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?
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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.
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