Explain the difference between Python's GIL (Global Interpreter Lock) and multi-threading vs multi-processing.
Quick Revision Summary
The Python GIL ensures thread-safe reference counting in CPython. Use multiprocessing for CPU-bound operations and multithreading for I/O operations.
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Model Answer & Deep-Dive Explanation
The Global Interpreter Lock (GIL) is a mutex in CPython that prevents multiple native threads from executing Python bytecodes simultaneously. Even on a multi-core machine, only one thread can execute Python code at any single instant.
Because of the GIL:
- Multi-threading (
threadingmodule): Best suited for I/O-bound tasks (e.g. web scraping, file I/O, database querying). While one thread waits for network or disk response, the GIL is released, allowing other threads to run. - Multi-processing (
multiprocessingmodule): Recommended for CPU-bound computations (e.g. mathematical transformations, image processing). Each process spawns its own Python interpreter and memory space, effectively bypassing the GIL and utilizing 100% of multi-core processors.
Interviewer Evaluation Points & Scoring Rubric
- 1 1. Correctly states CPython mutex limitation. 2. Explains CPU-bound vs I/O-bound distinction. 3. Identifies the multiprocessing module for true parallel execution.
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