[PaulHoule]

As a Java dev I think people don’t always appreciate the flexiblity of threads for manage parallelism, concurrency, and memory. In particular with threads you can have a large number of thread share a large data structure. Say you have an ML inference model that takes 1GB of RAM. No way can you let 25 Celery workers each have a copy of that model, so if you are using Python you have to introduce a special worker class. It’s one more thing to worry about and more parameters to tune. With Java all your “workers” could be in one process, even the same process as your web server and that will be the case in Python.

Threads break down so many bottlenecks of CPU resources, memory, data serialization, waiting for communications, etc. I have a 16-core computer on my desk and getting a 12x speed-up is possible for many jobs and often worth worse less efficient use of the individual CPU. Java has many primitives for threads that include tools for specialized communications (e.g. barrier synchronization) that are necessary to really get those speed-ups and I hope Python gets those too.