Thanks @johnthagen. This is more of a feature request I think. All of numpy.ma has type stubs, but no return types. The following diff will make your example pass (note: the actually correct way of doing this is a bit different, look at the class ndarray annotations in numpy/__init__.pyi for how to annotate an array class):

diff --git a/numpy/ma/core.pyi b/numpy/ma/core.pyi
index d6cc0a782c..c3f27e1271 100644
--- a/numpy/ma/core.pyi
+++ b/numpy/ma/core.pyi
@@ -167,7 +167,7 @@ def __next__(self): ...
 
 class MaskedArray(ndarray[_ShapeType, _DType_co]):
     __array_priority__: Any
-    def __new__(cls, data=..., mask=..., dtype=..., copy=..., subok=..., ndmin=..., fill_value=..., keep_mask=..., hard_mask=..., shrink=..., order=...): ...
+    def __new__(cls, data=..., mask=..., dtype=..., copy=..., subok=..., ndmin=..., fill_value=..., keep_mask=..., hard_mask=..., shrink=..., order=...) -> 'MaskedArray': ...
     def __array_finalize__(self, obj): ...
     def __array_wrap__(self, obj, context=..., return_scalar=...): ...
     def view(self, dtype=..., type=..., fill_value=...): ...
@@ -358,7 +358,7 @@ def array(
     shrink=...,
     subok=...,
     ndmin=...,
-): ...
+) -> MaskedArray: ...
 def is_masked(x): ...
 
 class _extrema_operation(_MaskedUFunc):

But that whole core.pyi file needs to be expanded to have return types. That's not a small amount of work.

I'll change this to an enhancement request.

I'll change this to an enhancement request.

No problem! I was under the impression that all of Numpy fully supported static typing (and even includes its own Mypy plugin) so that it why I thought it was a bug report if some of the static typing was incorrect/missing.

Regardless, thank you for the clear feedback and consideration.

I think all namespaces should have entries for all public objects, and the main namespaces and most important other namespaces (fft, linalg, etc.) are fully typed. But some other ones are not.

I'd be glad to help! I Just need some guidance or a checklist. Is it literally all the functions and methods in ma/core.pyi? I could create a PR for MaskedArray or any smaller class first.

Is it literally all the functions and methods in ma/core.pyi?

Pretty much, yes. Also the other numpy/ma/*.pyi files, but core.pyi contains the most important ones.

I'd suggest picking a small, representative subset and typing those. Once the review on those is done, that establishes the patterns to expand to the full set of functions/objects.

E.g.:

• functions: min, take, diag, ndim, set_fill_value, fix_invalid
• _MaskedUfunc
• MaskedArray methods/properties: all, copy, shape, mask

And use the type annotations for the functions in the main namespace, as well as the np.ndarray/np.ufunc ones, for reference.

Typing ma/core.pyi

The non-exhaustive list below serves as a guide for typing all of ma/core.pyi.

First batch

• functions
  • min TYP: type ma.min #26624
  • max
  • ptp
  • take
  • diag
  • ndim
  • shape
  • size
  • transpose
  • set_fill_value
  • fix_invalid
  • zeros_like TYP: add ma.zeros_like and ma.ones_like typing #27323
  • ones_like TYP: add ma.zeros_like and ma.ones_like typing #27323
• _MaskedUfunc
• MaskedArray
  • all
  • copy
  • shape TYP: Make array _ShapeType bound and covariant #26081
  • mask

Second batch

• functions
  • power
  • argsort
  • sort
  • compressed
  • concatenate
  • diag
  • left_shift
  • right_shift
  • put
  • putmask
  • reshape
  • resize
  • diff
  • where
  • choose
  • round
• _convert2ma:
• _MaskedUnaryOperation
• _MaskedBinaryOperation
• MaskedArray
  • ...

Third batch

• functions
  • inner
  • outer
  • correlate
  • convolve
  • allequal
  • allclose
  • asarray
  • asanyarray
  • fromflex
  • append
  • dot
  • mask_rowcols
  • default_fill_value
  • minimum_fill_value
  • maximum_fill_value
  • common_fill_value
  • filled
  • getdata
• _DomainBinaryOperation
• _frommethod

#26081 implements shape