Python: Something like `map` that works on threads [closed]

Answer 1

I'd wrap it up in a function (untested):

import itertools
import threading
import urllib2
import Queue

def openurl(url, queue):
    def starter():
        try:
            result = urllib2.urlopen(url)
        except Ecxeption, exc:
            def raiser():
                raise exc
            queue.put((url, raiser))
        else:
            queue.put((url, lambda:result))
    threadind.Thread(target=starter).start()

myurls = ... # the list of urls
myqueue = Queue.Queue()

map(openurl, myurls, itertools.repeat(myqueue))

for each in myurls:
    url, getresult = queue.get()
    try:
        result = getresult()
    except Exception, exc:
        print 'exception raised:' + str(exc)
    else:
        # do stuff with result

Answer 2

Someone recommended I use the futures package for this. I tried it and it seems to be working.

http://pypi.python.org/pypi/futures

Here's an example:

"Download many URLs in parallel."

import functools
import urllib.request
import futures

URLS = ['http://www.foxnews.com/',
        'http://www.cnn.com/',
        'http://europe.wsj.com/',
        'http://www.bbc.co.uk/',
        'http://some-made-up-domain.com/']

def load_url(url, timeout):
    return urllib.request.urlopen(url, timeout=timeout).read()

with futures.ThreadPoolExecutor(50) as executor:
   future_list = executor.run_to_futures(
           [functools.partial(load_url, url, 30) for url in URLS])

Answer 3

The Python module Queue might help you. Use one thread that uses Queue.put() to push all urls into the queue and the worker threads simply get() the urls one by one.

Python Docs: queue — A synchronized queue class

Answer 4

There is a map method in multiprocessing.Pool. That does multiple processes.

And if multiple processes aren't your dish, you can use multiprocessing.dummy which uses threads.

import urllib
import multiprocessing.dummy

p = multiprocessing.dummy.Pool(5)
def f(post):
    return urllib.urlopen('http://stackoverflow.com/questions/%u' % post)

print p.map(f, range(3329361, 3329361 + 5))

Answer 5

Here is my implementation of threaded map:

from threading import Thread
from queue import Queue

def thread_map(f, iterable, pool=None):
    """
    Just like [f(x) for x in iterable] but each f(x) in a separate thread.
    :param f: f
    :param iterable: iterable
    :param pool: thread pool, infinite by default
    :return: list if results
    """
    res = {}
    if pool is None:
        def target(arg, num):
            try:
                res[num] = f(arg)
            except:
                res[num] = sys.exc_info()

        threads = [Thread(target=target, args=[arg, i]) for i, arg in enumerate(iterable)]
    else:
        class WorkerThread(Thread):
            def run(self):
                while True:
                    try:
                        num, arg = queue.get(block=False)
                        try:
                            res[num] = f(arg)
                        except:
                            res[num] = sys.exc_info()
                    except Empty:
                        break

        queue = Queue()
        for i, arg in enumerate(iterable):
            queue.put((i, arg))

        threads = [WorkerThread() for _ in range(pool)]

    [t.start() for t in threads]
    [t.join() for t in threads]
    return [res[i] for i in range(len(res))]