What is the fastest way to send 100,000 HTTP requests in Python?


Question

I am opening a file which has 100,000 URL's. I need to send an HTTP request to each URL and print the status code. I am using Python 2.6, and so far looked at the many confusing ways Python implements threading/concurrency. I have even looked at the python concurrence library, but cannot figure out how to write this program correctly. Has anyone come across a similar problem? I guess generally I need to know how to perform thousands of tasks in Python as fast as possible - I suppose that means 'concurrently'.

1
237
2/6/2019 8:29:13 PM

Accepted Answer

Twistedless solution:

from urlparse import urlparse
from threading import Thread
import httplib, sys
from Queue import Queue

concurrent = 200

def doWork():
    while True:
        url = q.get()
        status, url = getStatus(url)
        doSomethingWithResult(status, url)
        q.task_done()

def getStatus(ourl):
    try:
        url = urlparse(ourl)
        conn = httplib.HTTPConnection(url.netloc)   
        conn.request("HEAD", url.path)
        res = conn.getresponse()
        return res.status, ourl
    except:
        return "error", ourl

def doSomethingWithResult(status, url):
    print status, url

q = Queue(concurrent * 2)
for i in range(concurrent):
    t = Thread(target=doWork)
    t.daemon = True
    t.start()
try:
    for url in open('urllist.txt'):
        q.put(url.strip())
    q.join()
except KeyboardInterrupt:
    sys.exit(1)

This one is slighty faster than the twisted solution and uses less CPU.

179
8/28/2014 12:38:46 PM

A solution using tornado asynchronous networking library

from tornado import ioloop, httpclient

i = 0

def handle_request(response):
    print(response.code)
    global i
    i -= 1
    if i == 0:
        ioloop.IOLoop.instance().stop()

http_client = httpclient.AsyncHTTPClient()
for url in open('urls.txt'):
    i += 1
    http_client.fetch(url.strip(), handle_request, method='HEAD')
ioloop.IOLoop.instance().start()

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