To try and add some more data points to the conversation:
Maybe we can go for a bit more distant name like "numpy.annotations" or whatever.
Interestingly this was proposed independently here: https://github.com/numpy/numpy-stubs/pull/66#issuecomment-619131274 Related to that, Ralf was opposed to numpy.typing because it would shadow a stdlib module name: https://github.com/numpy/numpy-stubs/pull/66#issuecomment-619123629 But, types is _also_ a stdlib module name. Maybe the above points give some extra weight to "numpy.annotations"?
Unless we anticipate adding a long list of type aliases (more than the three suggested so far)
While working on some types in SciPy here: https://github.com/scipy/scipy/pull/11936#discussion_r415280894 we ran into the issue of typing things that are "integer types" or "floating types". For the time being we just inlined a definition like Union[float, np.floating], but conceivably we would want to unify those definitions somewhere instead of redefining them in every project. (Note that existing types like SupportsInt etc. were not what we wanted.) This perhaps suggests that the ultimate number of type aliases might be larger than we initially thought. On Sun, Apr 26, 2020 at 6:25 AM Ilhan Polat <ilhanpolat@gmail.com> wrote:
I agree that parking all these in a secondary namespace sounds a better option, can't say that I feel for the word "typing" though. There are already too many type, dtype, ctypeslib etc. Maybe we can go for a bit more distant name like "numpy.annotations" or whatever.
On Sat, Apr 25, 2020 at 8:51 AM Kevin Sheppard <kevin.k.sheppard@gmail.com> wrote:
Typing is for library developers more than end users. I would also worry that putting it into the top level might discourage other typing classes since it is more difficult to add to the top level than to a lower level module. np.typing seems very clear to me.
On Sat, Apr 25, 2020, 07:41 Stephan Hoyer <shoyer@gmail.com> wrote:
On Fri, Apr 24, 2020 at 11:31 AM Sebastian Berg <sebastian@sipsolutions.net> wrote:
On Fri, 2020-04-24 at 11:10 -0700, Stefan van der Walt wrote:
On Fri, Apr 24, 2020, at 08:45, Joshua Wilson wrote:
But, Stephan pointed out that it might be confusing to users for objects to only exist at typing time, so we came around to the question of whether people are open to the idea of including the type aliases in NumPy itself. Ralf's concrete proposal was to make a module numpy.types (or maybe numpy.typing) to hold the aliases so that they don't pollute the top-level namespace. The module would initially contain the types
That sounds very sensible. Having types available with NumPy should also encourage their use, especially if we can add some documentation around it.
I agree, I might have a small tendency for `numpy.types` if we ever find any usage other than direct typing that may be the better name?
Unless we anticipate adding a long list of type aliases (more than the three suggested so far), I would lean towards adding ArrayLike to the top level NumPy namespace as np.ArrayLike.
Type annotations are becoming an increasingly core part of modern Python code. We should make it easy to appropriately type check functions that act on NumPy arrays, and a top level np.ArrayLike is definitely more convenient than np.types.ArrayLike.
Out of curiousity, I guess `ArrayLike` would be an ABC that a downstream project can register with?
ArrayLike will be a typing Protocol, automatically recognizing attributes like __array__ to indicate that something can be cast to an array.
- Sebastian
Stéfan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion