I have been using the rayproject/ray-ml Docker image and noticed that it has a Conda base virtual environment installed that runs by default. I’m curious what the reason is for including and running a virtual environment inside this image?
To extend your question, why was conda chosen as the virtual environment manager over the default python venv module? It’s quite difficult to extend the dependencies of a ray docker image when certain packages are unavailable for conda installation.