= Conda
{tag=Python virtualization}
{tag=Evil}
{wiki}
Conda is like <pip>, except that it also manages shared library dependencies, including providing prebuilts.
This has made <Conda> very popular in the <deep learning> community around 2020, where using Python frontends like <PyTorch> to configure faster precompiled backends was extremely common.
It also means that it is a full package manager and extremely overbloated and blows up all the time. People should just use <Docker> instead for that kind of stuff: https://www.reddit.com/r/learnmachinelearning/comments/kd88p8/comment/keco07k/
You also have to buy a license to use their repos if you are part of a large-enough organization: https://stackoverflow.com/questions/74762863/are-conda-miniconda-and-anaconda-free-to-use-and-open-source
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