====== **Edits by MSovara** ======

===== Jupyter / Ipython Notebook =====

Jupyter is installed in most of the python modules. To make use of it you would do something like:
<code bash>
jupyter-notebook
</code>

However using it effectively on the cluster is a bit more complicated...

After [[CHPC quickstart guide | Logging in]] your account check for your preferred python version as follows:

<code bash>
module avail 2>&1 | grep python
</code>

Now proceed to request for an interactive compute node where a configuration file and security measures will be established. A single core on an interactive node has proven sufficient for this exercise. Request an arbitrary interactive compute node as follows: 

<code bash>
qsub -I -P PROJ0101 -q serial -l select=1:ncpus=1:mpiprocs=1:nodetype=haswell_reg
</code>

//**Note**:// 
  -//"PROJ0101" is an arbitrary project name, kindly use your research project's shortname e.g. //ERTH0859\\
  -// Record the cnode ID because you will ssh into that particular compute node when setting up your password.//
  -//Advanced interactive compute node settings are found here: [[CHPC quickstart guide | Example interactive job request]].//

In your interactive compute node, load the preferred python module as follows: 
<code bash>
module add chpc/python/3.6.0_gcc-6.3.0
</code>
 
==== Security ====

You are not the only person on the system, so it is important to set up authentication on your notebook so that not everyone gets access to your notebook (and worse -- your data).

So first one needs a configuration file, this can be done by passing the generate-config parameter to jupyter as follows:

<code bash>
[USERNAME@cnode0010 ~]$ jupyter-notebook --generate-config
</code>

**Note**
  -//This writes default config to: /home/USERNAME/.jupyter/jupyter_notebook_config.py//
  -//The output file "jupyter_notebook_config.py" will be listed as a hidden file. Thus, to view it do a $ ls -a //

Next you need to generate your password (remember it -- you'll need it when you connect later):
<code bash>
python
</code>
<code python>
from notebook.auth import passwd
passwd()
Enter password:
Verify password:
'sha1:f27008fdb0eb:4c2f305d5e230edca16c7059882ba3ba63bee03b'
</code>

Use the following command to access the "jupyter_notebook_config.py" file: $ cd /home/USERNAME/.jupyter/jupyter_notebook_config.py \\
Now edit the ''jupyter_notebook_config.py'' file, specifically edit the ''c.NotebookApp.passwd'' line. 


<code>
c.NotebookApp.password = 'sha1:f27008fdb0eb:4c2f305d5e230edca16c7059882ba3ba63bee03b'
</code>

**Remember to uncomment it, don't just copy and paste my hash in**.

==== Starting a notebook inside a job ====

There might be a cleaner way of doing this... Please let us know if you have one!

**VERY IMPORTANT:**  Do not add the lines below to your .ssh/config file on the cluster, you //WILL// break any attempt at parallel processing!

Open a terminal on your local machine and create a ''.ssh/config'' file. 
 
<code>
touch .ssh/config
</code>

If your desktop system runs Windows, a simple way to deal with this is to run a unix-like environment inside Windows.  You can either use[[http://cygwin.com|Cygwin]] Cygwin directly, or start a "Local Terminal" in [[https://mobaxterm.mobatek.net/|MobaXterm]].  From this terminal you can edit the local ''~/.ssh/config'' file as if you were working on a Linux computer. 

 
Continue to edit the ''~/.ssh/config'' file on your local machine by adding in these lines:
<code>
Host cnode*
    Hostname %h
    User YOURUSERNAME
    ProxyCommand ssh YOURUSERNAME@lengau.chpc.ac.za nc %h 22
    LocalForward 8838 localhost:8838
</code>


**Note**
  -//Each session will be assigned a different compute node (cnode* changes everytime you request for an interactive compute node session)//
  -//Use localForward and localhost port number provided for each different session.//

Ultimately, what this will do is allow you to ''ssh'' directly to a compute node (note you can only do this to nodes where you currently have a job running). 

<code>
ssh cnode*
</code>

You should be prompted for your password, twice. This is because the ''ssh'' logs in to Lengau first and then from Lengau it logs into the the compute node. 

You are now ready to roll...

In your browser go to: http://localhost:8838

The jobscript will look something like:
<file bash jupyter.qsub>
#!/bin/bash
#PBS -P SHORTNAME
#PBS -q serial
#PBS -l select=1:ncpus=8:mpiprocs=1
#PBS -l walltime=08:00:00
#PBS -N Jupyter
#PBS -m abe
#PBS -M YOUR@EMAIL.ADDRESS

module add chpc/python/3.6.0_gcc-6.3.0

JUPYTERPORT=8838  # you could change this too, if you wanted to.

hostname > ~/jupyter.host

jupyter-notebook --port=${JUPYTERPORT} --no-browser
</file>

If you submit that job and wait for it to start running then you can check which host the session is running on with:
<code bash>
cat ~/jupyter.host
</code>

Then, again on your local machine, you need to connect to the compute node, i.e. ''ssh cnode0101''.  If you are working in Windows, do this from your Cygwin or MobaXterm terminal command line.  You will be prompted for your Lengau login password.