多线程以加快下载速度

Bla*_*ner 1 python lxml urllib urllib2 beautifulsoup

如何同时下载多个链接?我下面的脚本有效,但一次只下载一个,速度非常慢.我无法弄清楚如何在我的脚本中加入多线程.

Python脚本:

from BeautifulSoup import BeautifulSoup
import lxml.html as html
import urlparse
import os, sys
import urllib2
import re

print ("downloading and parsing Bibles...")
root = html.parse(open('links.html'))
for link in root.findall('//a'):
  url = link.get('href')
  name = urlparse.urlparse(url).path.split('/')[-1]
  dirname = urlparse.urlparse(url).path.split('.')[-1]
  f = urllib2.urlopen(url)
  s = f.read()
  if (os.path.isdir(dirname) == 0): 
    os.mkdir(dirname)
  soup = BeautifulSoup(s)
  articleTag = soup.html.body.article
  converted = str(articleTag)
  full_path = os.path.join(dirname, name)
  open(full_path, 'w').write(converted)
  print(name)
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HTML文件名为links.html:

<a href="http://www.youversion.com/bible/gen.1.nmv-fas">http://www.youversion.com/bible/gen.1.nmv-fas</a>

<a href="http://www.youversion.com/bible/gen.2.nmv-fas">http://www.youversion.com/bible/gen.2.nmv-fas</a>

<a href="http://www.youversion.com/bible/gen.3.nmv-fas">http://www.youversion.com/bible/gen.3.nmv-fas</a>

<a href="http://www.youversion.com/bible/gen.4.nmv-fas">http://www.youversion.com/bible/gen.4.nmv-fas</a>
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mgi*_*son 9

multiprocessing用来并行化东西 - 出于某些原因我比它更喜欢它threading

from BeautifulSoup import BeautifulSoup
import lxml.html as html
import urlparse
import os, sys
import urllib2
import re
import multiprocessing


print ("downloading and parsing Bibles...")
def download_stuff(link):
  url = link.get('href')
  name = urlparse.urlparse(url).path.split('/')[-1]
  dirname = urlparse.urlparse(url).path.split('.')[-1]
  f = urllib2.urlopen(url)
  s = f.read()
  if (os.path.isdir(dirname) == 0): 
    os.mkdir(dirname)
  soup = BeautifulSoup(s)
  articleTag = soup.html.body.article
  converted = str(articleTag)
  full_path = os.path.join(dirname, name)
  open(full_path, 'w').write(converted)
  print(name)

root = html.parse(open('links.html'))
links = root.findall('//a')
pool = multiprocessing.Pool(processes=5) #use 5 processes to download the data
output = pool.map(download_stuff,links)  #output is a list of [None,None,...] since download_stuff doesn't return anything
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