I do not like to use homebrew for python, but I install it for Homebrew dependencies.
I use the native installer available on python.org. It works perfectly on my mac, and gives me no issues. I create local virtualenvs for each project, from the base distribution of choice.
I have found zero reasons NOT to use the standard distribution, and it allows me to install any version of sub-version I desire.
4 comments
[ 2.9 ms ] story [ 17.8 ms ] threadA poetry/.toml/requirements.txt file and venv is enough to manage without having 100's of data science libs installed.
> Feel free to use conda but keep it scoped to individual projects rather than as a system-wide configuration.
Good advice!
I use the native installer available on python.org. It works perfectly on my mac, and gives me no issues. I create local virtualenvs for each project, from the base distribution of choice.
I have found zero reasons NOT to use the standard distribution, and it allows me to install any version of sub-version I desire.
[0] https://github.com/pyenv/pyenv
[1] https://github.com/pyenv/pyenv#automatic-installer