Getting started with a containerized Jupyter on the GEOMAR scalc machines

[kathoef]

To download, disambiguate and start a containerized JupyterLab on the scalc machines simply execute singularity pull, a unix mv command and a singularity run as follows:

$ singularity pull docker://martinclaus/py-da-stack:latest
$ ls
py-da-stack_latest.sif
$ mv py-da-stack_latest.sif py-da-stack_latest_$(date +"%Y-%m-%d").sif
$ ls
py-da-stack_latest_2020-10-23.sif
$ singularity run py-da-stack_latest_2020-10-23.sif
...
[I 20:35:40.586 LabApp] JupyterLab extension loaded from /opt/conda/lib/python3.8/site-packages/jupyterlab
[I 20:35:40.586 LabApp] JupyterLab application directory is /opt/conda/share/jupyter/lab
[I 20:35:40.853 LabApp] [Jupytext Server Extension] Deriving a JupytextContentsManager from LargeFileManager
[I 20:35:40.858 LabApp] Serving notebooks from local directory: /home/khoeflich/py-da-stack
[I 20:35:40.858 LabApp] Jupyter Notebook 6.1.4 is running at:
[I 20:35:40.858 LabApp] http://scalc03:8888/?token=xxx
[I 20:35:40.858 LabApp]  or http://127.0.0.1:8888/?token=xxx
[I 20:35:40.858 LabApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
...

Connecting to this JupyterLab server works exactly as you are already used to. I have (only) quick checked if all necessary Python packages are available, please tell me if that is not the case.

/cc @vopikamm

[kathoef]

I should probably also add the repository that builds these Jupyter envs: https://github.com/martinclaus/py-da-stack