Reproducibility is a cornerstone of sound computational work, so please ensure full reproducibility of your project by setting up a GitHub Actions CI as your continuous integration service. We provide an introductory tutorial for conda and GitHub Actions here.

If, for example, the computation of results takes multiple hours, you might not be able to run parts of your code on GitHub Actions CI. In such cases, you can add the result in a file to your repository and load it in the notebook. See below for an example code.

# If we are running on GitHub Actions CI we will load a file with existing results.

if os.environ.get("CI") == "true":
    rslt = pkl.load(open("stored_results.pkl", "br"))
    rslt = compute_results()

# Now, we are ready for further processing.

However, if you decide to do so, please be sure to provide an explanation in your notebook explaining why exactly this is required in your case.