On Sat, 7 Jan 2023 at 04:54, jacob kruger <jacob.kruger.w...@gmail.com> wrote: > > I am just trying to make up my mind with regards to what I should look > into working with/making use of in terms of what have put in subject line? > > > As in, if want to be able to trigger multiple/various threads/processes > to run in the background, possibly monitoring their states, either via > interface, or via global variables, but, possibly while processing other > forms of user interaction via the normal/main process, what would be > recommended? >
Any. All. Whatever suits your purpose. They all have different goals, different tradeoffs. Threads are great for I/O bound operations; they're easy to work with (especially in Python), behave pretty much like just having multiple things running concurrently, and generally are the easiest to use. But you'll run into limits as your thread count climbs (with a simple test, I started seeing delays at about 10,000 threads, with more serious problems at 100,000), so it's not well-suited for huge scaling. Also, only one thread at a time can run Python code, which limits them to I/O-bound tasks like networking. Multiple processes take a lot more management. You have to carefully define your communication channels (for instance, a multiprocessing.Queue() to collect results), but they can do CPU-bound tasks in parallel. So multiprocessing is a good way to saturate all of your CPU cores. Big downsides include it being much harder to share information between the processes, and much MUCH higher resource usage than threads (with the same test as the above, I ran into limitations at just over 500 processes - way fewer than the 10,000 threads!). Asynchronous I/O runs a single thread in a single process. So like multithreading, it's only good for I/O bound tasks like networking. It's harder to work with, though, since you have to be very careful to include proper await points, and you can stall out the entire event loop with one mistake (common culprits being synchronous disk I/O, and gethostbyname). But the upside is that you get near-infinite tasks, basically just limited by available memory (or other resources). Use whichever one is right for your needs. ChrisA -- https://mail.python.org/mailman/listinfo/python-list
