pyenv VS miniforge

For more information visit: pyenv repository

Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.

Python version manager pyenv

First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.

Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.

When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.

For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.

For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.

Nope they don't use venv for any of the oobabooga# variants nor is it recommended for the git version. I'm using https://github.com/conda-forge/miniforge#mambaforge-pypy3 (better version of the recommended conda) for the git variant. The oobabooga* variant uses micro/miniconda (I suck with names) which you can easily drop into with cmd_?something? and does it all internally. Like whoever built that whole environment setup for the _windows/linux/mac did a great job.

wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh .

Mambaforge!

Just to further clarify: you don't need mamba to avoid the Anaconda distribution. The place you get mambaforge also supplies (and originally supplied) miniforge, which is miniconda with conda-forge set as the default channel. All the *forge installers do in this regard is automatically set conda-forge as the default (and only) channel, which is something one can do manually with miniconda.

I'd recommend using miniforge if you're comfortable with CLIs, otherwise https://www.anaconda.com/.

Tip 1: To use less of your Codespaces resources start with a smaller image like Miniconda or Miniforge and install only what you need.

miniforge, no need to deal with conda environments anymore. https://github.com/conda-forge/miniforge