Sure, I wouldn't mind doing that, but it would also be better to have clear alternative/complement to duck array (as I'm hoping to be the case with with coerce). I will try to give a bit more thought on the coercion ideas and start writing a NEP for that this week and the next. Perhaps we can then sync both NEPs.
On Tue, Aug 6, 2019 at 4:23 PM Sebastian Berg <sebast...@sipsolutions.net> wrote: > > On Tue, 2019-08-06 at 10:24 +0200, Peter Andreas Entschev wrote: > > Thanks for the concerns raised, and Stephan for promptly answering > > them. > > > > > An alternative to introducing np.duckarray() would be to just > > > modify np.asarray(). Of course this has backwards compatibility > > > impact, but if you're going to be raising a TypeError from > > > __array__ then that impact is there anyway. Note: I don't think > > > this is necessarily a better idea, because it may lead to less > > > clear errors, but it's worth putting in the alternatives section at > > > least. > > > > I don't know if mentioning alternatives in that way is good, it gives > > me the impression that NumPy is encouraging them (unless it really > > is). > > Well, if you think alternatives is too open to actually using them, I > think it would be fine to list them as "Rejected Alternatives"? > > - Sebastian > > > > In that sense, I think the best is indeed going down the path of > > finding a good coercion solution (as Stephan already mentioned) and > > later we could just add a pointer to the new NEP in this one. > > > > Best, > > Peter > > > > > > On Tue, Aug 6, 2019 at 3:17 AM Stephan Hoyer <sho...@gmail.com> > > wrote: > > > On Mon, Aug 5, 2019 at 2:48 PM Ralf Gommers <ralf.gomm...@gmail.com > > > > wrote: > > > > Having __array__ give a TypeError is fine for libraries that want > > > > to prevent unintentional coercion with, e.g., > > > > `np.asarray(my_ducktype)`. However that leaves the obvious > > > > question of what the right way is to do this intentionally. Would > > > > be good to recommend something, for example a `numpy()` or > > > > `to_numpy()` method. Also, the NEP should make it clearer that > > > > this is not the obviously correct thing to do, it only makes > > > > sense in cases where coercion is very expensive, like CuPy and > > > > Sparse. For Dask for example, coercion to a numpy array is > > > > perfectly reasonable. > > > > > > I agree, we need another solution for explicit array conversion, > > > either from duck arrays to NumPy arrays or between duck arrays. > > > > > > As has come-up on GitHub [1], think this should probably be another > > > protocol, to allow for third-party conversions like sparse <-> dask > > > that in principle could be implemented by either library. > > > > > > To get discussion start, here's one possible proposal for what the > > > NumPy API(s) could look like: > > > np.coerce(sparse_array) # by default, coerce to np.ndarray > > > np.coerce(sparse_array, dask.array.Array) # coerces to dask > > > np.coerce_like(sparse_array, dask_array) # coerce like the second > > > array type > > > np.coerce_arrays(list_of_arrays) # coerce to first type that can > > > handle everything > > > > > > The protocol itself should probably either use __array_function__ > > > (e.g., for np.coerce_like, if all the dispatched on arguments are > > > arrays) or a custom protocol in the same style that allows for > > > implementations on either the array being converted or the type of > > > the result [2]. > > > > > > [1] https://github.com/numpy/numpy/issues/13831 > > > [2] > > > https://github.com/numpy/numpy/pull/14170#issuecomment-517004293 > > > > > > > The NEP currently does not say who this is meant for. Would you > > > > expect libraries like SciPy to adopt it for example? > > > > > > > > The NEP also (understandably) punts on the question of when > > > > something is a valid duck array. If you want this to be widely > > > > used, that will need an answer or at least some rough guidance > > > > though. For example, we would expect a duck array to have a > > > > mean() method, but probably not a ptp() method. A library author > > > > who wants to use np.duckarray() needs to know, because she can't > > > > test with all existing and future duck array implementations. > > > > > > I think this is covered in NEP-22 already. As discussed there, I > > > don't think NumPy is in a good position to pronounce decisive APIs > > > at this time. I would welcome efforts to try, but I don't think > > > that's essential for now. > > > > > > > An alternative to introducing np.duckarray() would be to just > > > > modify np.asarray(). Of course this has backwards compatibility > > > > impact, but if you're going to be raising a TypeError from > > > > __array__ then that impact is there anyway. Note: I don't think > > > > this is necessarily a better idea, because it may lead to less > > > > clear errors, but it's worth putting in the alternatives section > > > > at least. > > > > > > > > Cheers, > > > > Ralf > > > > > > > > > > Would be great to get some comments on that. > > > > > > > > > > [1] > > > > > https://github.com/numpy/numpy/blob/master/doc/neps/nep-0030-duck-array-protocol.rst > > > > > [2] https://github.com/numpy/numpy/pull/14170 > > > > > [3] > > > > > https://numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html > > > > > > > > > > Best, > > > > > Peter > > > > > _______________________________________________ > > > > > 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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
