[the_watcher]

The reason Jupyter notebooks are so popular is that people who only learned to code or are learning to code to enable some kind of analysis can easily do it without needing to get much of anything else set up. If all you really need is to read in some data, do some statistical tests, and make some plots, I'd argue it's by far the simplest solution. Many academics don't need much more than this. Similarly, when a data scientist or product analyst is just doing analysis, not much more is needed.

Your comments about what Jupyter notebooks incentivize are definitely true (I'd argue its part of the appeal - people new to programming often don't immediately grok types of state and Jupyter kind of just says "eh, work around it"). I certainly fall victim to it and often wish for a week of "the expectation is that you will go through your notebooks and create modules or packages for them".

I also agree that running automated jobs from Jupyter isn't an optimal solution, but for many companies, if it means a data scientist (whose coding skills are primarily statistical) can get a report into production without a single engineering hour, it's often worth it.