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

Stephan Hoyer shoyer at gmail.com
Fri Apr 26 11:41:31 EDT 2019

On Fri, Apr 26, 2019 at 3:10 AM Hameer Abbasi <einstein.edison at gmail.com>

> Here’s how `uarray` solves each of these issues:
>    1. Backends… There is no default implementation.
>    2. This is handled by (thread-safe) context managers, which make
>    switching easy.
>    3. There’s one coercion function per type of objec
>       - Libraries are only asked to dispatch over objects they know how
>       to convert, so there’s no backwards-incompatible break when we add dtypes
>       or ufuncs.
>       - Conversion can be as simple as lambda x: x.
>       - There’s a generic dispatcher and reverse dispatcher per function,
>       with “marks” to indicate the type of object.
>    4. Arrays are just one “type” of object you can dispatch over, so
>    there’s no repition by definition.
> Hameer, it's great that you are exploring these problems with a fresh
approach! I'm excited to see how dispatching problems could be solved
without the constraint of compatibility with NumPy's legacy approaches.

When you have a prototype and/or design documents ready for review, please
do share them with the numpy-discussion list. I would be very glad to
review them and share my perspective.

That said, please save it a separate discussion thread, given that the
design of uarray is (wisely) orthogonal to NEP-18.
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