Re: [Numpy-discussion] start of an array (tensor) and dataframe API standardization initiative

On Wed, Nov 11, 2020 at 10:56 AM Ilhan Polat wrote:

This is great work. Thanks to everyone who contributed. Very clean user-interface too.

One question: Can we propose feature requests already or is that discussion closed?

It's not closed, this is the start of community review so if things are missing or need changing, now is a good time to bring them up - please have a look at CONTRIBUTING.md in the array-api repo. What I would personally expect is that most discussion will be about the bigger picture topics and about the clarity of the document. There may be some individual functions that are important to add, if that's what you have in mind I would recommend looking at some merged PRs to see how the analysis is done (e.g. usage data, comparison between existing libraries). https://github.com/data-apis/array-api/pull/42 is a good example. Cheers, Ralf

On Tue, Nov 10, 2020 at 7:21 PM Ralf Gommers wrote:

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Hi all,

I'd like to share an update on this topic. The draft array API standard is now ready for wider review:

- Blog post: https://data-apis.org/blog/array_api_standard_release - Array API standard document: https://data-apis.github.io/array-api/latest/ - Repo: https://github.com/data-apis/array-api/

It would be great if people - and in particular, NumPy maintainers - could have a look at it and see if that looks sensible from a NumPy perspective and whether the goals and benefits of adopting it are described clearly enough and are compelling.

I'm sure a NEP will be needed for proposing adoption of the standard once it is closer to completion, and work out what that means for interaction with the array protocol NEPs and/or NEP 37, and how an implementation would look. It's a bit early for that now, I'm thinking maybe by the end of the year. Some initial discussion now would be useful though, since it's easier to make changes now rather than when that API standard is already further along.

Cheers, Ralf

On Mon, Aug 17, 2020 at 9:34 PM Ralf Gommers wrote:

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Hi all,

I'd like to share this announcement blog post about the creation of a consortium for array and dataframe API standardization here: https://data-apis.org/blog/announcing_the_consortium/. It's still in the beginning stages, but starting to take shape. We have participation from one or more maintainers of most array and tensor libraries - NumPy, TensorFlow, PyTorch, MXNet, Dask, JAX, Xarray. Stephan Hoyer, Travis Oliphant and myself have been providing input from a NumPy perspective.

The effort is very much related to some of the interoperability work we've been doing in NumPy (e.g. it could provide an answer to what's described in https://numpy.org/neps/nep-0037-array-module.html#requesting-restricted-subs... ).

At this point we're looking for feedback from maintainers at a high level (see the blog post for details).

Also important: the python-record-api tooling and data in its repo has very granular API usage data, of the kind we could really use when making decisions that impact backwards compatibility.

Cheers, Ralf

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