Reproducible Experimentation Workflows With Popper

In this lesson you will learn how to automate an experimentation workflow using Popper, a Github Actions (GHA) workflow execution engine. Using the GHA workflow language allows experimenters to implement automated and portable workflows that are easy to re-execute and extend by others.


In this lesson we use the Unix Shell, and previous experience is highly recommended before taking this lesson. We assume you are familiar with tasks such as listing directories, creating, copying, remove and listing files, as well as modifying file permissions and running scripts. We also make use of Git (and Github) basic features such as creating commits and pushing to remote repos. In addition, we also make basic use of Python and Docker, which we also encourage you to learn before taking this lesson.


Setup Download files required for the lesson
00:00 1. Introduction How can I make my results easier to reproduce?
00:20 2. Actions and Workflows How can I automate a scientific exploration using a Github Actions workflow?
00:20 3. Sharing Workflows
00:20 4. Continuous Validation
00:20 5. Visualizing Workflows How can I quickly get an idea of what a workflow does?
00:40 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.