Redlining Your CPU for Fun and Profit: Threading and Multiprocessing in Python
summary
Shows how to swap a simple for loop for concurrent.futures and get real parallelism using ProcessPoolExecutor for CPU‑bound primes (two lines changed to .map) and ThreadPoolExecutor for IO using .submit and futures.as_completed. Explains future.result blocking semantics, default worker counts and context manager usage, and when to prefer processes vs threads or a hybrid. Demonstrations claim noticeable speedups and drive CPU to near 100%.
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