Pyenv – lets you easily switch between multiple versions of Python
1–10 of 341 posts
Re: Pyenv – lets you easily switch between multiple versions of Python
#2Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning stack up and running was really tough.
Re: Pyenv – lets you easily switch between multiple versions of Python
#3OP - I'm curious why you've submitted this today, you seem experienced enough to guess this is not the first time you've used it. Has there been a major change or something happened in the community I need to know about? Or are you just spreading the love for a great piece of open source software?
Re: Pyenv – lets you easily switch between multiple versions of Python
#4Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning s…
uv has been really awesome as a replacement for pip:
https://github.com/astral-sh/uv
So fast it finally made virtual environments usable for me. But it's not (yet) a full replacement for conda, e.g. it won't install things outside of Python packages
Re: Pyenv – lets you easily switch between multiple versions of Python
#5I have to warn again users that think they have found the silver bullet that pyenv comes with a big caveat: it compiles python on your machine.
The number of possible modes of failure in this situation is huge.
See also: "Why not tell people to "simply" use pyenv, poetry or anaconda"
https://www.bitecode.dev/p/why-not-tell-people-to-simply-use
I'm not saying pyenv is not a useful tool, but it is not a tool for beginners fighting with python packaging problems. It's a specialist tool to normalize your setup.
Very often, I see people tell me they don't have problems with pyenv, but later on have other unrelated problems with their dependencies. Analysis then prove it was because of pyenv, they just didn't know it. The cost is not obvious.
Re: Pyenv – lets you easily switch between multiple versions of Python
#6Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning s…
I use poetry and direnv. Coming from node/npm, it feels natural for me to just do this. I have really no troubles of installing Pytorch with poetry
Re: Pyenv – lets you easily switch between multiple versions of Python
#7Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning s…
For anything related to CUDA/CuDNN, use one of NVIDIA base Docker images. Then whether you use Conda / Pip / Poetry / Pipenv does not matter much. Not at all a Conda fan myself and avoid it like the plague
Re: Pyenv – lets you easily switch between multiple versions of Python
#8Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning s…
uv has been really awesome as a replacement for pip: https://github.com/astral-sh/uv So fast it finally made virtual environments usable for me. But it's not (yet) a full replacement for conda, e.g. it won't install things outside of Python packages
How about prefix then?
https://prefix.dev/blog/uv_in_pixi
Re: Pyenv – lets you easily switch between multiple versions of Python
#9Is anyone is the AI/ML area finding success with anything other than conda, where installation of CUDA/CUDnn is required? Although I often have to pip install a lot of packages, I find conda's nvidia/pytorch/conda-forge channels are still by far the easiest way to get a deep learning stack up and running, and so I just stick with conda environments. I've tried poetry in the past but getting the NVidia deep learning s…
Yes. I simply do
python -m pip install torch torchvision
There's a very good chance I've installed cuda on my system before this though. And usually cudnn and some other packages because this is part of my standard install. And then I also never run into the issue where a package is looking for nvcc.
Re: Pyenv – lets you easily switch between multiple versions of Python
#10Homebrew really bugs me. The devs want you to use the most current version of Python. Except the requirement is set at the package level and there's no enforcement. So you just keep getting python versions installed.
I don't get why you just don't set a minimum version like every other manager. Or if you want to do this crazy thing, don't rely on package maintainers to enforce it. I just ends up in major bloat