Demystifying Python Asyncio: When to Use Concurrency vs. Multiprocessing in Production.

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Learn when to use Python asyncio, threading, or multiprocessing to improve API performance, handle I/O efficiently, and scale CPU-intensive workloads.
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Choosing between asyncio and multiprocessing starts with identifying your bottleneck. Asyncio improves throughput for I/O-bound workloads by letting tasks share an event loop while waiting for network or database responses. Multiprocessing runs CPU-intensive work across separate processes, bypassing the traditional CPython GIL constraint. This guide explains when to use each approach, how threads fit into the picture, and which production anti-patterns can undermine performance.