Sharing data among users

To share data among the users of JupyterHub, when installing or reconfiguring, start by selecting a volume in the persistent storage field. Then, navigate to the Advanced configuration section and check the enabled checkbox in the sharedData subsection.

Reconfigure jupyter with shared data

The shared data is by default not editable by other users, but you can enable this by unchecking the readOnly checkbox. Note that this will allow any users to add files or edit existing files.

If you want to mount a subfolder in the persistent storage, specify the path to the subfolder in the subPath field. Note that this path is relative to the root of the persistent storage.


Accessing the admin panel

Jupyterhub allows you to administer and access the notebooks that are associated with the Jupyterhub server. This can for instance be useful in order to help users with debugging, or shutting down notebooks that use a lot of resources.

To access the admin panel, begin by navigating to the Control Panel which should be in on the right-hand side of the Jupyter navigation bar on the top of the page.

Jupyter notebook overview

Then, click on the Admin tab in the navigation bar. This tab should be on the left side of the navigation bar.

Jupyter control panel

You should then be taken to a page which allows you to add new users, stop, access and edit the notebooks of individual users, as well as shutting down the Hub.

Jupyter admin panel

How to add new packages

In case you are missing some packages from the default application image, you can add those packages yourself by creating a custom docker image. See this tutorial for generic instructions on how to add packages.

After having read the tutorial above, you can use the dockerfile below as a starting point when creating the dockerfile that adds new packages.

# See the value of userImage in
# to determine the latest base image


# Install system packages
USER root
RUN apt update && apt install -y vim

# Install other packages
USER notebook
RUN pip install scikit-learn

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