Urllib2 和 BeautifulSoup ：不错的一对，但太慢 - urllib3 和线程？

当我听到有关线程和 urllib3 的一些好消息时，我正在寻找一种方法来优化我的代码。显然，人们不同意哪种解决方案是最好的。

下面我的脚本的问题是执行时间：太慢了！

Step 1: 我获取此页面

Step 2：我用 BeautifulSoup 解析页面

Step 3:我把数据放在excel文档中

Step 4:我对我列表中的所有国家（大列表）一次又一次地这样做 （我只是将网址中的“阿富汗”更改为另一个国家）

这是我的代码：

ws = wb.add_sheet("BULATS_IA") #We add a new tab in the excel doc
    x = 0 # We need x and y for pulling the data into the excel doc
    y = 0
    Countries_List = ['Afghanistan','Albania','Andorra','Argentina','Armenia','Australia','Austria','Azerbaijan','Bahrain','Bangladesh','Belgium','Belize','Bolivia','Bosnia and Herzegovina','Brazil','Brunei Darussalam','Bulgaria','Cameroon','Canada','Central African Republic','Chile','China','Colombia','Costa Rica','Croatia','Cuba','Cyprus','Czech Republic','Denmark','Dominican Republic','Ecuador','Egypt','Eritrea','Estonia','Ethiopia','Faroe Islands','Fiji','Finland','France','French Polynesia','Georgia','Germany','Gibraltar','Greece','Grenada','Hong Kong','Hungary','Iceland','India','Indonesia','Iran','Iraq','Ireland','Israel','Italy','Jamaica','Japan','Jordan','Kazakhstan','Kenya','Kuwait','Latvia','Lebanon','Libya','Liechtenstein','Lithuania','Luxembourg','Macau','Macedonia','Malaysia','Maldives','Malta','Mexico','Monaco','Montenegro','Morocco','Mozambique','Myanmar (Burma)','Nepal','Netherlands','New Caledonia','New Zealand','Nigeria','Norway','Oman','Pakistan','Palestine','Papua New Guinea','Paraguay','Peru','Philippines','Poland','Portugal','Qatar','Romania','Russia','Saudi Arabia','Serbia','Singapore','Slovakia','Slovenia','South Africa','South Korea','Spain','Sri Lanka','Sweden','Switzerland','Syria','Taiwan','Thailand','Trinadad and Tobago','Tunisia','Turkey','Ukraine','United Arab Emirates','United Kingdom','United States','Uruguay','Uzbekistan','Venezuela','Vietnam']
    Longueur = len(Countries_List)



    for Countries in Countries_List:
        y = 0

        htmlSource = urllib.urlopen("http://www.cambridgeesol.org/institutions/results.php?region=%s&type=&BULATS=on" % (Countries)).read() # I am opening the page with the name of the correspondant country in the url
        s = soup(htmlSource)
        tableGood = s.findAll('table')
        try:
            rows = tableGood[3].findAll('tr')
            for tr in rows:
                cols = tr.findAll('td')
                y = 0
                x = x + 1
                for td in cols:
                    hum =  td.text
                    ws.write(x,y,hum)
                    y = y + 1
                    wb.save("%s.xls" % name_excel)

        except (IndexError):
            pass

所以我知道一切并不完美，但我期待着在 Python 中学习新东西！该脚本非常慢，因为 urllib2 没那么快，而 BeautifulSoup。对于汤的事情，我想我真的无法让它变得更好，但对于 urllib2，我不能。

编辑1：多处理对 urllib2 没用？ https://stackoverflow.com/questions/6905800/multiprocessing-useless-with-urllib2对我来说似乎很有趣。 你们觉得这个潜在的解决方案怎么样？

# Make sure that the queue is thread-safe!!

def producer(self):
    # Only need one producer, although you could have multiple
    with fh = open('urllist.txt', 'r'):
        for line in fh:
            self.queue.enqueue(line.strip())

def consumer(self):
    # Fire up N of these babies for some speed
    while True:
        url = self.queue.dequeue()
        dh = urllib2.urlopen(url)
        with fh = open('/dev/null', 'w'): # gotta put it somewhere
            fh.write(dh.read())

编辑2：URLLIB3 谁能告诉我更多有关这方面的事情吗？

对多个请求重复使用同一个套接字连接 （HTTPConnectionPool 和 HTTPSConnectionPool）（可选 客户端证书验证）。https://github.com/shazow/urllib3 https://github.com/shazow/urllib3

至于我为不同页面请求同一网站 122 次，我想重复使用相同的套接字连接可能会很有趣，我错了吗？ 不能再快一点吗？ ...

http = urllib3.PoolManager()
r = http.request('GET', 'http://www.bulats.org')
for Pages in Pages_List:
    r = http.request('GET', 'http://www.bulats.org/agents/find-an-agent?field_continent_tid=All&field_country_tid=All&page=%s' % (Pages))
    s = soup(r.data)

考虑使用类似的东西工作池 http://pypi.python.org/pypi/workerpool/。参考海量下载器 https://github.com/shazow/workerpool/wiki/Mass-Downloader例如，结合urllib3 http://pypi.python.org/pypi/urllib3看起来像：

import workerpool
import urllib3

URL_LIST = [] # Fill this from somewhere

NUM_SOCKETS = 3
NUM_WORKERS = 5

# We want a few more workers than sockets so that they have extra
# time to parse things and such.

http = urllib3.PoolManager(maxsize=NUM_SOCKETS)
workers = workerpool.WorkerPool(size=NUM_WORKERS)

class MyJob(workerpool.Job):
    def __init__(self, url):
       self.url = url

    def run(self):
        r = http.request('GET', self.url)
        # ... do parsing stuff here


for url in URL_LIST:
    workers.put(MyJob(url))

# Send shutdown jobs to all threads, and wait until all the jobs have been completed
# (If you don't do this, the script might hang due to a rogue undead thread.)
workers.shutdown()
workers.wait()

您可能会从 Mass Downloader 示例中注意到，有多种方法可以执行此操作。我选择这个特定的例子只是因为它不那么神奇，但任何其他策略也都是有效的。

免责声明：我是 urllib3 和workerpool 的作者。