Re: [Numpy-discussion] Stricter numpydoc validation

[Eric Larson]

I have written and/or used something like this (though not nearly as
complete!) in several other projects. It would be great to have one
maintained source for such a checker, and numpydoc seems like a reasonable
place for it.

The one thing I worry about is maintenance burden, where numpydoc is
already spread a little bit thin -- would any of the Pandas developers be
willing to maintain it?

Eric


On Tue, Jul 16, 2019 at 6:56 AM Marc Garcia  wrote:

> In pandas we've been, for more than a year now, enforcing a stricter
> numpydoc standard. And we've got a script to help with it, which validates
> things like capitalization and punctuation of paragraphs, the documented
> parameters (they must match the ones in the signature, have both a type and
> a description...), PEP-8 of the standards, and many more things, so all our
> docstrings are consistent.
>
> I saw that there is an issue with a discussion on having a more strict
> standard for numpydoc, I added a comment there on whether would make sense
> to move the pandas standard and validation code to numpydoc:
> https://github.com/numpy/numpydoc/issues/213#issuecomment-511760580
>
> I think it's worth opening the discussion here too. Is there interest in
> the rest of the community on having a stricter standard, and move the
> pandas validation (with the required updates) to numpydoc? Of course we can
> discuss also the exact standard, but probably worth finding out first if a
> stricter numpydoc standard would make sense for everyone.
>
> You can find the documentation of our standard at:
> https://dev.pandas.io/development/contributing_docstring.html
>
> And the script that we use to validate, as well as the exact list of
> errors we detect in:
> https://github.com/pandas-dev/pandas/blob/master/scripts/validate_docstrings.py#L76
>
> Cheers!
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Re: [Numpy-discussion] manylinux wheels with Github Actions

[Eric Larson]

I have had good experiences for about a year now using CIBUILDWHEEL
 on Azure for VisPy
 and on
python-rtmixer

to
deploy Linux, Windows, and macOS wheels to PyPi automatically when a
release is tagged. It wasn't difficult to set up rtmixer after David Hoese
did the heavy lifting sorting out everything with VisPy.

I haven't used other methods so I can't really offer any comparison, but
the overhead for those two fairly simple (from a build-and-deploy
perspective) projects at least has seemed pretty low.

My 2c,
Eric

On Mon, Nov 16, 2020 at 12:27 PM Robert McLeod  wrote:

> Everyone,
>
> I'm looking to move `numexpr` into GitHub Actions for the combination of
> testing but also building wheels for deployment to pypi. I've never really
> been satisfied with the Appveyor/Travis combo and the documentation around
> Actions seems to be a lot stronger. I thought I might ask for advice on the
> mailing list before I jump in.
>
> Does anyone here know of good, working examples of such for scientific
> packages that I could crib as a guide? I would want/need to make use of
> manylinux1 Docker images for building Linux wheels.
>
> https://github.com/pypa/manylinux
>
> This is an example recipe that builds Cython using a custom Docker image.
> It's a nice starting point but it would be preferable to use the official
> pypa images.
>
> https://github.com/marketplace/actions/python-wheels-manylinux-build
> Kivy is a working example with a pretty complete test and build setup
> (although it's a bit over complicated for my purposes):
>
> https://github.com/kivy/kivy/tree/master/.github/workflows
>
> Anyone have any experiences to share with test and deploy via Actions?
> Robert
>
> --
> Robert McLeod
> robbmcl...@gmail.com
> robert.mcl...@hitachi-hhtc.ca
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