O'Reilly logo

Functional Python Programming by Steven Lott

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Using a multiprocessing pool for concurrent processing

One elegant way to make use of the multiprocessing module is to create a processing Pool object and assign work to the various processes in that pool. We will use the OS to interleave execution among the various processes. If each of the processes has a mixture of I/O and computation, we should be able to assure that our processor is very busy. When processes are waiting for I/O to complete, other processes can do their computation. When an I/O completes, a process will be ready to run and can compete with others for processing time.

The recipe for mapping work to a separate process looks as follows:

    import multiprocessing
    with multiprocessing.Pool(4) as workers:
 workers.map(analysis, glob.glob(pattern)) ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required