self-contained-runnable-py VS flit

The approach I prefer is to not mess with setuptools etc at all in the first place, and simply make a nice executable package.

e.g. https://github.com/tpapastylianou/self-contained-runnable-py...

The title should be: How to create a "Python DISTRIBUTION package".

The term "python package" means something entirely different (or at the very least is ambiguous in a pypi/distribution context).

To add to the confusion, creating a totally normal, runnable python package in a manner that makes it completely self-contained such that it can be "distributed" in a standalone manner, while still being a totally normal boring python package, is also totally possible (if not preferred, in my view).

Shameless plug: https://github.com/tpapastylianou/self-contained-runnable-py...

Shameless plug: I use my own template, which organises things as runnable projects.

https://github.com/tpapastylianou/self-contained-runnable-py...

It serves my purposes very well (which is creating projects that represent standalone experiments).

Sharing in case someone else here finds it useful.

More recently I've modified this a bit to also generate nice html reports straight from the __main__.py file, independently of the underlying python code, and use this as lab books (where each lab book contains a single analysis and its report). I'll upload this template separately when I find the time.

Queries on https://github.com/pypa/flit/tree/main/flit_core/flit_core (omitted tests/)

(Pdb) print(indexer.query("def normalize_dist_name(name: str, version: str) -> str:"))

If it's pure Python, the only packaging file you need is `pyproject.toml`. You can fill that file with packaging metadata per PEP 518 and PEP 621, including using modern build tooling like flit[1] for the build backend and build[2] for the frontend.

With that, you entire package build (for all distribution types) should be reducible to `python -m build`. Here's an example of a full project doing everything with just `pyproject.toml`[3] (FD: my project).

[1]: https://github.com/pypa/flit

[2]: https://github.com/pypa/build

[3]: https://github.com/pypa/pip-audit

I published a very simple project flit_pytest_circleci_template that uses: * [flit](https://github.com/pypa/flit) to build a package. * pytest to test it * circleci to run the above and publish the package to pypi whenever a source file is committed. This is the hard part IMO as I do not know circleci well (and didn't know it at all when I started this project).

flit

I hadn't heard of flit, it does seem like it's not brand new on the scene, however it is primarily a single contributor:

https://github.com/takluyver/flit/graphs/contributors

With a title like this, I'd be expecting to see an article describing the latest tools and recommendations from the PyPA.