Difference between conda and pip installs within a conda environment
I seem to be asking myself this question a lot, having recently switched to using conda environments (Anaconda), but I end up Googling and not getting too far. I now run all my projects within their own conda environments, as I like to keep everything as separate and with as little dependencies on other programs as possible. For example, a recent environment: conda create -n RL numpy tensorflow-gpu Then I activate the environment, and realise "Oh - I forgot to install gym". In this case, this is only available in the PIP package manager, and so I simply type pip install gym . But in other