---
title: Jupyterhub on Merlin
#tags:
#keywords:
last_updated: 31 July 2019
#summary: ""
sidebar: merlin6_sidebar
permalink: /merlin6/jupyterhub.html
---

Jupyterhub provides [jupyter notebooks](https://jupyter.org/) that are launched on
cluster nodes of merlin and can be accessed through a web portal.

## Accessing Jupyterhub and launching a session

The service is available inside of PSI (or through a VPN connection) at


**<https://merlin-jupyter.psi.ch:8000>**


   1. **Login**: You will be presented with a **Login** web page for
      authenticating with your PSI account. We are still in a **TEST
      PHASE** and we are using a self-generated certificate, so your
      browser will generate a warning about it. Please agree to the
      exception in this special case.
   1. **Spawn job**: The **Spawner Options** page allows you to
      specify the properties (Slurm partition, running time,...) of
      the batch jobs that will be running your jupyter notebook. Once
      you click on the `Spawn` button, your job will be sent to the
      Slurm batch system. If the cluster is not currently overloaded
      and the resources you requested are available, your job will
      usually start within 30 seconds.
   






## Jupyter software environments - running different kernels

Your notebooks can run within different software environments which are offered by a number of available **Jupyter kernels**.

E.g. in this test installation we provide two environments targeted at data science
  * **tensorflow-1.13.1_py36**: contains Tensorflow, Keras, scikit-learn, Pandas, numby, and dependencies. Stable
  * **talos_py36**: also contains the Talos package. This
    environment is experimental and subject to updates and changes.

When you create a new notebook you will be asked to specify which kernel you want to use. It is also possible to switch the kernel of a running notebook, but you will lose the state of the current kernel, so you will have to recalculate the notebook cells with this new kernel.

These environments are also available for standard work in a shell session. You can activate an environment in a normal merlin terminal session by using the `module` (q.v. [using Pmodules](using-modules.html)) command to load anaconda python, and from there using the `conda` command to switch to the desired environment

```
module use unstable
module load anaconda/2019.07
conda activate tensorflow-1.13.1_py36
```

When the `anaconda` module has been loaded, you can list the available environments by executing

```
conda info -e
```


## Using nbextensions for adding features to your notebook

There exist a number of useful [contributed but unofficial
extensions](https://jupyter-contrib-nbextensions.readthedocs.io/en/latest/index.html)
that add useful features to your notebooks.

From the classic Notebook UI you can access the available extensions in a separate tab as displayed in the screenshot, below. You may have to unselect the *disable configuration for nbextensions without explicit copatibility*. The extensions we tested still worked fine with this jupyterhub version of 1.0.0.

{% include image.html file="jupyter-nbextensions.png" caption="Launch Classic Notebook" max-width=586 %}

Especially the following extensions make working with larger notebooks easier
   * **Table of Contents**: Displays a TOC on the left and you can also configure it
     to add and update a TOC at the head of the document.
   * **Collapsible Headings**: allows you to fold all the cells below a heading

## Troubleshooting

   In case of problems or request, please either submit a **[PSI Service Now](https://psi.service-now.com/psisp)** incident containing *"Merlin Jupyterhub"* as part of the subject, or contact us by mail through <merlin-admins@lists.psi.ch>.