To build the docker file, run from home folder docker build -t gametime -f docker/Dockerfile .

To run the docker file, run docker run -it gametime bash

Using VS Code or Pycharm, you should be able to connect to your docker container interpreter and work from your host computer.

To conda environment for cross platform use, use conda env export --from-history > conda_environment.yml. This would export conda dependencies only explicitly installed with version number only if explicitly specified during installation.

Due to the fact that docker containers are large and cumbersome, the recommended setup is to use the docker container on a remote server. Then, it is possible to have IDE's like Pycharm of code editors like VS Code to connect remotely to the server, and then use the remote python interpreter in the docker container.

You would need Pycharm for this procedure. This procedure has only been tested on Pycharm Professional, which Berkeley students can access for free. First SSH into your remote server. Then, clone the repo git clone [email protected]:icyphy/gametime.git

Once the repo is cloned, setup Pycharm remote by clicking on the remote development menu on the left and then click "New Connection" button on the top right. Input your SSH information. This should allow pycharm to access your remote server. Once you are in the remote server, you should be able to point Pycharm to your newly cloned repo and open a remote session with Pycharm

To configure the interpreter, go to File->Settings->Project: Gametime->Python Interpreter. Add a new interpreter from Docker. In the popup window select the folder . for context folder, and uncheck rebuilt each time for run at the bottom. Pycharm should be able to setup the interpreter and docker environment. Wait a few minutes, and you should have an interpreter with packages such as PyPuLP available to it.

As of 3/20/2023, Docker and Pycharm does not play well together, and many syntax highlighting features might be missing. To work around that, configure a local interpreter in the server to gain syntax highlighting. Since we are not going to be using the interpreter to run our code, the exact environment doesn't really matter, and you can add to it as you go.