__()
+
+a: _SupportsArray[np.dtype[np.float64]] = A()
+a.__array__()
+a.__array__()
+
+# Escape hatch for when you mean to make something like an object
+# array.
+object_array_scalar: object = (i for i in range(10))
+np.array(object_array_scalar)