Web Reference: 4 days ago · It runs on both POSIX and Windows. The multiprocessing module also introduces the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data parallelism). In Python the multiprocessing module can be used to run a function over a range of values in parallel. For example, this produces a list of the first 100000 evaluations of f. The Python multiprocessing package allows you to run code in parallel by leveraging multiple processors on your machine, effectively sidestepping Python’s Global Interpreter Lock (GIL) to achieve true parallelism.
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