On Wed, Aug 7, 2019 at 5:11 PM Ralf Gommers <ralf.gomm...@gmail.com> wrote:
> > On Mon, Aug 5, 2019 at 6:18 PM Stephan Hoyer <sho...@gmail.com> wrote: > >> On Mon, Aug 5, 2019 at 2:48 PM Ralf Gommers <ralf.gomm...@gmail.com> >> wrote: >> >> >>> 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. >> > > It's not really. We discussed this briefly in the community call today, > Peter said he will try to add some text. > > We should not add new functions to NumPy without indicating who is > supposed to use this, and what need it fills / problem it solves. It seems > pretty clear to me that it's mostly aimed at library authors rather than > end users. And also that mature libraries like SciPy may not immediately > adopt it, because it's too fuzzy - so it's new libraries first, mature > libraries after the dust has settled a bit (I think). > I totally agree -- we definitely should clarify this in the docstring and elsewhere in the docs. An example in the new doc page on "Writing custom array containers" (https://numpy.org/devdocs/user/basics.dispatch.html) would also probably be appropriate. > 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. >> > > There's no need to pronounce a decisive API that fully covers duck array. > Note that RNumPy is an attempt in that direction (not a full one, but way > better than nothing). In the NEP/docs, at least saying something along the > lines of "if you implement this, we recommend the following strategy: check > if a function is present in Dask, CuPy and Sparse. If so, it's reasonable > to expect any duck array to work here. If not, we suggest you indicate in > your docstring what kinds of duck arrays are accepted, or what properties > they need to have". That's a spec by implementation, which is less than > ideal but better than saying nothing. > OK, I agree here as well -- some guidance is better than nothing. Two other minor notes on this NEP, concerning naming: 1. We should have a brief note on why we settled on the name "duck array". Namely, as discussed in NEP-22, we don't love the "duck" jargon, but we couldn't come up with anything better since NumPy already uses "array like" and "any array" for different purposes. 2. The protocol should use *something* more clearly namespaced as NumPy specific than __duckarray__. All the other special protocols NumPy defines start with "__array_". That suggests either __array_duckarray__ (sounds a little redundant) or __numpy_duckarray__ (which I like the look of, but is a different from the existing protocols).
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
