Computational reproducibility: A how-to guide based on The Turing Way

Reproducible research is necessary to ensure that our scientific output can be independently verified and built upon in future work. But conducting reproducible research requires software development skills that are not usually taught or expected of academic researchers. The Turing Way is an open-source, community-led handbook that supports this knowledge (among others) in an accessible and comprehensible form for everyone. Its moonshot goal is to make reproducible research “too easy not to do”. This talk will guide you through the best practices in computational reproducibility outlined by The Turing Way. I will show you how to version control your code, how to improve its quality, how to test its functionality, and how to make it open-source, using Python as an example. I will also demonstrate how to capture and share your computational environment, and how to incorporate continuous integration techniques into your coding workflow.