What about migrating numpy-stubs over time to just be a literal stub for numpy's own built-in implications? Once numpy's version is done, a depreciation warming can then be added to numpy-stubs.
On Tue, Mar 24, 2020, 14:15 Eric Wieser <wieser.eric+nu...@gmail.com> wrote: > > Putting > > aside ndarray, as more challenging, even annotations for numpy functions > > and method parameters with built-in types would help, as a start. > > This is a good idea in principle, but one thing concerns me. > > If we add type annotations to numpy, does it become an error to have > numpy-stubs installed? > That is, is this an all-or-nothing thing where as soon as we start, > numpy-stubs becomes unusable? > > Eric > > On Tue, 24 Mar 2020 at 17:28, Roman Yurchak <rth.yurc...@gmail.com> wrote: > >> Thanks for re-starting this discussion, Stephan! I think there is >> definitely significant interest in this topic: >> https://github.com/numpy/numpy/issues/7370 is the issue with the largest >> number of user likes in the issue tracker (FWIW). >> >> Having them in numpy, as opposed to a separate numpy-stubs repository >> would indeed be ideal from a user perspective. When looking into it in >> the past, I was never sure how well in sync numpy-stubs was. Putting >> aside ndarray, as more challenging, even annotations for numpy functions >> and method parameters with built-in types would help, as a start. >> >> To add to the previously listed projects that would benefit from this, >> we are currently considering to start using some (minimal) type >> annotations in scikit-learn. >> >> -- >> Roman Yurchak >> >> On 24/03/2020 18:00, Stephan Hoyer wrote: >> > When we started numpy-stubs [1] a few years ago, putting type >> > annotations in NumPy itself seemed premature. We still supported Python >> > 2, which meant that we would need to use awkward comments for type >> > annotations. >> > >> > Over the past few years, using type annotations has become increasingly >> > popular, even in the scientific Python stack. For example, off-hand I >> > know that at least SciPy, pandas and xarray have at least part of their >> > APIs type annotated. Even without annotations for shapes or dtypes, it >> > would be valuable to have near complete annotations for NumPy, the >> > project at the bottom of the scientific stack. >> > >> > Unfortunately, numpy-stubs never really took off. I can think of a few >> > reasons for that: >> > 1. Missing high level guidance on how to write type annotations, >> > particularly for how (or if) to annotate particularly dynamic parts of >> > NumPy (e.g., consider __array_function__), and whether we should >> > prioritize strictness or faithfulness [2]. >> > 2. We didn't have a good experience for new contributors. Due to the >> > relatively low level of interest in the project, when a contributor >> > would occasionally drop in, I often didn't even notice their PR for a >> > few weeks. >> > 3. Developing type annotations separately from the main codebase makes >> > them a little harder to keep in sync. This means that type annotations >> > couldn't serve their typical purpose of self-documenting code. Part of >> > this may be necessary for NumPy (due to our use of C extensions), but >> > large parts of NumPy's user facing APIs are written in Python. We no >> > longer support Python 2, so at least we no longer need to worry about >> > putting annotations in comments. >> > >> > We eventually could probably use a formal NEP (or several) on how we >> > want to use type annotations in NumPy, but I think a good first step >> > would be to think about how to start moving the annotations from >> > numpy-stubs into numpy proper. >> > >> > Any thoughts? Anyone interested in taking the lead on this? >> > >> > Cheers, >> > Stephan >> > >> > [1] https://github.com/numpy/numpy-stubs >> > [2] https://github.com/numpy/numpy-stubs/issues/12 >> > >> > _______________________________________________ >> > 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 >
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