jenv VS pyenv

https://github.com/jenv/jenv to switch among multiple Java versions

I would recommend https://www.jenv.be/

Look at the https://www.jenv.be/ configure section and add the Java location where Homebrew installed your java. If I remember correctly, it should be somewhere in /usr/local/Cellar/openjdk/**

On my case I prefer use jenv (which is available on aur)

You might like jenv

There are a handful of different ways to temporarily swap out Java versions. In this case, you could probably edit the start scripts to point directly to the path for the Java version you want to use (instead of just "java" which is most likely referring to the most recent). I was already using jEnv for other things, so I configured it so JRE 1.6 would be used in my Nullpomino directory, and the latest JRE would be used everywhere else.

I like jenv for that. You can have a java version set per-project, systemwide, shell session, etc.

I don’t know if this is the “correct” way, but if you are Unix based I would recommend jenv. This is a Java environment manager, similar to pyenv if you know it. Using this tool you can easily switch from one installed version to another. It makes managing Java versions a bliss.

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.