That has nothing to do with Python tooling being bad. A safe assumption is that Python package managers are being developed by developers, who have no excuse.

If a C++ codebase developed by scientists had null pointer exceptions in it, then I could excuse things. But if the C++ compiler itself introduced unforced null pointer errors, then it absolutely deserves criticism.

It shouldn't be possible for a ML researcher to use Conda or whatever package manager in a way that despite using a formally specified "requirements.txt", it won't build a week later because of how loose the specification of module versions is allowed to be.

The Python attitude and more specifically Conda is at fault here, not the ML researching trying to get his job done.