Technical Mid Level

Explain the Global Interpreter Lock. How does it affect concurrency in Python and what strategies do you use to work around it?

Quick Tip

Distinguish I/O-bound from CPU-bound: "For I/O-bound work, asyncio or threading works fine despite the GIL. For CPU-bound work, I use multiprocessing or offload to C extensions that release the GIL."

What good answers include

The GIL ensures only one thread executes Python bytecode at a time, protecting internal state but limiting CPU-bound parallelism in threads. Workarounds: multiprocessing for CPU-bound work (separate processes, each with its own GIL), asyncio for I/O-bound concurrency, C extensions that release the GIL (NumPy), and concurrent.futures for clean process/thread pool abstractions. Strong candidates also mention that the GIL does not affect I/O-bound threading and know about the ongoing efforts to remove it (PEP 703, free-threaded Python 3.13+).

What interviewers are looking for

Core Python knowledge. Candidates who do not know about the GIL will make poor concurrency decisions. Those who can discuss both the limitations and the practical workarounds demonstrate depth.

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