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

[Ralf Gommers]

On Wed, Nov 11, 2020 at 12:15 PM YueCompl <compl.yue at icloud.com> wrote:

> This is great!
>
> I'm working on some Haskell based mmap shared array lib, with Python like
> surface language API. I would adhere to such standard very willingly.
>

Awesome. Library authors from other languages is definitely something else
we had in mind, so glad to hear it's helpful.

A quick skim but I can't find dataframe related info, that's scheduled for
> the future? Will take Pandas as primary reference?
>

Yes, that is planned but will take a while longer. Dataframes are less
mature, and Pandas itself is still very much in flux (the first proposal
after the 1.0 release was "let's deprecate <stuff> for 2.0", so it's a more
complex puzzle. Pandas is an important reference, but I'd expect the end
result to deviate more from Pandas than the array API differs from NumPy.

Cheers,
Ralf



> Thanks with best regards,
> Compl
>
>
> On 2020-11-11, at 02:19, Ralf Gommers <ralf.gommers at gmail.com> wrote:
>
> 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 <ralf.gommers at gmail.com>
> wrote:
>
>> 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-subsets-of-numpy-s-api
>> ).
>>
>> 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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