一个非常简单的多线程并行URL提取(没有队列)

时间:2013-04-23 23:58:43

标签: python multithreading callback python-multithreading urlfetch

我花了一整天的时间在Python中寻找最简单的多线程URL提取器,但我找到的大多数脚本都使用队列或多处理或复杂的库。

最后我自己写了一个,我作为答案报告。请随时提出改进建议。

我猜其他人可能一直在寻找类似的东西。

5 个答案:

答案 0 :(得分:39)

尽可能简化原始版本:

import threading
import urllib2
import time

start = 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)

这里唯一的新技巧是:

  • 跟踪您创建的主题。
  • 如果你只想知道他们什么时候完成,不要打扰线程的反击; join已经告诉你了。
  • 如果您不需要任何州或外部API,则不需要Thread子类,只需要target函数。

答案 1 :(得分:26)

multiprocessing有一个不会启动其他进程的线程池:

#!/usr/bin/env python
from multiprocessing.pool import ThreadPool
from time import time as timer
from urllib2 import urlopen

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):
    try:
        response = urlopen(url)
        return url, response.read(), None
    except Exception as e:
        return url, None, e

start = 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,))

与基于Thread的解决方案相比的优势:

  • ThreadPool允许限制最大并发连接数(代码示例中为20
  • 输出没有乱码,因为所有输出都在主线程中
  • 记录错误
  • 代码适用于Python 2和3,无需更改(假设Python 3为from urllib.request import urlopen)。

答案 2 :(得分:12)

concurrent.futures中的主要示例可以完成您想要的一切,更简单。此外,它可以一次只执行5次处理大量的URL,并且可以更好地处理错误。

当然这个模块只是内置在Python 3.2或更高版本中......但是如果你使用2.5-3.1,你可以在PyPI上安装反向端口futures。您需要更改示例代码的所有内容是使用concurrent.futures搜索和替换futures,而对于2.x,urllib.requesturllib2

以下是向后移植到2.x的示例,修改为使用您的URL列表并添加时间:

import concurrent.futures
import urllib2
import time

start = 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 contents
def 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 promptly
with 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)

但你可以让这更简单。真的,你所需要的只是:

def load_url(url):
    conn = urllib2.urlopen(url, timeout)
    data = conn.readall()
    print '"%s" fetched in %ss' % (url,(time.time() - start))
    return data

with futures.ThreadPoolExecutor(max_workers=5) as executor:
    pages = executor.map(load_url, urls)

print "Elapsed Time: %ss" % (time.time() - start)

答案 3 :(得分:1)

我现在正在发布一个不同的解决方案,通过让工作线程不是-damon并将它们连接到主线程(这意味着阻塞主线程直到所有工作线程完成)而不是通知每个工作线程的执行结束,并回调一个全局函数(正如我在上一个答案中所做的那样),就像在一些注释中所指出的那样,这种方式不是线程安全的。

import threading
import urllib2
import time

start = time.time()
urls = ["http://www.google.com", "http://www.apple.com", "http://www.microsoft.com", "http://www.amazon.com", "http://www.facebook.com"]

class FetchUrl(threading.Thread):
    def __init__(self, url):
        threading.Thread.__init__(self)
        self.url = url

    def run(self):
        urlHandler = urllib2.urlopen(self.url)
        html = urlHandler.read()
        print "'%s\' fetched in %ss" % (self.url,(time.time() - start))

for url in urls:
    FetchUrl(url).start()

#Join all existing threads to main thread.
for thread in threading.enumerate():
    if thread is not threading.currentThread():
        thread.join()

print "Elapsed Time: %s" % (time.time() - start)

答案 4 :(得分:-1)

此脚本从数组中定义的一组URL中提取内容。它为每个要获取的URL生成一个线程,因此它可用于一组有限的URL。

每个线程都使用队列对象,而不是使用队列对象,而是通过对全局函数的回调来通知它,该函数会保持运行的线程数的计数。

import threading
import urllib2
import time

start = time.time()
urls = ["http://www.google.com", "http://www.apple.com", "http://www.microsoft.com", "http://www.amazon.com", "http://www.facebook.com"]
left_to_fetch = len(urls)

class FetchUrl(threading.Thread):
    def __init__(self, url):
        threading.Thread.__init__(self)
        self.setDaemon = True
        self.url = url

    def run(self):
        urlHandler = urllib2.urlopen(self.url)
        html = urlHandler.read()
        finished_fetch_url(self.url)


def finished_fetch_url(url):
    "callback function called when a FetchUrl thread ends"
    print "\"%s\" fetched in %ss" % (url,(time.time() - start))
    global left_to_fetch
    left_to_fetch-=1
    if left_to_fetch==0:
        "all urls have been fetched"
        print "Elapsed Time: %ss" % (time.time() - start)


for url in urls:
    "spawning a FetchUrl thread for each url to fetch"
    FetchUrl(url).start()