If you are looking for a convenient way to run JupyterLab notebooks try UFRC JupyterHub service. It presents a convenient web interface to start notebooks, consoles, or terminals with multiple custom kernels and several job resource request profiles, which we can expand on request to satisfy your needs.
Note: you might see a different username in the top-right corner of your jhub page. It's a mostly harmless cachine issues, but it could prevent you from stopping your server and show you a permission denied error as JupyterHub thinks you're trying to control another user's server. It's a known issue. We'll update jhub when there is a fix. For now do a hard reload of the jhub webpage (shift+F5 or hold the shift key on the keyboard and click on the reload browser button) and you'll see your username in the top-right corner and be able to stop your server.
[8 min, 1 sec] This video covers the use of Jupyter Notebooks via https://jhub.rc.ufl.edu/ to run Python, R and other notebooks on HiPerGator.
- Connect to https://jhub.rc.ufl.edu/
- Launch notebooks in various coding languages
- Launch a terminal
- Upload and download files via your browser
- 'Python3 3.7 (basic)' - the default python3 kernel from the jupyterhub, which doesn't have much in it.
- 'Python3 3.6 (full)' - our main HiPerGator python3/3.6 environment module with "Everything and the kitchen sink" in it as far as python modules are concerned.
- 'PyViz-0.10.0' - special environment for https://pyviz.org/ based data analysis and plotting environment.
- 'R 3.6 (full)' - our main R/3.6 environment module from HiPerGator with everything and a kitchen sink as far as packages are concerned.
Packages and modules in the full python3 and R environments are installed on request (https://support.rc.ufl.edu).
Users can define their own Jupyter kernels for use in JupyterHub. See https://jupyter-client.readthedocs.io/en/stable/kernels.html
In short, kernel definitions can be put into ~/.local/share/jupyter/kernels directory. See
/apps/jupyterhub/kernels/ for examples of how we define commonly used kernels.