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.
A quick skim but I can't find dataframe related info, that's scheduled for the future? Will take Pandas as primary reference? Thanks with best regards, Compl > On 2020-11-11, at 02:19, Ralf Gommers <ralf.gomm...@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 > <https://data-apis.org/blog/array_api_standard_release/> > - Array API standard document: https://data-apis.github.io/array-api/latest/ > <https://data-apis.github.io/array-api/latest/> > - Repo: https://github.com/data-apis/array-api/ > <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.gomm...@gmail.com > <mailto:ralf.gomm...@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/ > <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 > > <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 > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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