What is the difference between concurrency and parallelism in Python?
An example of an AI chatbot conversation about Python concurrency and parallelism concepts.
What is the difference between concurrency and parallelism in Python?
Concurrency is about dealing with lots of things at once, while parallelism is about doing lots of things at once. In Python, concurrency can be achieved using threads or async programming, while parallelism often involves multiprocessing.
Can you give me an example of concurrency in Python?
Sure! An example of concurrency in Python is using the asyncio library to run multiple tasks at the same time without blocking each other.
What about parallelism? How is it implemented?
Parallelism in Python can be implemented using the multiprocessing module, which allows you to run multiple processes simultaneously, taking advantage of multiple CPU cores.
Which one is better for performance?
It depends on the task. For I/O-bound tasks, concurrency is often better, while for CPU-bound tasks, parallelism can provide better performance.
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