[Numpy-discussion] manylinux wheels with Github Actions

[Robert McLeod]

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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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
> ___
> NumPy-Discussion mailing list
> NumPy-Discussion@python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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Re: [Numpy-discussion] manylinux wheels with Github Actions

[Andrew Nelson]

For my project (refnx) I solely use GH Actions to test and make wheels. In
my workflow (
https://github.com/refnx/refnx/blob/master/.github/workflows/pythonpackage.yml)
I make a 3.7/3.8/3.9 matrix across Linux/macOS/Windows. First of all I make
the wheels for all those combos, then install the wheels, then run tests on
the installed wheel (thereby checking that the libraries are all delocated
nicely). The final step in the workflow is uploading the wheel artefacts
(stored somewhere on GH).
To make the Linux 2010/2014 wheels I use PyPA docker images (
https://github.com/refnx/refnx/blob/master/.github/workflows/pythonpackage.yml#L70).
I specify what platform I want to make wheels for, as an environment
variable that is used to select the correct docker image
["manylinux2010_x86_64", "manylinux2014_x86_64"]. There are other images
available. The docker image runs a script to make all the wheels (
https://github.com/refnx/refnx/blob/master/tools/build_manylinux_wheels.sh)
and put them in a wheelhouse, that is then uploaded as an artefact along
with the macOS and windows wheels.

I decided to make the deployment step to PyPI a manual process, just so I
can check that everything went ok. When I've just made a release tag I
download the artefacts corresponding to the release commit, then upload
them from my personal PC.

It all works really well.
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