Merge pull request numpy#27736 from jorenham/typing/scalar-type-parameter-defaults

TYP: Optional ``numpy.number`` type parameters

Author: charris

doc/release/upcoming_changes/27736.new_feature.rst

@@ -0,0 +1,3 @@
+* The "nbit" type parameter of ``np.number`` and its subtypes now defaults
+  to ``typing.Any``. This way, type-checkers will infer annotations such as
+  ``x: np.floating``  as ``x: np.floating[Any]``, even in strict mode.

numpy/__init__.pyi

@@ -3081,8 +3081,8 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType_co, _DType_co]):
 # See https://github.com/numpy/numpy-stubs/pull/80 for more details.
 
 _ScalarType = TypeVar("_ScalarType", bound=generic)
-_NBit = TypeVar("_NBit", bound=NBitBase)
-_NBit1 = TypeVar("_NBit1", bound=NBitBase)
+_NBit = TypeVar("_NBit", bound=NBitBase, default=Any)
+_NBit1 = TypeVar("_NBit1", bound=NBitBase, default=Any)
 _NBit2 = TypeVar("_NBit2", bound=NBitBase, default=_NBit1)
 _NBit_fc = TypeVar("_NBit_fc", _NBitHalf, _NBitSingle, _NBitDouble, _NBitLongDouble)