Once your container is running, click on its name on the left-hand panel if necessary, to view all details including Jupyter console logs:

Next to the logs, you can see ‘Volumes’ listing /home/jovyan/work. This is the standard path to the Jupyter root workspace within the Linux containers that are based on Jupyter images. ContainDS has taken care of mapping that path to the workspace folder you provided on your local computer.

Launching Jupyter Lab

Docker will have allocated a web port on your machine that maps to the container’s internal Jupyter server port (8888). You don’t need to know what port has been allocated. To launch Jupyter Lab (or notebook) in your default web browser, just click on the ‘WEB’ button:

There should be no need to provide a token or password.

You can now use Jupyter as normal. To install packages into the environment, e.g. Python packages, use the ‘Terminal’ option under ‘Other’ in the Launch tab within Jupyter Lab. To access the Launcher tab if you can’t find it, click the ‘+’ button beneath the menu bar in Jupyter Lab.

If you need to use sudo to install an operating system package such as NodeJS, you may need to ensure your container runs with the correct privileges. Use the ‘Allow sudo in container’ option in Preferences before starting the container.

Jupyter’s Lifecycle

Jupyter should remain running as long as Docker Desktop is running (unless you stop the container through ContainDS). You can even close ContainDS and the Jupyter server should remain running.

If you explicitly Restart (or Stop then Start) the container using ContainDS then you may find that Docker has allocated a different port on your computer. In that case, you may need to click ‘WEB’ again to launch a new Jupyter Lab session in your browser under the new port.

Continue to Working with the Container.