multiprocessing.Pool()

The multiprocessing.Pool() is a class in the Python multiprocessing module that provides a convenient way to parallelize the execution of a function across multiple input values. It allows you to create a pool of worker processes that can execute a given function in parallel, with each process taking care of a different subset of the input values.

The Pool() class provides a number of methods for submitting tasks to the pool and retrieving their results. The most commonly used methods are map() and apply_async(). The map() method takes a function and an iterable of input values, and applies the function to each value in the iterable in parallel. The apply_async() method is similar, but allows you to submit individual tasks to the pool asynchronously, and retrieve their results as they become available.

The Pool() class is useful for speeding up CPU-bound tasks by distributing them across multiple processor cores. However, it is important to note that it may not always result in a speedup, and can even slow down certain types of tasks if the overhead of managing the pool becomes significant. Therefore, it is important to carefully benchmark and tune your code to ensure that multiprocessing is the right solution for your particular problem.