The Jupyter notebook system gives Python users a visual, interactive way to run code, display the results, and share the source with others. But Jupyter notebooks have limited interactivity.

Because of the client/server architecture, it is very simple to share notebooks with other users. You can — in theory — use Jupyter for anything you could use Python for.

Any Python module that runs well in a notebook interface (essentially, anything that writes to stdout as part of its behavior) is a good candidate for this. Sharing code and data generally.

As someone who often works with Python scripts, Jupyter Notebook is my favorite tool for making notes during lectures and sharing my painstakingly-written code with my programming friends and rivals.

Kite's code completions powered deep learning now work with JupyterLab and JupyterHub, helping data scientists as they type Python.