I did exactly that for a recent paper [1].

    1. 9 Jupyter Notebooks attached (with HTML converts to the journal), all figures and statistics generated in notebooks, all commits of the entire 5 year research process versioned in a Gitlab repo, using Jupytext for clarity
    2. All base data shared, using HyperLogLog to reduce privacy conflicts
    3. Versioned docker image added to our registry, which includes Jupyter and the analysis environment used for the study (Carto-Lab Docker Version 0.9.0 [2])
    4. Post acceptance, I published another notebook how other users can load and work with the shared data, including making (limited) additional inference [3]
    5. For the peer review process, I added all (redacted) notebook HTML files to a Github repo [4]

It was a fun experiment where I tried a maximum of transparency in research. This maybe added 1 full year of additional work, but I still don't regret it. Given the quite specific audience for this paper, I doubt that anyone has ever tried to open the Jupyter Notebooks - I even doubt that reviewers had a look at them, at least by judging from the comments during peer review.

[1] https://doi.org/10.1371/journal.pone.0280423

[2] https://gitlab.vgiscience.de/lbsn/tools/jupyterlab

[3] https://kartographie.geo.tu-dresden.de/ad/sunsetsunrise-demo...

[4] https://anonymous-peer12345.github.io/