Quick Answer
Python threading: threads share memory, good for I/O-bound tasks (network, file I/O). GIL prevents true CPU parallelism. threading.Thread, Lock, RLock, Semaphore, Event, Condition. For CPU-bound tasks use multiprocessing (separate processes, no GIL). concurrent.futures.ThreadPoolExecutor for thread pool. AsyncIO for high-concurrency I/O without threads (event loop, single thread, cooperative multitasking).
Answer
threading handles I/O-bound tasks. GIL limits CPU-bound threads. multiprocessing enables true parallelism. concurrent.futures simplifies thread/process pool usage.
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SugharaIQ Editorial Team
Verified Answer
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