Default Environment

The default environment includes a set of kernels that are automatically built from the EGI-Federation/egi-notebooks-images GitHub repository.

These are the available kernels:

• Python: Default Python 3 kernel, it includes commonly used data analysis and machine learning libraries. Created from the jupyter/scipy-notebook stack.

• Julia: The Julia programming language with the libraries described in jupyter/datascience-notebook.

• R: The R programming language with several packages from the R ecosystem as provided by jupyter/r-notebook and some extra libraries.

• RStudio: RStudio Server offers a RStudio IDE from the Notebooks interface.

• Octave: The Octave programming language installed on its own conda environment (named octave).

If you want to add a new kernel, just let us know, and we will discuss the best way to support your request.

CVMFS

Notebooks mounts several CVMFS repositories where you can find software relevant to your community. These are accessible from the default CVMFS location /cvmfs and also linked in your home directory /home/jovyan/cvmfs. These repositories are available:

• atlas-condb.cern.ch
• atlas.cern.ch
• auger.egi.eu
• biomed.egi.eu
• cms.cern.ch
• dirac.egi.eu
• eiscat.egi.eu
• grid.cern.ch
• notebooks.egi.eu

If you need access to any other repositories, please open a request in GGUS.

Installing your own kernels/environments permanently

If you want to have a completely customised environment for your Notebooks that persists across sessions, you can create your own conda environment in your home directory. Thanks to the nb_conda_kernels plugin these will show up automatically as an option to start notebooks with by following these steps:

1. Create a $HOME/.condarc file specifying where your environments will be created, e.g. in /home/jovyan/conda-envs/:

   env_dirs:
     - /home/jovyan/conda-envs/
   

2. Create your environments as needed, make sure to install a kernel (ipykernel) for it to show automatically:

   $ conda create -p /home/jovyan/conda-envs/myenv ipykernel scipy
   

3. The environment will show up in the launcher as a new option