Package for using processes which mimics the threading module
processing is a package for the Python language which supports the spawning of processes using the API of the standard library’s threading module. It runs on both Unix and Windows.
- Objects can be transferred between processes using pipes or multi-producer/multi-consumer queues.
- Objects can be shared between processes using a server process or (for simple data) shared memory.
- Equivalents of all the synchronization primitives in threading are available.
- A Pool class makes it easy to submit tasks to a pool of worker processes.
The processing.Process class follows the API of threading.Thread. For example
from processing import Process, Queue def f(q): q.put('hello world') if __name__ == '__main__': q = Queue() p = Process(target=f, args=[q]) p.start() print q.get() p.join()
Synchronization primitives like locks, semaphores and conditions are available, for example
>>> from processing import Condition >>> c = Condition() >>> print c <Condition(<RLock(None, 0)>), 0> >>> c.acquire() True >>> print c <Condition(<RLock(MainProcess, 1)>), 0>
One can also use a manager to create shared objects either in shared memory or in a server process, for example
>>> from processing import Manager >>> manager = Manager() >>> l = manager.list(range(10)) >>> l.reverse() >>> print l [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] >>> print repr(l) <Proxy[list] object at 0x00E1B3B0>
Tasks can be offloaded to a pool of worker processes in various ways, for example
>>> from processing import Pool >>> def f(x): return x*x ... >>> p = Pool(4) >>> result = p.mapAsync(f, range(10)) >>> print result.get(timeout=1) [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
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