MANYLINUX.md

Install docker.

Get the manylinux docker environment. At the time of this writing, manylinux1 is compatible; however, I used manylinx2014. There is a tool which will label the manylinux binary with the oldest compatible standard.

docker pull quay.io/pypa/manylinux2014_x86_64

Run an interactive bash shell in the manylinux docker environment.

docker run -it quay.io/pypa/manylinux2014_x86_64 /bin/bash

Inside the interactive bash shell for the docker environment, download lie_learn and change to the source directory.

git clone https://github.com/AMLab-Amsterdam/lie_learn.git
cd lie_learn

Create wheels. You have to determine which versions of python are appropriate.

/opt/python/cp35-cp35m/bin/python setup.py bdist_wheel
/opt/python/cp36-cp36m/bin/python setup.py bdist_wheel
/opt/python/cp37-cp37m/bin/python setup.py bdist_wheel
/opt/python/cp38-cp38/bin/python setup.py bdist_wheel

Use auditwheel to check for success and modify the binaries to be labeled with the oldest compatible standard (lowest priority).

auditwheel repair ./dist/lie_learn-0.0.1.post1-cp35-cp35m-linux_x86_64.whl -w ./manylinux
auditwheel repair ./dist/lie_learn-0.0.1.post1-cp36-cp36m-linux_x86_64.whl -w ./manylinux
auditwheel repair ./dist/lie_learn-0.0.1.post1-cp37-cp37m-linux_x86_64.whl -w ./manylinux
auditwheel repair ./dist/lie_learn-0.0.1.post1-cp38-cp38-linux_x86_64.whl -w ./manylinux

Open a new terminal window (host environment) and get the running docker CONTAINER ID.

docker ps

yields

CONTAINER ID        IMAGE                               COMMAND             CREATED             STATUS              PORTS               NAMES
8e2b2c3baa8e        quay.io/pypa/manylinux2014_x86_64   "/bin/bash"         30 minutes ago      Up 30 minutes                           charming_shannon

In my case, the CONTAINER ID is 8e2b2c3baa8e. In the new terminal window, copy the manylinux wheels from the running container to a folder you'll remember.

mkdir ~/manylinux
docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp35-cp35m-manylinux1_x86_64.whl ~/manylinux/
docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp36-cp36m-manylinux1_x86_64.whl ~/manylinux/
docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp37-cp37m-manylinux1_x86_64.whl ~/manylinux/
docker cp 8e2b2c3baa8e:/lie_learn/manylinux/lie_learn-0.0.1.post1-cp38-cp38-manylinux1_x86_64.whl ~/manylinux/

First do a test by uploading to test pypi.

twine upload --repository-url https://test.pypi.org/legacy/ ~/manylinux/*

Try downloading and testing lie_learn from there before proceeding. This is easier said than done. You will need to download all of the dependencies manually then download from test pypi without any dependencies using pip install --no-cache-dir --index-url https://test.pypi.org/simple/ --no-deps lie_learn.

Once you know it's working, upload the wheels to pypi with twine.

twine upload ~/manylinux/*

For a bit more info, another useful resource is https://opensource.com/article/19/2/manylinux-python-wheels.