JupyterLab is a widely use tool in the scientific and data science community.
It allows for very fast interactive work.
It is way more powerful than the standard Python REPL or other terminal-based,
improved REPL.
This tutorial introduces basic and more advanced JupyterLab features.
In addition it highlights potential problems that result from the principles
JupyterLab is based upon.
Being aware of these problems is important to avoid them.
Examples of workflows show how JupyterLab can be used by everybody for various
tasks.
You will learn when to use or not to use JupyterLab.
If you haven't use JupyterLab before, you will learn about a new tool that can
be a good addition to your programming toolbox.
If you have already been using JupyterLab, but found it not ideal for your
purposes, you will learn how you can avoid potential pitfalls, to apply
appropriate workflows, and when to switch to or combine JupyterLab with a
different tool.