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Refresh Jupyter in your browser, you should now have your environment available as a kernel.

R Notebook

Creation of an R is slightly different from the kernel is essentially the same as creating a kernel for Python Notebooks (section above), however, one needs to install multiple R packages for it to work properly. Instead of creating a new conda environment from scratch and installing this different packages manually we recommend you copy our JupyterHub conda environment which already has all you need for setting up your own R kernel:

conda create --name <new_environment_for_R> --clone /albedo/soft/sw/conda-sw/jupyterhub-<newest_version_available>/

Then, activate your new environment and install the R packages you need, either with the R package manager or with conda (as in the following example):

conda activate <new_environment_for_R>
conda install r-<my_package>

Finally, create your new R kernel:

Rscript -e 'IRkernel::installspec(name="<new_environment_for_R>", displayname="<new_environment_for_R>")'

Refresh Jupyter in your browser, you should now have your environment available as a kernel.

Singularity

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