Getting started with JupyterLab
08-29, 08:30–10:00 (Europe/Zurich), HS 118

JupyterLab is very widely used in the Python scientific community. Most, if not all, of the other tutorials will use Jupyter as a tool. Therefore, a solid understanding of the basics is very helpful for the rest of the conference as well as for your later daily work.
This tutorial provides an overview of important basic Jupyter features.



  • Terminology: JupyterLab, Notebook, IPython (10 min)
  • Notebook approach - cells, code, markdown and more (15 min)


  • Help system and history (10 min)
  • Magic functions basics (15 min)


  • Runtime measurements and profiling (20 min)
  • Exceptions and debugging (20 min)

The tutorial will be hands on.
While the students will receive a comprehensive PDF with all course content,
I will not distribute pre-filled Notebooks.
Instead, I will start with a blank Notebook for each topic and develop the
content step-by-step.
The participants are encouraged to type along.
My typing speed is usually appropriate and allows participants to follow.
In addition, the supplied PDF contains all needed code and commands to get back
on track, if I should be too fast.
I also explicitly ask for feedback if I am too fast or things are unclear.
I encourage questions at any time.
In fact, questions and my answers are often an important part of my teaching,
making the learning experience much more lively and typically more useful.

Software Requirements

You need to have Python and JupyterLab installed. I will use Python 3.10. Older versions such as 3.8. or 3.9 should work too. If you use Anaconda, you should be all set. Otherwise, if you use conda install with conda install -c conda-forge jupyterlab (or use mamba instead of conda); if you use pip install with pip install jupyterlab.

Abstract as a tweet

Affordable travel to Jupyter, no rocket (science) required



Expected audience expertise: Domain


Expected audience expertise: Python