Oh I don't disagree, the ecosystem does has a packaging reproducibility and multitenancy problem with out-of-box tooling, and projects seldom provide basic instructions for people outside the ecosystem, like using a virtual env.
That said, this tortoise-tts project might be a particularly bad example. It somehow locks to scipy 0.10.1 from 2012 [1] (during the Python 3.2 release cycle, when Python 3 was heavily in flux) in requirements.txt [2]. Probably not terribly surprising it doesn't work. I didn't bother to look into why they lock to that.
I think I personally keep running into these bad examples every time I use something with Python and I do use venv every time. Rarely something works out of the box. Even colabs I try somehow won't work after a while. There is always some sort of version mismatch, sometimes something like numpy, tensorflow and some other deps.
That said, this tortoise-tts project might be a particularly bad example. It somehow locks to scipy 0.10.1 from 2012 [1] (during the Python 3.2 release cycle, when Python 3 was heavily in flux) in requirements.txt [2]. Probably not terribly surprising it doesn't work. I didn't bother to look into why they lock to that.
[1] https://pypi.org/project/scipy/0.10.1/
[2] https://github.com/neonbjb/tortoise-tts/blob/0ea829d37aa6528...