tips for folks getting started.

Don't use the system-level python as that can update and break dependencies. E.g. Arch uses 3.13 if you update and Tensorflow can't go above 3.12.

Use pyenv to do version management per project. github.com/pyenv/pyenv

Don't install pip dependencies globally. Use virtualenv to set up dependencies per project. virtualenv.pypa.io/

Python versioning is rough out of the box and these tips can save you some pain.

@mauve This is reasonable advice, even pip gives me a warning that I should do this! However, I do not agree with this approach 100%. Often I am using a single-application virtual machine or container, in which case I don't need separate per-project virtual environments. Also, there are too many python virtual environment managers to choose from. Finally, sometimes using a virtual environment (specifically, virtualenv) is not compatible with the fish shell that I use. I prefer simplicity.

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@brandon Have you messed with Qubes OS? I've been considering setting a machine up with it to see how it goes.

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