[Numpy-discussion] Type annotations for NumPy
Robert T. McGibbon
rmcgibbo at gmail.com
Tue Nov 28 12:09:31 EST 2017
I'm strongly in support of this proposal. Type annotations have really
helped me write more correct code.
I started working on numpy type stubs a few months ago. I needed a mypy
plugin to support shape-aware functions. Those whole thing is pretty
tricky. Still very WIP, but I'll clean them up a little bit and opensource
On Sun, Nov 26, 2017 at 1:58 PM, Stephan Hoyer <shoyer at gmail.com> wrote:
> On Sat, Nov 25, 2017 at 3:34 PM Matthew Rocklin <mrocklin at gmail.com>
>> Thoughts on basing this on a more generic Array type rather than the
>> np.ndarray? I can imagine other nd-array libraries (XArray, Tensorflow,
>> Dask.array) wanting to reuse this work. For dask.array in particular we
>> would want to copy this entirely, but we probably can't specify that
>> dask.arrays are np.ndarrays. It would be nice to ensure that the container
>> type was swappable.
> Yes, absolutely. I do briefly mention this in my longer doc (see the
> "Syntax" section). This is also one of my personal goals for this project.
> This will be most relevant when we start working on typing support for
> array shapes and broadcasting: details like data types can be more library
> specific, and can probably be expressed with the existing generics system
> in the typing module.
> After we do some experimentation to figure out appropriate syntax and
> semantics for array shape typing, I would like to standardize the rules for
> typing multi-dimensional arrays in Python. This will probably entail
> writing a PEP, so we can add appropriate base classes in the typing module.
> I view this as the natural complement to existing standard library features
> that make it easier to interchange between multiple multi-dimensional array
> libraries, such as memory views and the buffer protocol.
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