What are the main challenges of parallelism in Python?
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What are the main challenges of parallelism in Python?
Some key challenges include the Global Interpreter Lock (GIL), managing shared state, and debugging concurrent code.
How does the Global Interpreter Lock affect performance?
The GIL allows only one thread to execute at a time, which can limit the performance of CPU-bound programs.
Are there any libraries that help with parallelism in Python?
Yes, libraries like multiprocessing, concurrent.futures, and joblib can help manage parallel tasks effectively.
What strategies can I use to debug parallel code?
You can use logging, breakpoints, and tools like PyCharm's debugger to trace issues in parallel code.
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