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Introduction

JupyterHub spawns, manages multiple instances of the single-user Jupyter notebook server. The Jupyter notebook server is run on the interactive psana nodes to allow direct access to LCLS data.The Jupyter notebooks are running python kernels from the new Conda Release System. It is possible to run both Python 2 and Python 3 kernel, but only Python 2 provides the LCLS psana analysis package.

The Jupyter notebook server is run on the interactive psana nodes or  the interactive psffb nodes. For most users psana should be used. The psff should be used only for current experiments that require very high bandwidth to the data. See the table below for what is accessible:

JupyterHub is a web service and is available at:

https://pswww.slac.stanford.edu/jupyterhub/hub/home

or following the links at pswww.

NOTE: The jupyterhub web interface by default will only allow you to navigate to subdirectories of your home directory (see https://github.com/jupyter/notebook/issues/2032 for the reasoning behind this decision).  If you want to navigate to another directory that is not underneath your home directory, run a script like this in your home directory to make a softlink that you can click on in the jupyterhub web interface:

import os
os.symlink("/reg/d/psdm/xpp/xpptut15","xpptut15")

Creating Your Own Jupyter Kernels

See https://jupyter-client.readthedocs.io/en/latest/kernels.html#kernelspecs.  To create your own custom kernel (e.g. to select a particular version of psana) insert a kernel directory in your home directory ~/.local/share/jupyter/kernels.  You can copy one of the production kernel directories from /reg/g/psdm/sw/conda/jhub_config/prod-rhel7/kernels and modify as you see fit.

511 Error

If you try to start a server and see a "511 error" it is often an indication that your ssh keys are too old (or non-existent).  When that happens you need to generate new keys by running this script:

/reg/g/psdm/sw/jupyterhub/psjhub/jhub/generate-keys.sh

Upgrades