Python thread pool similar to the multiprocessing Pool?

Q:

Is there a Pool class for worker threads, similar to the multiprocessing module's Pool class?

I like for example the easy way to parallelize a map function

def long_running_func(p):    c_func_no_gil(p)p = multiprocessing.Pool(4)xs = p.map(long_running_func, range(100))

however I would like to do it without the overhead of creating new processes.

I know about the GIL. However, in my usecase, the function will be an IO-bound C function for which the python wrapper will release the GIL before the actual function call.

Do I have to write my own threading pool?

A:

I just found out that there actually is a thread-based Pool interface in the multiprocessing module, however it is hidden somewhat and not properly documented.

It can be imported via

from multiprocessing.pool import ThreadPool

It is implemented using a dummy Process class wrapping a python thread. This thread-based Process class can be found in multiprocessing.dummy which is mentioned briefly in the docs. This dummy module supposedly provides the whole multiprocessing interface based on threads.

A:

In Python 3 you can use concurrent.futures.ThreadPoolExecutor, i.e.:

executor = ThreadPoolExecutor(max_workers=10)a = executor.submit(my_function)

See the docs for more info and examples.

A:

from Queue import Queuefrom threading import Threadclass Worker(Thread):    """Thread executing tasks from a given tasks queue"""    def __init__(self, tasks):        Thread.__init__(self)        self.tasks = tasks        self.daemon = True        self.start()        def run(self):        while True:            func, args, kargs = self.tasks.get()            try: func(*args, **kargs)            except Exception, e: print e            self.tasks.task_done()class ThreadPool:    """Pool of threads consuming tasks from a queue"""    def __init__(self, num_threads):        self.tasks = Queue(num_threads)        for _ in range(num_threads): Worker(self.tasks)    def add_task(self, func, *args, **kargs):        """Add a task to the queue"""        self.tasks.put((func, args, kargs))    def wait_completion(self):        """Wait for completion of all the tasks in the queue"""        self.tasks.join()if __name__ == '__main__':    from random import randrange    delays = [randrange(1, 10) for i in range(100)]        from time import sleep    def wait_delay(d):        print 'sleeping for (%d)sec' % d        sleep(d)        # 1) Init a Thread pool with the desired number of threads    pool = ThreadPool(20)        for i, d in enumerate(delays):        # print the percentage of tasks placed in the queue        print '%.2f%c' % ((float(i)/float(len(delays)))*100.0,'%')                # 2) Add the task to the queue        pool.add_task(wait_delay, d)        # 3) Wait for completion    pool.wait_completion()