running multiple threads in python, simultaneously - is it possible?

Question

I'm writing a little crawler that should fetch a URL multiple times, I want all of the threads to run at the same time (simultaneously).

I've written a little piece of code that should do that.

import thread
from urllib2 import Request, urlopen, URLError, HTTPError


def getPAGE(FetchAddress):
    attempts = 0
    while attempts < 2:
        req = Request(FetchAddress, None)
        try:
            response = urlopen(req, timeout = 8) #fetching the url
            print "fetched url %s" % FetchAddress
        except HTTPError, e:
            print 'The server didn\'t do the request.'
            print 'Error code: ', str(e.code) + "  address: " + FetchAddress
            time.sleep(4)
            attempts += 1
        except URLError, e:
            print 'Failed to reach the server.'
            print 'Reason: ', str(e.reason) + "  address: " + FetchAddress
            time.sleep(4)
            attempts += 1
        except Exception, e:
            print 'Something bad happened in gatPAGE.'
            print 'Reason: ', str(e.reason) + "  address: " + FetchAddress
            time.sleep(4)
            attempts += 1
        else:
            try:
                return response.read()
            except:
                "there was an error with response.read()"
                return None
    return None

url = ("http://www.domain.com",)

for i in range(1,50):
    thread.start_new_thread(getPAGE, url)

from the apache logs it doesn't seems like the threads are running simultaneously, there's a little gap between requests, it's almost undetectable but I can see that the threads are not really parallel.

I've read about GIL, is there a way to bypass it with out calling a C\C++ code? I can't really understand how does threading is possible with GIL? python basically interpreters the next thread as soon as it finishes with the previous one?

Thanks.

Answer 1

As you point out, the GIL often prevents Python threads from running in parallel.

However, that's not always the case. One exception is I/O-bound code. When a thread is waiting for an I/O request to complete, it would typically have released the GIL before entering the wait. This means that other threads can make progress in the meantime.

In general, however, multiprocessing is the safer bet when true parallelism is required.