What are the benefits of using parallelism in Python?
Parallelism in Python allows for concurrent execution of tasks, improving performance and efficiency, especially in CPU-bound operations.
Can you give me some examples of where parallelism is useful?
Sure! It's particularly useful in data processing, web scraping, and machine learning tasks where large datasets are involved.
Are there any libraries in Python that support parallelism?
Yes, popular libraries include multiprocessing
, concurrent.futures
, and joblib
, which facilitate parallel execution.
What are the challenges of implementing parallelism in Python?
Challenges include managing shared state, debugging parallel code, and the Global Interpreter Lock (GIL) which can limit true parallelism.
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