本文实例为大家分享了python使用tornado实现简单爬虫的具体代码,供大家参考,具体内容如下
代码在官方文档的示例代码中有,但是作为一个tornado新手来说阅读起来还是有点困难的,于是我在代码中添加了注释,方便理解,代码如下:
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# coding=utf-8
#!/usr/bin/env python
import time
from datetime import timedelta
try :
from HTMLParser import HTMLParser
from urlparse import urljoin, urldefrag
except ImportError:
from html.parser import HTMLParser
from urllib.parse import urljoin, urldefrag
from tornado import httpclient, gen, ioloop, queues
# 设置要爬取的网址
base_url = 'http://www.baidu.com'
# 设置worker数量
concurrency = 10
# 此代码会获取base_url下的所有其他url
@gen .coroutine
def get_links_from_url(url):
try :
# 通过异步向url发起请求
response = yield httpclient.AsyncHTTPClient().fetch(url)
print ( 'fetched %s' % url)
# 响应如果是字节类型 进行解码
html = response.body if isinstance (response.body, str ) \
else response.body.decode(errors = 'ignore' )
# 构建url列表
urls = [urljoin(url, remove_fragment(new_url))
for new_url in get_links(html)]
except Exception as e:
print ( 'Exception: %s %s' % (e, url))
# 报错返回空列表
raise gen.Return([])
# 返回url列表
raise gen.Return(urls)
def remove_fragment(url):
#去除锚点
pure_url, frag = urldefrag(url)
return pure_url
def get_links(html):
#从html页面里提取url
class URLSeeker(HTMLParser):
def __init__( self ):
HTMLParser.__init__( self )
self .urls = []
def handle_starttag( self , tag, attrs):
href = dict (attrs).get( 'href' )
if href and tag = = 'a' :
self .urls.append(href)
url_seeker = URLSeeker()
url_seeker.feed(html)
return url_seeker.urls
@gen .coroutine
def main():
# 创建队列
q = queues.Queue()
# 记录开始时间戳
start = time.time()
# 构建两个集合
fetching, fetched = set (), set ()
@gen .coroutine
def fetch_url():
# 从队列中取出数据
current_url = yield q.get()
try :
# 如果取出的数据在队列中已经存在 返回
if current_url in fetching:
return
print ( 'fetching %s' % current_url)
# 如果不存在添加到集合当中
fetching.add(current_url)
# 从新放入的链接中继续获取链接
urls = yield get_links_from_url(current_url)
# 将已经请求玩的url放入第二个集合
fetched.add(current_url)
for new_url in urls:
# Only follow links beneath the base URL
# 如果链接是以传入的url开始则放入队列
if new_url.startswith(base_url):
yield q.put(new_url)
finally :
# 队列内数据减一
q.task_done()
@gen .coroutine
def worker():
while True :
# 保证程序持续运行
yield fetch_url()
# 将第一个url放入队列
q.put(base_url)
# Start workers, then wait for the work queue to be empty.
for _ in range (concurrency):
# 启动对应数量的worker
worker()
# 等待队列数据处理完成
yield q.join(timeout = timedelta(seconds = 300 ))
# 如果两个集合不相等抛出异常
assert fetching = = fetched
# 打印执行时间
print ( 'Done in %d seconds, fetched %s URLs.' % (
time.time() - start, len (fetched)))
if __name__ = = '__main__' :
io_loop = ioloop.IOLoop.current()
io_loop.run_sync(main)
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以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。
原文链接:https://blog.csdn.net/wf134/article/details/79900407