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.

Code can run directly from text files as well as Jupyter Notebook files, and many common file formats for both code and data can be rendered with live previews.

The trick is that, when using the Python kernel, you can use a ! to execute shell commands and a %% to specify that a particular cell lives in a file. So consider this notebook from Google Collab: ...

Image: Jupyter Notebook Jupyter is a browser-based, open-source data science notebook tool that supports Python, Julia, and other dynamic programming languages such as R, Scilab and Octane.