On Fri, Apr 26, 2019 at 1:24 AM Ralf Gommers <ralf.gomm...@gmail.com> wrote:
> Thanks, this helped clarify what's going on here. This example is clear. > The problem seems to be that there's two separate discussions in this > thread: > 1. your original proposal, __numpy_implementation__. it does not have the > problem of your np.concatenate example, as the "numpy implementation" is > exactly the same as it is today. > 2. splitting up the current numpy implementation into *multiple* entry > points. this can be with and without coercion, with and without checking > for invalid values etc. > > So far NEP 18 does (1). Your proposed __numpy_implementation__ addition to > NEP 18 is still (1). Claiming that this affects the situation with respect > to backwards compatibility is incorrect. > > (2) is actually a much more invasive change, and one that does much more > to increase the size of the NumPy API surface. And yes, affects our > backwards compatibility situation as well. > > Also note that these have very different purposes: > (1) was to (quoting from the NEP) "allow using NumPy as a high level API > for efficient multi-dimensional array operations, even with array > implementations that differ greatly from numpy.ndarray." > (2) is for making duck arrays work with numpy implementations of functions > (not just with the NumPy API) > > I think (1) is mostly achieved, and I'm +1 on your NEP addition for that. > (2) is quickly becoming a mess, and I agree with Nathaniel's sentiment > above "I shouldn't expect __array_function__ to be useful for duck > arrays?". For (2) we really need to go back and have a well thought out > design. Hameer's mention of uarray could be that. Growing more __array_*__ > protocols in a band-aid fashion seems unlikely to get us there. > Yes, very well put. I agree, let's try to keep focused on (1) for now. (2) got brought up because of potential confusing about what "__numpy_implementation__" means, but certainly we don't want to figure out those issues now. To that end, I'd love to hear more suggestions for naming what I tentatively called "__numpy_implementation__". I suppose we could always go for "__implementation_used_by_numpy_ndarray_array_function__" ;)
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