This document aims to teach how to install additional kernels in JupyterHub. A kernel, in this context, is a program that runs and introspects the user’s code. JupyterHub uses kernels to run and support different programming languages. This guide was tested on a deployment of ‘The littlest JupyterHub’ running on Ubuntu 18 inside of a VirtualBox.
- Login to JupyterHub as an admin user, and run a terminal.
- Run the command:
sudo -E conda install r
- After the installation is done, run r with the command: R
- Install needed R packages with:
install.packages(c('repr', 'IRdisplay', 'IRkernel'), type = 'source')
- Make the R kernel available to all JupyterHub users:
IRkernel::installspec(user = FALSE)
- Installation is done, R notebooks should now be supported.
- Login to JupyterHub as an admin user, and run a terminal.
- Install Octave with conda:
sudo conda install octave
- If the above doesn't work, run:
conda install octave
- Install the Octave Kernel with conda:
conda config --add channels conda-forge
conda install octave_kernel
- Installation should be done, Octave notebooks should now be supported.