Running Multiple RStudio Environments on Jupyter

Running RStudio within Jupyter has been possible for quite some time with jupyter-server-proxy. Doing so has its benefits, notably the ability to leverage JupyterHub’s systemdspawner to control the amount of resources users can use, a feature that is not available in the free version of RStudio.

It would have been nice to have the ability to choose between different R versions, which is another feature that is only available in the paid version of RStudio. Because jupyter-server-proxy relies on iterating through entry points in each proxy package, the only way to enable that right now is to modify jupyter-ression-proxy itself.

This is where our #PR133 comes in. By allowing setup_rserver to receive a custom name and a configuration file as arguments, all it takes to add additional R versions on Jupyter is to create a new skeleton package that imports jupyter-ression-proxy:setup_rserver and
has additional entry points for jupyter_serverproxy_servers.

Here is a working example we currently use on our HPC cluster.