多线程以加快下载速度

Question

如何同时下载多个链接？我下面的脚本可以工作，但一次只能下载一个，而且速度非常慢。我不知道如何在脚本中合并多线程。

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)

名为links.html的HTML文件：

<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>

Answer 1

我使用multiprocessing来并行化事物——出于某种原因，我更喜欢它而不是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

Answer 2

2017年，还有其他一些选择，比如asyncio和ThreadPoolExecutor。

以下是ThreadPoolExecutor的一个示例（包含在Python futures中）

from concurrent.futures import ThreadPoolExecutor

def download(url, filename):
    ... your dowload function...
    pass

with ThreadPoolExecutor(max_workers=12) as executor:
    future = executor.submit(download, url, filename)
    print(future.result())

函数的作用是：将任务提交到队列中。（队列管理为您完成）

Python version 3.5 and above:
if max_workers is None or not given, it will default to the number of processors on the 
machine, multiplied by 5.

您可以设置max_workers，实际上是CPU核心数的几倍，然后根据上下文切换开销进行一些测试，看看faw的性能如何提高。

更多信息： https://docs.python.org/3/library/concurrent.futures.html

Answer 3

在我看来，这就像是消费者-生产者问题-参见维基百科

你可以用

import Queue, thread

# create a Queue.Queue here
queue = Queue.Queue()

print ("downloading and parsing Bibles...")
root = html.parse(open('links.html'))
for link in root.findall('//a'):
  url = link.get('href')
  queue.put(url) # produce




def thrad():
  url = queue.get() # consume
  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, 'wb').write(converted)
  print(name)

thread.start_new(thrad, ()) # start 1 threads