[Numpy-discussion] Adding to the non-dispatched implementation of NumPy methods

Hameer Abbasi einstein.edison at gmail.com
Sun Apr 28 16:51:16 EDT 2019

Hey Stephan,

After some discussion with Ralf, I feel that the best way forward would be to add the __numpy_implementation__ (which is my preferred name for it). While I consider the interface final (or at least to the point where we would only add functionality and not remove it), I would prefer to keep the experimental tag, for this very reason: Avoiding having to write a new NEP for adding functionality.

However, I’m open to declaring it non-experimental it as well.

Best Regards,
Hameer Abbasi

> On Sunday, Apr 28, 2019 at 5:50 AM, Stephan Hoyer <shoyer at gmail.com (mailto:shoyer at gmail.com)> wrote:
> On Sat, Apr 27, 2019 at 4:39 PM Hameer Abbasi <einstein.edison at gmail.com (mailto:einstein.edison at gmail.com)> wrote:
> > > On Saturday, Apr 27, 2019 at 6:21 PM, Stephan Hoyer <shoyer at gmail.com (mailto:shoyer at gmail.com)> wrote:
> > > Are there aspects of your uarray proposal that are relevant to the current proposed revisions to NEP 18? If so, please restate them :).
> > >
> > >
> > >
> > >
> >
> >
> > Of course, here’s my proposal:
> >
> > We leave NEP-18 as-is for now, and instead of writing separate protocols for coercion, dtypes and ufuncs (which will be needed somewhere down the line), we have a discussion about uarray and see if it can help there. :-)
> I don't want to add separate protocols for coercion, dtypes or ufuncs as part of NEP-18. Whatever form these should take, they should definitely be a separate proposals.
> __array_function__ is not the end of the story about duck array support in NumPy, but I think it's valuable incremental step, as evidenced by the projects that are already eager to adopt it. I would really, really like to try to get a usable and near-final version of it released in NumPy 1.17. That doesn't leave us much time.
> I've very interested in your work on uarray, but as far as I can tell, it would not directly interact with NumPy's implementation of __array_function__, so discussing it doesn't feel immediately urgent to me. Rather, it's an alternative and possibly more complete solution for some of the same problems. That's fantastic -- but please, let us finish __array_function__ first. _______________________________________________
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