This was already in my research pile. "Myth #2" there is what I meant about "not treating Python as anything special". The GvR quote is infamous, and seen as short-sighted, but it made sense in context.
The story is often told (though the link doesn't do this) as if the "main" Python community intended to ostracize the PyData folks. But 12 years later there is still much important dialog with them, and NumPy is one of the most commonly downloaded PyPI packages. My discussions on discuss.python.org exposed me to entire websites of analysis of the existing problems (like https://pypackaging-native.github.io/) and people like Henry Schreiner and Ralf Gommers are driving much of the discussion.
> in that non pure Python case, compiler is needed at some point, and that is going to cause problems if you have no control over it. Conda essentially achieve reproducibility, with the necessary compiler considered as part of the dependencies.
This is one of the major differences, yes: Conda has a system for ensuring you have the right compiler. It's hoped that PEP 725 "Specifying external dependencies in pyproject.toml" (https://peps.python.org/pep-0725/) will be a first step towards resolving this in the Pip world, or perhaps towards better interoperation with Conda. (Of course, the hard part is actually using that metadata to install compilers.)