Comment by andreldm
I worked at a company where data scientists wrote python code using pandas and we had port it to java and a library called keanu that was very useful but soon became unmaintained.
Of course this was very time consuming and unrewarding, all because only java applications could be deployed to production due to a stupid top-down decision.
This GraalPy sounds like something I wish existed back then.
jep[0] has existed for a while now, and does what GraalPy is doing quite well.
I'm using it for similar purposes as you stated and for that it works quite well. A research group I am collaborating with does a lot of their work in one Java application (ImageJ for microscopy), so by integrating my Python processing code into that application, it finds its way a lot quicker into the daily workflows of everyone in that group.
Most recently I've also extended the jep setup to include optional Python version bootstrapping via uv[1], so that I can be sure that the plugins I'm writing have the correct Python version available, without people having to install that manually on the machine.
[0]: https://github.com/ninia/jep
[1]: https://github.com/astral-sh/uv