TYP: Relax the return-type of np.vectorize (#20908)

* MAINT: Relax the return-type of `np.vectorize`

* DOC: Add a note regarding a potential future mypy plugin for dealing with literal signatures

Co-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>

numpy/__init__.pyi

@@ -3679,6 +3679,8 @@ class memmap(ndarray[_ShapeType, _DType_co]):
     ) -> Any: ...
     def flush(self) -> None: ...
 
+# TODO: Add a mypy plugin for managing functions whose output type is dependant
+# on the literal value of some sort of signature (e.g. `einsum` and `vectorize`)
 class vectorize:
     pyfunc: Callable[..., Any]
     cache: bool
@@ -3695,7 +3697,7 @@ class vectorize:
         cache: bool = ...,
         signature: None | str = ...,
     ) -> None: ...
-    def __call__(self, *args: Any, **kwargs: Any) -> NDArray[Any]: ...
+    def __call__(self, *args: Any, **kwargs: Any) -> Any: ...
 
 class poly1d:
     @property

numpy/typing/tests/data/reveal/lib_function_base.pyi

@@ -26,7 +26,7 @@ reveal_type(vectorized_func.signature)  # E: Union[None, builtins.str]
 reveal_type(vectorized_func.otypes)  # E: Union[None, builtins.str]
 reveal_type(vectorized_func.excluded)  # E: set[Union[builtins.int, builtins.str]]
 reveal_type(vectorized_func.__doc__)  # E: Union[None, builtins.str]
-reveal_type(vectorized_func([1]))  # E: ndarray[Any, dtype[Any]]
+reveal_type(vectorized_func([1]))  # E: Any
 reveal_type(np.vectorize(int))  # E: vectorize
 reveal_type(np.vectorize(  # E: vectorize
     int, otypes="i", doc="doc", excluded=(), cache=True, signature=None