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 cluster.