Hi everyone,
I've noticed that NumPy currently users separate type stub files for specifying
types for both pure Python and native modules. For example the (untyped)
implementation of np.core._asarray is in [1], but the types are in [2]. This
works fine for type checkers, and if anything, impro
> I think that's on purpose, because the type annotations are quite complex.
> For reasons of correctness/completeleness, they use protocols, mixins, and
> overloads. Inside pure Python code, that would be harder to read and
> maintain.
I agree that NumPy type annotations are quite complex. Howeve
