You can use Jupyter Notebooks to share Python code and its output with third parties, to run code with live interactive feedback, or to systematically track and document the progress of your work.

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.

Dask’s task framework works hand-in-hand with Python’s native concurrent.futures interfaces, so for those who’ve used that library, most of the metaphors for how jobs work should be familiar.

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.