What are some use cases for parallelism in Python?
An example of an AI chatbot conversation about parallelism in Python and its applications.
What are some use cases for parallelism in Python?
Parallelism in Python can be used for tasks like data processing, web scraping, and machine learning model training.
Can you give me an example of how to implement parallelism in a data processing task?
Sure! You can use the concurrent.futures module to run tasks in parallel. For example, using ThreadPoolExecutor to process a list of URLs.
What are the benefits of using parallelism in Python?
The main benefits include improved performance, reduced execution time, and better resource utilization.
Are there any limitations or challenges with parallelism in Python?
Yes, challenges include the Global Interpreter Lock (GIL), which can limit true parallel execution in CPU-bound tasks.
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