What are the best practices for parallelism in Python?
An example of an AI chatbot conversation about best practices for parallelism in Python.
What are the best practices for parallelism in Python?
When using parallelism in Python, consider using the concurrent.futures module for easier thread and process management.
Can you explain the difference between threading and multiprocessing?
Sure! Threading is best for I/O-bound tasks, while multiprocessing is ideal for CPU-bound tasks due to Python's GIL.
How do I handle exceptions in parallel tasks?
You can use the as_completed method from concurrent.futures to handle exceptions for each future as they complete.
Are there any libraries you recommend for parallel processing?
Yes, libraries like Dask and Joblib are great for parallel processing and can simplify complex workflows.
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