Web Reference: Even though David Beazley's talk explains that network traffic improves the scheduling of Python threading module, you should use the multiprocessing module. I included this as an option in your code (see bottom of my answer). 2 days ago · Why Threads and asyncio Won't Help Here Because of Python's Global Interpreter Lock (GIL), only one thread can execute Python code at a time. Adding threads to a CPU-bound task doesn't parallelise anything — it just adds overhead. The threaded version runs in roughly 40 seconds, slightly slower than the synchronous one. In this tutorial, you'll explore concurrency in Python, including multi-threaded and asynchronous solutions for I/O-bound tasks, and multiprocessing for CPU-bound tasks. By the end of this tutorial, you'll know how to choose the appropriate concurrency model for your program's needs.
YouTube Excerpt: Concurrency is the act of having your computer do multiple things at the same time. This video shows the difference of adding ...
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