On Sat, 2024-10-12 at 12:13 -0400, Marten van Kerkwijk wrote: > Hi Dan, others, >
<snip> > Regardless, since there have been 7 years of > PendingDeprecationWarning, > I think changing that to a regular DeprecationWarning should not > surprise anybody, at least not if they had built a package based on > np.matrix. `PendingDeprecationWarning` is hidden by default for all code, so only "well maintained" libraries are unlikely to have noticed it. I think there are warnings in the docs as well, though. So hopefully, few new code uses it I am very happy to escalate (also to `VisibleDeprecationWarning`), but the question is always how many users are affected by it and how. And I am not that optimistic that it is few enough that we don't have to make dealing with the change easier in some form. > > It is maybe good to add that it is less easy to split of matrix into > its > own package than it was for the financial routines: because matrix > overrides some pretty basic assumptions of arrays (mostly how shapes > behave), there are bits of special-casing for np.matrix throughout > the > rest of the code, which we would want to remove if np.matrix is no > longer part of numpy. I.e., moving it might mean having to define > ``matrix.__array_function__`` and override those functions. This > means a > new package would need a bit of a champion. This actually made me think a bit. We have two options (both need a champion, and I hope we have that here in Dan). An (almost) drop in package may indeed need `__array_function__` because NumPy has a few `matrix` isinstance checks. I am slightly curious what code still uses matrix. If it is just some localized matrix-heavy code, an incredibly light-weight replacement might also serve the purpose well enough? That would never pass `isinstance()` checks in third-party packages, etc. so not sure it can work, though. In any case, overall, I am definitely in favor. The only question is if we have to go to the trouble to create a drop-in replacement. And for that it would be nice if we can see how easy that is, because while tedious, it may not be all that hard. - Sebastian > > All the best, > > Marten > _______________________________________________ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: sebast...@sipsolutions.net > _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
