A very simple multithreading parallel URL fetching (without queue)

Simplifying your original version as far as possible:

import threadingimport urllib2import timestart = time.time()urls = ["http://www.google.com", "http://www.apple.com", "http://www.microsoft.com", "http://www.amazon.com", "http://www.facebook.com"]def fetch_url(url):    urlHandler = urllib2.urlopen(url)    html = urlHandler.read()    print "'%s\' fetched in %ss" % (url, (time.time() - start))threads = [threading.Thread(target=fetch_url, args=(url,)) for url in urls]for thread in threads:    thread.start()for thread in threads:    thread.join()print "Elapsed Time: %s" % (time.time() - start)

The only new tricks here are:

• Keep track of the threads you create.
• Don't bother with a counter of threads if you just want to know when they're all done; join already tells you that.
• If you don't need any state or external API, you don't need a Thread subclass, just a target function.

multiprocessing has a thread pool that doesn't start other processes:

#!/usr/bin/env pythonfrom multiprocessing.pool import ThreadPoolfrom time import time as timerfrom urllib2 import urlopenurls = ["http://www.google.com", "http://www.apple.com", "http://www.microsoft.com", "http://www.amazon.com", "http://www.facebook.com"]def fetch_url(url):    try:        response = urlopen(url)        return url, response.read(), None    except Exception as e:        return url, None, estart = timer()results = ThreadPool(20).imap_unordered(fetch_url, urls)for url, html, error in results:    if error is None:        print("%r fetched in %ss" % (url, timer() - start))    else:        print("error fetching %r: %s" % (url, error))print("Elapsed Time: %s" % (timer() - start,))

The advantages compared to Thread-based solution:

• ThreadPool allows to limit the maximum number of concurrent connections (20 in the code example)
• the output is not garbled because all output is in the main thread
• errors are logged
• the code works on both Python 2 and 3 without changes (assuming from urllib.request import urlopen on Python 3).

The main example in the concurrent.futures does everything you want, a lot more simply. Plus, it can handle huge numbers of URLs by only doing 5 at a time, and it handles errors much more nicely.

Of course this module is only built in with Python 3.2 or later… but if you're using 2.5-3.1, you can just install the backport, futures, off PyPI. All you need to change from the example code is to search-and-replace concurrent.futures with futures, and, for 2.x, urllib.request with urllib2.

Here's the sample backported to 2.x, modified to use your URL list and to add the times:

import concurrent.futuresimport urllib2import timestart = time.time()urls = ["http://www.google.com", "http://www.apple.com", "http://www.microsoft.com", "http://www.amazon.com", "http://www.facebook.com"]# Retrieve a single page and report the url and contentsdef load_url(url, timeout):    conn = urllib2.urlopen(url, timeout=timeout)    return conn.readall()# We can use a with statement to ensure threads are cleaned up promptlywith concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:    # Start the load operations and mark each future with its URL    future_to_url = {executor.submit(load_url, url, 60): url for url in urls}    for future in concurrent.futures.as_completed(future_to_url):        url = future_to_url[future]        try:            data = future.result()        except Exception as exc:            print '%r generated an exception: %s' % (url, exc)        else:            print '"%s" fetched in %ss' % (url,(time.time() - start))print "Elapsed Time: %ss" % (time.time() - start)

But you can make this even simpler. Really, all you need is:

def load_url(url):    conn = urllib2.urlopen(url, timeout)    data = conn.readall()    print '"%s" fetched in %ss' % (url,(time.time() - start))    return data    with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:    pages = executor.map(load_url, urls)print "Elapsed Time: %ss" % (time.time() - start)