To run on Windows you will need:

• An Nvidia GPU with latest drivers installed
• Docker Desktop
• WSL2
• VSCode with the DevContainers extension

If you need to apt-get any apps, add them to the Dockerfile where indicated.

Add any pip packages you need to pip-packages.txt before building the container.

To build and launch the VSCode and Jupyter servers in a dev container, open the command pallete and run Dev Containers: Reopen in Container.

Once it has finished launching then VSCode will hopefully auto-detect the Jupyter Python kernel and prompt you for the Jupyter password, which is dev.

This password can be changed in the Docker file or ommitted completely to force Jupyter to create a new GUID key which be displayed along with the server URL in the terminal.

If it doesn't do this automatically, set the kernel of your Polyglot Notebooks by

• Clicking the kernel selector at the top right of the notebook.
• Selecting Existing Jupyter Server.
• Scroll down and select Enter the URL of the running Jupyter Server.
• Paste in https://127.0.0.1:8888/lab?token=dev
• Press enter again to select 127.0.0.1 (which will be prefilled)
• Select Python 3 (ipykernel).

You can also visit that URL in your browser if you would rather use the Jupyter Labs IDE.

If you see some errors about the .NET SDK version and Python Kernel being invalid after first launch, don't worry, the installer is just catching up. You don't need to install anything.

Any files you put in the src folder will be available to the Docker container and the Jupyter server.

After you launch the DevContainer you can select extensions in VSCode, click their settings cog and select Add to devcontainer.json.

Once you have done this for all the extensions you need, open the command pallete and run Dev Containers: Rebuild and Reopen in Container.