问题
I have code like this.
for p in range(1,1000):
result = False
while result is False:
ret = urllib2.Request(\'http://server/?\'+str(p))
try:
result = process(urllib2.urlopen(ret).read())
except (urllib2.HTTPError, urllib2.URLError):
pass
results.append(result)
I would like to make two or three request at the same time to accelerate this. Can I use urllib2 for this, and how? If not which other library should I use? Thanks.
回答1:
You can use asynchronous IO to do this.
requests + gevent = grequests
GRequests allows you to use Requests with Gevent to make asynchronous HTTP Requests easily.
import grequests
urls = [
'http://www.heroku.com',
'http://tablib.org',
'http://httpbin.org',
'http://python-requests.org',
'http://kennethreitz.com'
]
rs = (grequests.get(u) for u in urls)
grequests.map(rs)
回答2:
Take a look at gevent — a coroutine-based Python networking library that uses greenlet to provide a high-level synchronous API on top of libevent event loop.
Example:
#!/usr/bin/python
# Copyright (c) 2009 Denis Bilenko. See LICENSE for details.
"""Spawn multiple workers and wait for them to complete"""
urls = ['http://www.google.com', 'http://www.yandex.ru', 'http://www.python.org']
import gevent
from gevent import monkey
# patches stdlib (including socket and ssl modules) to cooperate with other greenlets
monkey.patch_all()
import urllib2
def print_head(url):
print 'Starting %s' % url
data = urllib2.urlopen(url).read()
print '%s: %s bytes: %r' % (url, len(data), data[:50])
jobs = [gevent.spawn(print_head, url) for url in urls]
gevent.joinall(jobs)
回答3:
So, it's 2016 😉 and we have Python 3.4+ with built-in asyncio module for asynchronous I/O. We can use aiohttp as HTTP client to download multiple URLs in parallel.
import asyncio
from aiohttp import ClientSession
async def fetch(url):
async with ClientSession() as session:
async with session.get(url) as response:
return await response.read()
async def run(loop, r):
url = "http://localhost:8080/{}"
tasks = []
for i in range(r):
task = asyncio.ensure_future(fetch(url.format(i)))
tasks.append(task)
responses = await asyncio.gather(*tasks)
# you now have all response bodies in this variable
print(responses)
loop = asyncio.get_event_loop()
future = asyncio.ensure_future(run(loop, 4))
loop.run_until_complete(future)
Source: copy-pasted from http://pawelmhm.github.io/asyncio/python/aiohttp/2016/04/22/asyncio-aiohttp.html
回答4:
I know this question is a little old, but I thought it might be useful to promote another async solution built on the requests library.
list_of_requests = ['http://moop.com', 'http://doop.com', ...]
from simple_requests import Requests
for response in Requests().swarm(list_of_requests):
print response.content
The docs are here: http://pythonhosted.org/simple-requests/
回答5:
Either you figure out threads, or you use Twisted (which is asynchronous).
回答6:
maybe using multiprocessing and divide you work on 2 process or so .
Here is an example (it's not tested)
import multiprocessing
import Queue
import urllib2
NUM_PROCESS = 2
NUM_URL = 1000
class DownloadProcess(multiprocessing.Process):
"""Download Process """
def __init__(self, urls_queue, result_queue):
multiprocessing.Process.__init__(self)
self.urls = urls_queue
self.result = result_queue
def run(self):
while True:
try:
url = self.urls.get_nowait()
except Queue.Empty:
break
ret = urllib2.Request(url)
res = urllib2.urlopen(ret)
try:
result = res.read()
except (urllib2.HTTPError, urllib2.URLError):
pass
self.result.put(result)
def main():
main_url = 'http://server/?%s'
urls_queue = multiprocessing.Queue()
for p in range(1, NUM_URL):
urls_queue.put(main_url % p)
result_queue = multiprocessing.Queue()
for i in range(NUM_PROCESS):
download = DownloadProcess(urls_queue, result_queue)
download.start()
results = []
while result_queue:
result = result_queue.get()
results.append(result)
return results
if __name__ == "__main__":
results = main()
for res in results:
print(res)
来源:https://stackoverflow.com/questions/4119680/multiple-asynchronous-connections-with-urllib2-or-other-http-library