What are the best practices for using parallelism in Python?
An example of an AI chatbot conversation about best practices for parallelism in Python.
What are the best practices for using parallelism in Python?
When using parallelism in Python, consider using the concurrent.futures module for easier management of threads and processes.
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 Global Interpreter Lock.
How do I handle exceptions in parallel tasks?
You can handle exceptions by using the as_completed method from concurrent.futures, which allows you to check for exceptions in each future.
Are there any performance considerations I should be aware of?
Yes, be mindful of overhead from context switching in threading and the memory usage in multiprocessing. Profiling your code is essential.
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