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Setup
<iframe src="https://indico.cern.ch/event/1058838/attachments/2427696/4157672/HSF%20Matplotlib%20Setup.mp4" title= "HSF Matplotlib Setup" width="100%" height="500" frameborder="0" allowfullscreen=""> </iframe>

Binder setup

For this tutorial we will be using Binder. It offers a no setup, click and ready to go Jupyter Notebook environment.

We will be using the following Github Repository to follow the lesson.

You would only need to look for the Binder

Binder is good for live coding sessions and thus has a 10-20 min inactivity timeout. If this occurs during the session follow these steps (they should work most of the time)

  • Click on cloud with down arrow
  • Close the Binder
  • Click on the Binder badge to open a new Binder session
  • Create new notebook
  • Click on cloud with up arrow to regain your changes

Plan B: Google Colab

If for whatever reason Binder is not working. All notebooks should have a Open In Colab Just click and run the cells that say If on Colab

This only requires the user to have a Google account but it is much more stable and does not have the inactivity limit like Binder.

Some details on Google Colab:

  • Colab allows you to create a copy of the notebook and stores it in your google drive
  • Colab comes with some python libraries installed but not the ones required for our workshop. This forces us to run the first cell of the notebook which downloads the materials from Github and installs the necessary packages into your session.
  • However, when running this cell for the first time, Colab will not be able to make use of some of the libraries installed unless we click on Runtime and then click on Restart Runtime. Rerun the first cell and we are good to go!
  • The caveat is that this procedure would need to be executed for each notebook in the lesson.

Plan C: SWAN

SWAN is a CERN based notebook hosting service. It is stable like Colab and setup is easy like Binder. Simply click on the Badge below and log in to SWAN with your CERN account.

SWAN

If you want to run locally

We highly recommend you create a virtual environment first. Open your terminal and do

conda create --name mpl
conda activate mpl
git clone https://github.com/hsf-training/hsf_matplotlib_notebooks.git
cd hsf_matplotlib_notebooks
# Now install the requirements
conda install -c conda-forge --file requirements.txt
conda install notebook jupyterlab

Now you can launch your jupyter notebook or jupyter-lab session

jupyter notebook --no-browser
# Or
jupyter lab --no-browser

Then copy one of the urls printed on the terminal window and paste in your browser.

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