python multi threading/ multiprocess code

Question

In the code below, I am considering using mutli-threading or multi-process for fetching from url. I think pools would be ideal, Can anyone help suggest solution..

Idea: pool thread/process, collect data... my preference is process over thread, but not sure.

import urllib

URL = "http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=sl1t1v&e=.csv"
symbols = ('GGP', 'JPM', 'AIG', 'AMZN','GGP', 'JPM', 'AIG', 'AMZN')
#symbols = ('GGP')

def fetch_quote(symbols):
    url = URL % '+'.join(symbols)
    fp = urllib.urlopen(url)
    try:
        data = fp.read()
    finally:
        fp.close()
    return data

def main():
    data_fp = fetch_quote(symbols)
#    print data_fp
if __name__ =='__main__':
    main()

Answer 1

Actually it's possible to do it without neither. You can get it done in one thread using asynchronous calls, like for example twisted.web.client.getPage from Twisted Web.

Answer 2

As you would know multi-threading in Python is not actually multi-threading due to GIL. Essentially it's a single thread that's running at a given time. So in your program if you want multiple urls to be fetched at any given time, multi-threading might not be the way to go. Also after the crawl you store the data in a single file or some persistent db? The decision here could affect your performance.

multi-processes are more efficient that way but have the time & memory overhead of extra processes spawn. I have explored both these options in Python recently. Here's the url (with code) -

http://stackoverflow.com/questions/3586723/python-multiprocessing-module

Answer 3

So here's a very simple example. It iterates over symbols passing one at a time to fetch_quote.

import urllib
import multiprocessing

URL = "http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=sl1t1v&e=.csv"
symbols = ('GGP', 'JPM', 'AIG', 'AMZN','GGP', 'JPM', 'AIG', 'AMZN')
#symbols = ('GGP')

def fetch_quote(symbol):
    url = URL % '+'.join(symbol)
    fp = urllib.urlopen(url)
    try:
        data = fp.read()
    finally:
        fp.close()
    return data


def main():

    PROCESSES = 4
    print 'Creating pool with %d processes\n' % PROCESSES
    pool = multiprocessing.Pool(PROCESSES)
    print 'pool = %s' % pool
    print

    results = [pool.apply_async(fetch_quote, sym) for sym in symbols]

    print 'Ordered results using pool.apply_async():'
    for r in results:
        print '\t', r.get()

    pool.close()
    pool.join()

if __name__ =='__main__':
    main()

Answer 4

You have a process that request, several information at once. Let's try to fetch these information one by one.. Your code will be :

def fetch_quote(symbols):
    url = URL % '+'.join(symbols)
    fp = urllib.urlopen(url)
    try:
        data = fp.read()
    finally:
        fp.close()
    return data

def main():
    for symbol in symbols:
        data_fp = fetch_quote((symbol,))
        print data_fp

if __name__ == "__main__":
    main()

So main() call, one by one every url to get the data. Let's multiprocess it with a pool:

import urllib
from multiprocessing import Pool

URL = "http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=sl1t1v&e=.csv"
symbols = ('GGP', 'JPM', 'AIG', 'AMZN','GGP', 'JPM', 'AIG', 'AMZN')

def fetch_quote(symbols):
    url = URL % '+'.join(symbols)
    fp = urllib.urlopen(url)
    try:
        data = fp.read()
    finally:
        fp.close()
    return data

def main():
    for symbol in symbols:
        data_fp = fetch_quote((symbol,))
        print data_fp

if __name__ =='__main__':
    pool = Pool(processes=5)
    for symbol in symbols:
        result = pool.apply_async(fetch_quote, [(symbol,)])
        print result.get(timeout=1)

In the following main a new process is created to request each symbols urls.

Note: on python, since the GIL is present, multithreading must be mostly considered as a wrong solution.

For documentation see: Multiprocessing in python