[oefrha]

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.

[1] https://pypi.org/project/scipy/0.10.1/

[2] https://github.com/neonbjb/tortoise-tts/blob/0ea829d37aa6528...

[pmarreck]

> the ecosystem does has a packaging reproducibility and multitenancy problem with out-of-box tooling

this is exactly why I am learning Nix, to help contain chaotically-designed dependency garbage like this to 1 project directory

[bspammer]

Yep nix is awesome at this kind of thing. Check out this project which packages a couple of AI projects with nix, both work out of the box for me.

https://nixified.ai/

[pmarreck]

oh absolutely YES.

Ironically, the poo of things like python multitenant dependency management will likely push Nix adoption forward (and unfortunately also Docker)

[mewpmewp2]

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.