My RSS reader is written in async Python but I think it was a mistake and I built my image sorter to use gunicorn which means I have to run it inside WSL on Windows but actually it works really well. My "image sorter" is actually a lot of different things (it has a webcrawler in it, a tagging system, will probably take over the RSS reader's job someday) but it does an unholy mix of )(i) "things that require significant CPU" (like... math) and (ii) "things that require just a touch of CPU" like serving images.
I found that (i) was blocking (ii) making the image sorter unusable.
So far though that is processes and not threads.
For the last few weeks for the hell of it I've been writing a small and very pedagogical chess playing program in Python (trying to outdo Lisp) and once I got the signs figured out in the alpha-beta negamax algorithm it can now beat my tester most of the time. (When I had the signs wrong it managed to find the fool's mate which is not too surprising in retrospect since it looks ahead enough plies)
That was my major goal but I'd also like to try an MCTS chess program which is more of a leap into the unknown. Unlike alpha-beta MCTS can be almost trivially parallelized (run 16 threads of it for, say, 0.1 s, merge the trees, repeat, ...) and threads would be a convenient way to handle concurrency here although multiprocessing out to be good enough. So I am thinking about using a non-GIL Python but on the other hand I could also rewrite in Java and get a 50x or so speedup and great thread support.
(Note the problem here is that unlike games where you fill up a board, chess doesn't really progress when you play out random moves. With random moves for instance you can't reproduce White's advantage at the beginning of the game and if your evaluation function can't see that you are doing really bad. I need a weak player for the playouts that plays well enough that it can take advantage of situations that real players can take advantage of at least some of the time. A really good move ordering function for an alpha-beta search might do the trick.
I found that (i) was blocking (ii) making the image sorter unusable.
So far though that is processes and not threads.
For the last few weeks for the hell of it I've been writing a small and very pedagogical chess playing program in Python (trying to outdo Lisp) and once I got the signs figured out in the alpha-beta negamax algorithm it can now beat my tester most of the time. (When I had the signs wrong it managed to find the fool's mate which is not too surprising in retrospect since it looks ahead enough plies)
That was my major goal but I'd also like to try an MCTS chess program which is more of a leap into the unknown. Unlike alpha-beta MCTS can be almost trivially parallelized (run 16 threads of it for, say, 0.1 s, merge the trees, repeat, ...) and threads would be a convenient way to handle concurrency here although multiprocessing out to be good enough. So I am thinking about using a non-GIL Python but on the other hand I could also rewrite in Java and get a 50x or so speedup and great thread support.
(Note the problem here is that unlike games where you fill up a board, chess doesn't really progress when you play out random moves. With random moves for instance you can't reproduce White's advantage at the beginning of the game and if your evaluation function can't see that you are doing really bad. I need a weak player for the playouts that plays well enough that it can take advantage of situations that real players can take advantage of at least some of the time. A really good move ordering function for an alpha-beta search might do the trick.