The beauty of python for someone like me is that I can get my job done without actually having to do it. I free up my own time to leverage more of my creativity and have a multiplicative effect on my productivity.
The reason I bring all of this up is that so many of the examples for advanced libraries I see are geared towards seasoned software engineers. The examples include false arrays of data so that you can "just see" how to use it. I don't think anyone realizes how confusing this is to the guy who is a restaurant manager, or the gal who is a researcher that just needs to know how to make this work for them.
If it's an image, how about putting image = cv2.imread("C:\image.jpg") or whatever?
Anyway, a bit of a rant but there are people who are very thankful that smart people in this world like yourself write libraries we can use to make our daily lives better. Including example code that is stupid simple would make me so much happier.
I have used ray (a year ago) in one of the advertised basic applications: parallelising the environments for RL. It was unusable back then, as it was clogging up the memory.
The plasma store which is backend for arrow was never cleaned which made the computation stop after 3 hours
Here’s the issue:
https://github.com/ray-project/ray/issues/2128
Or perhaps this has been fixed already?
It's nice to have the option to speed up python in certain cases though.
https://github.com/stackless-dev/stackless/wiki
It got less attention than pypy, but might be more pragmatic wrt parallel perf. There's also some work in pypy to remove the GIL, but not sure if there's been any news on that lately.
