setuptools VS Python-docker

To be fair, that seems to have been a 2 year warning:

https://github.com/pypa/setuptools/commit/3544de73b3662a27fa...

There was/is some discussion in setuptools about how to normalize the tarball (https://github.com/pypa/setuptools/issues/2133#issuecomment-...) coudl something similar be applied to Building Python itself ?

❯ yay -Sy python-setuptools python-jaraco.text ❯ pip show setuptools Name: setuptools Version: 67.7.0 Summary: Easily download, build, install, upgrade, and uninstall Python packages Home-page: https://github.com/pypa/setuptools Author: Python Packaging Authority Author-email: [email protected] License: Location: /usr/lib/python3.11/site-packages Requires: jaraco.text, more-itertools, ordered-set, packaging, platformdirs, tomli, validate-pyproject Required-by: Cerberus, fs, httpie, input-remapper, pecan, pycountry, python-lsp-server, reuse, setuptools-scm, zc.lockfile

Link: https://github.com/pypa/setuptools/issues/3772

For example, when it comes to Python, one option is to use the same packaging system that a huge number of open-source libraries and tools are published with. You can use setuptools or Hatch to build a "packaged" version of your code, and publish it to either the public PyPi repository or an internal one that you set up. Then your users can use pip to install your package, automatically fetch its dependencies, and keep it up to date, just like any other Python module.

You could maybe make it a click Application, and use setuptools.

Not sure how advisable it is to depend on setup.py given the setuptools team has very clearly stated that they are not interested in supporting any cli commands anymore including setup.py install. Relavant PR

This defines which image to inherit from, In this case we are using a Python image with the Python 3.11 version running on a slim version of the Bookwork version of Debian linux. Image definitions can be viewed from the DockerHub TAG link such as the python:3.11-slim-bookworm and official images like this one typically have pretty complicated definitions in order to get them highly optimized.

> You are going to eventually run into the same issue most people trying to use Alpine Linux just because of simplicity and being lightweight run: musl is not a completely ABI-compatible seamless replacement to glibc and might cause issue with statically linked binaries, and other annoying issues you won't foresee.

Well, if all you need is the server to run Docker/Podman, SSH and some other limited amount of packages, it shouldn't be too bad. Of course, there are also horror stories of Alpine resulting in way worse performance in select use cases: https://github.com/docker-library/python/issues/509 and there's the fact that Alpine might be popular inside of containers, but way less so outside.

Also, because of the short EOL cycle, I personally ditched Debian on servers (and Alpine in containers) myself for Ubuntu everywhere: https://blog.kronis.dev/articles/using-ubuntu-as-the-base-fo... A bit of a polarizing move (though RPM distros aren't much better at the moment), but it seems to have worked out for me in the end.

Doesn't mean that someone can't try, though, maybe their use case is suitable for Alpine.

This is the actual raw Dockerfile: https://github.com/docker-library/python/blob/master/3.9/slim-bullseye/Dockerfile

I usually cannibalize Docker Community's examples: Here

Official Docker image of Python 3.10.5-slim

If you want Python v3.7, perhaps try FROM python:3.7 (link)

Navigate into the Python directory and configure and ensure enable-optimization option is added as shown in the command below.

It looks like you are running into this bug: https://github.com/docker-library/python/issues/674