On the note of Jupyter notebooks and version control - there was a talk at this year's Pycon Ireland about using a built in cleaner for notebooks when committing the JSON (discard the cell results), and then dropping the whole lot into a CI system utilising remote execution (and Bazel or similar) to run and cache the outputs. Was a talk from CodeThink. No video up yet though. Scenario was reproducible notebooks for processing data from a system under test.
gucci-on-fleek|2 months ago
Yup, I use a long "jq" command [0] as a Git clean filter for my Jupyter notebooks, and it works really well. I use a similar program [1] for Mathematica notebooks, and it also works really well.
[0]: https://stackoverflow.com/a/74104693
[1]: https://github.com/JP-Ellis/mathematica-notebook-filter