We automate wheel building using this custom github repository that builds on the travis-ci OSX machines and the travis-ci Linux machines.
The travis-ci interface for the builds is https://travis-ci.org/MacPython/scipy-wheels
Appveyor interface at https://ci.appveyor.com/project/scipy/scipy-wheels
The driving github repository is https://github.com/MacPython/scipy-wheels
There are two important branches:
master
- for building releases;daily
- for daily builds.
Travis-CI builds the daily
branch - er - daily, via a Travis-CI cron job to check that we can build
against current Scipy master. When trying to fix builds against master, or
developing new CI build machinery, please use the daily
branch.
Builds from the daily
branch upload to a Rackspace container for
pre-releases at
https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com
Meanwhile, we usually leave the master
branch in a state where it can
build the last release.
Builds from the master
branch upload to a Rackspace container for releases
at
https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com
Before releasing, we merge ``daily`` into ``master``.
Therefore, you will usually want to submit pull requests to the daily
branch, for testing.
The wheel-building repository:
- does a fresh build of any required C / C++ libraries;
- builds a scipy wheel, linking against these fresh builds;
- processes the wheel using delocate (OSX) or auditwheel
repair
(Manylinux1).delocate
andauditwheel
copy the required dynamic libraries into the wheel and relinks the extension modules against the copied libraries; - uploads the built wheels to a Rackspace container - see "Using the repository" above. The containers were kindly donated by Rackspace to scikit-learn).
The resulting wheels are therefore self-contained and do not need any external dynamic libraries apart from those provided as standard by OSX / Linux as defined by the manylinux1 standard.
The .travis.yml
file in this repository has a line containing the API key
for the Rackspace container encrypted with an RSA key that is unique to the
repository - see https://docs.travis-ci.com/user/encryption-keys. This
encrypted key gives the travis build permission to upload to the Rackspace
containers we use to house the uploads.
You will likely want to edit the .travis.yml
and appveyor.yml
files to
specify the BUILD_COMMIT
before triggering a build - see below.
You will need write permission to the github repository to trigger new builds on the travis-ci interface. Contact us on the mailing list if you need this.
You can trigger a build by:
- making a commit to the scipy-wheels repository (e.g. with git commit --allow-empty); or
- clicking on the circular arrow icon towards the top right of the travis-ci page, to rerun the previous build.
In general, it is better to trigger a build with a commit, because this makes a new set of build products and logs, keeping the old ones for reference. Keeping the old build logs helps us keep track of previous problems and successful builds.
The scipy-wheels repository will build the commit specified in the
BUILD_COMMIT
at the top of the .travis.yml
file and appveyor.yml
files. This can be any naming of a commit, including branch name, tag name or
commit hash.
Note: when making a SciPy release, it's best to only push the commit (not the
tag) of the release to the scipy
repo, then change BUILD_COMMIT
to the
commit hash, and only after all wheel builds completed successfully push the
release tag to the repo. This avoids having to move or delete the tag in case
of an unexpected build/test issue.
- pre-releases container visible at https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com
- release container visible at https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com
Be careful, these links point to containers on a distributed content delivery network. It can take up to 15 minutes for the new wheel file to get updated into the containers at the links above.
When the wheels are updated, you can download them to your machine manually, and then upload them manually to pypi, or by using twine. You can also use a script for doing this, housed at : https://github.com/MacPython/terryfy/blob/master/wheel-uploader
For the wheel-uploader
script, you'll need twine and beautiful soup 4.
You will typically have a directory on your machine where you store wheels, called a wheelhouse. The typical call for wheel-uploader would then be something like:
VERSION=0.18.0 CDN_URL=https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com wheel-uploader -u $CDN_URL -s -v -w ~/wheelhouse -t all scipy $VERSION
where:
-u
gives the URL from which to fetch the wheels, here the https address, for some extra security;-s
causes twine to sign the wheels with your GPG key;-v
means give verbose messages;-w ~/wheelhouse
means download the wheels from to the local directory~/wheelhouse
.
scipy
is the root name of the wheel(s) to download / upload, and
0.18.0
is the version to download / upload.
In order to upload the wheels, you will need something like this
in your ~/.pypirc
file:
[distutils] index-servers = pypi [pypi] username:your_user_name password:your_password
So, in this case, wheel-uploader will download all wheels starting with
scipy-0.18.0- from the URL in $CDN_URL
above to ~/wheelhouse
, then
upload them to PyPI.
Of course, you will need permissions to upload to PyPI, for this to work.