What are common performance issues with Python's multiprocessing?
An example of an AI chatbot conversation about Python multiprocessing performance issues.
What are common performance issues with Python's multiprocessing?
Common issues include overhead from process creation, inter-process communication delays, and GIL limitations.
How can I reduce the overhead when using multiprocessing?
You can reduce overhead by using a process pool, minimizing the number of processes, and optimizing task granularity.
What is the Global Interpreter Lock (GIL) and how does it affect multiprocessing?
The GIL is a mutex that protects access to Python objects, limiting the execution of threads and affecting CPU-bound tasks.
Are there any alternatives to multiprocessing in Python?
Yes, you can consider using threading for I/O-bound tasks or libraries like Dask and Joblib for parallel processing.
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