When is Python's Global Interpreter Lock a bottleneck and how can it be mitigated?

15 Eyl 22:45

I often hear that Python's Global Interpreter Lock (GIL) limits concurrency in CPU‑bound workloads. In practice, when does the GIL become a real performance bottleneck, and what strategies are effective for working around it without switching languages? For example, are multiprocessing, C extensions, or async I/O sufficient in typical data‑processing pipelines? I’m curious about real‑world trade‑offs and how you decide which approach to use. What has been your experience?