Creating shareable Python software#
Data science and scientific computing are often taught in interactive environments like the Jupyter notebook that facilitate exploration and communication. But these environments do not encourage modularity and reusability. This leaves many to wonder what the next step is. Once you have written software that does what you want it to do, how do you reuse this software? And how do you share the software with others? How do you harden and future-proof it? What are some best practices for documenting your software for others to use, and for making it easier for others to install, use and ultimately contribute back to the software that you have written?
This tutorial focuses on these steps. Through the different steps of the tutorial we will go from code that we write in an analysis script or notebook, to a well-documented, properly-tested, installable Python package. We will also see how we set up continuous integration, as well as a few socio-technical constructs that make software broadly usable (if not useful…), and enable collaboration.
Table of contents#
[./software/01-from-notebook-to-module.md](From notebook to module)
[./software/02-from-module-to-package.md](From module to package)
[./software/06-what-next.md](A few next steps)
Copyright (c) 2020 Ariel Rokem. This tutorial is released under the CC-BY 4.0 license.