Pythons breakages have also been security centric. I'm not a big fan of it, but yea Julia isn't 30 yrs old and it's done things like this every minor release without anouncement. To be clear though I'm not talking about a conscious researchable decision to drop support after 5 years. I'm talking about bugs that pop up over night. Anyway has Julia ever been audited for security? Most of the netstack was written by a single person... Makes ya wonder...
Because it has a new feature that's save the day(if it worked), fixes bugs in a janky patched Julia version, and production in the data science world looks different in research and development phases then it does for software. Production in r and d can simply be, boss wants to see the pros and cons next week with a successful run. Only with Julia have I run into these kinds of predicaments
Look at the backlog of issues in their GitHub for backports. You'll see detailed lists of reported and fixed breakages. The lists aren't small... Now go on to imagine the ones people don't report and instead patch and fix them locally. We aren't even talking about Julia code fixes, often these involve the C that creates it and are a nightmare to diagnose. I can't reply to your post unfortunately the thread is too long.
Just look at the first one: "In certain cases, pointAt method of satellite scenario Satellite class interprets Euler angle inputs in radians rather than degrees"
Now, something as fundamental as numpy dropped support for Python<3.6 in a minor release: https://numpy.org/devdocs/release/1.19.0-notes.html
And I've been bitten by relevant python libs breaking stuff even in patch releases.
It happens and it's far from particular to Julia. I just make sure to test stuff property before going to production.