The Docker images should generalize and facitlitate the often complicated creation of python wheels especially if they have complicated dependecies or binary dependencies e.g numpy.
First the build base image needs to be created with the manylinux-base base image.
cd manylinux_base/
docker build -t manylinux-base .
Second run the image and provide the name of the package to be build as a parameter. This only works if no further binary dependencies are needed. (Alternative see at the end)
docker run --rm -v /opt/wheel_build/output:/wheelhouse manylinux-base numpy
Alternative: Work with the specific images tailored for the desired python package, e.g. ta-lib. Can be used without any parameters if nothing special is required. Will build a wheel of the python package and audit it to the most recent manylinux definition.
cd packages/ta-lib/
docker build -t build/ta-lib .
docker run --rm -v /opt/wheel_build/output:/wheelhouse build/ta-lib
Options to run specialized containers are:
-t linux_armv7l specify the target platform other than the default of auditwheel.
-p 311 specify the desired python version, e.g. 310, 311
ta-lib provide the package name to be build.
0.4.25 (optional): provide a specific version to be build.
docker run --rm -v /opt/wheel_build/output:wheelhouse build/ta-lib -t linux_armv7l ta-lib 0.4.25
If a build fails try to change the target platform via -t to the less compatible linux_armv7l. This usually works but makes the wheel less portable.
For debugging purposes omit the --rm flag during build and open the container afterwards in interactive mode.