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pyreadstat_wheels3

Wheels for pyreadstat

This is a repo building wheels for pyreadstat using the multibuild package. It is a modification from the older repo https://github.com/ofajardo/pyreadstat_wheels2. The main modification respect to the old one is that here we use azure to build linux and mac instead of Travis. Numpy wheels was taking as model for building the azure-pipelines.yml and azure templates, see here

Wheels are uploaded to Anaconda Cloud. In order to do that a anaconda cloud account had to be set and the token retrived via WEB UI (also possible with CLI), set the Token in Azure and APPVEYOR as secret environment variable for the project, and then just upload the wheels using the Anaconda-client in azure-pipelines.yml and appveyor.yml.

The wheels are then visible in https://anaconda.org/ofajardo/pyreadstat/files

Also, in appveyor we are building using MINGW with anaconda insetead of MVSC because readstat cannot be built with MVSC at the moment.

######################################## Building and uploading pyreadstat wheels ########################################

We automate wheel building using this custom github repository that builds on the azure-pipelines OSX machines, azure-pipelines Linux machines, and the Appveyor VMs.

How it works

The wheel-building repository:

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.

Triggering a build

You will likely want to edit the azure-pipelines.yml and appveyor.yml files to specify the BUILD_COMMIT before triggering a build - see below.

You can trigger a build by:

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.

Which pyreadstat commit does the repository build?

The pyreadstat-wheels repository will build the commit specified in the BUILD_COMMIT at the top of the azure-pipelines.yml and appveyor.yml files. This can be any naming of a commit, including branch name, tag name or commit hash.

Note: when making a release, it's best to only push the commit (not the tag) of the release to the pyreadstat 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.

Uploading the built wheels to pypi

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 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 <bs4>_.

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=0.2.0
CDN_URL=https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com
wheel-uploader -u $CDN_URL -s -v -w ~/wheelhouse -t all pyreadstat $VERSION

where:

pyreadstat is the root name of the wheel(s) to download / upload, and 0.2.0 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 pyreadstat-0.2.0- 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.

.. _manylinux1: https://www.python.org/dev/peps/pep-0513 .. _twine: https://pypi.python.org/pypi/twine .. _bs4: https://pypi.python.org/pypi/beautifulsoup4 .. _delocate: https://pypi.python.org/pypi/delocate .. _auditwheel: https://pypi.python.org/pypi/auditwheel