IPython and Jupyter provide tools for interactive computing that are widely used in scientific computing, education, and data science, but can benefit any Python developer.
In this tutorial we will introduce you to the latest developement in IPython and Jupyter, get you up to speed on how to install jupyter on your machine and where to seek help for larger deployment. Then we will dive into intermediate features that makes the power of IPython and Jupyter.
We will dive into how to make the best use of features like
- Async REPL (New in IPython 7)
- And how to tie that into the Visualisation capabilities of Jupyter, and the new JupyterLab interface.
- Widgets (building simple interactive dashboards based on ipywidgets)
- Multilanguage integration,
The notebooks also allow for code in multiple languages allowing to mix Python with Cython, C, R and other programming languages to access features hard to obtain from Python.
For full details about IPython including documentation, previous presentations and videos of talks, please see the project website.
The materials for this tutorial will be available on a github repository.