First, KDTree returns NumPy scalars everywhere because the results come from indexing NumPy arrays. Whereas, cKDTree returns python ints wherever possible. Is it reasonable for an API to change from returning NumPy scalars to python int? The NumPy scalars do mimic the array interface to some extent so there is a small interface incompatibility. However, the documentation usually just says a function returns int or float, not NumPy scalar specifically.

Secondly, KDTree uses `dtype=int` everywhere which results in 64-bit integers on linux but 32-bit integers on windows. Ideally, I'd want to return 64-bit integers (or at least np.intp) on all platforms for consistency and to avoid issues with integer overflow. Again, this is behaviour that isn't documented but code could still be relying on implicitly.

Changing to a NumPy int return type seems fine in this case, especially since it can be considered a bugfix (32-bit int problems seem to come up a lot across SciPy for Windows users).