However the new interface is quite confusing because you can’t disable the setting at first. This is not needed if you are using a container, because the files are already mounted there and you don’t need to copy them again using sftp, etc. As of now, in version 2020.2, when we set up a remote interpreter, P圜harm implicitly defines a deployment configuration. Recent P圜harm versions are making it more difficult to set up a remote interpreter. So we keep doing the old way, using a remote interpreter. Since Django used environment variables to override its settings file, this setup was unusable. The first issue that I remember is that the interpreter forgot all the environment variables declared in the docker-compose file. Things didn’t transition smoothly back then. Then finally JetBrains released support to allow interpreters inside a docker-compose configuration. This worked for quite a long time (almost 5 years). Then we setup P圜harm so that it treated the docker container as a remote interpreter. To debug with this kind of setup, we used an SSH daemon inside our container. We already managed some of our projects as microservices described by one or more docker-compose files. However, back then the notion of developing a Django project from inside a container was not so common. JetBrains generously gave us a free licence to use the whole suite of JetBrains tools as their way of supporting open source projects. Back then the standard approach of attaching your debug interpreter was by creating a virtual environment in your python project. I was involved with different kinds of Django projects in the past.

Python interpreter pycharm