CLH blog AI CV Algorithm

爬虫-Scrapy


Scrapy


爬虫:自动抓取互联网上信息的程序,有效地利用互联网上的数据;简单爬虫架构如下:

  • Url管理器:是为了防止重复抓取和循环抓取,其实现方式有三种:内存(Python内存,set()方法)、关系型数据库(MySQL, urls(url,is_crawled)、缓存数据库(redis)。
  • 网页下载器:将Url对应的网页下载到本地,存储成本地文件或内存字符串,Python的文件下载器有:urllib2(Python基础模块)、requests(第三方包):

    下载网页的方法:

方法一:

import urllib2
response = urllib2.urlopen('http://www.baidu.com')
print response.getcode() 	#返回200表示获取成功
cont = response.read()		#读取内容

方法二:

import urllib2
request = urllib2.Request(url)		#创建Requset对象
request.add_data('a','1')			#添加数据
request.add_header('User-Agent','Mozilla/5.0')	#添加http的header
response = urllib2.urlopen(request)	#发送请求获取结果

特殊情景的处理器

HTTPCookieProcessor ProxyHandler HTTPSHandler HTTPRedirectHandler
opener = urllib2.build_opener(handler)
urllib2.install_opener(opener)
urllib2.urlopen(url)
urllib2.urlopen(request)

例:cookie的处理

import urllib2,cookielib
cj = cookielib.CookieJar()	#创建cookie容器
opener = urllib2.build_opener(urllib2,HTTPCookieProcessor(cj))	#创建一个opener
urllib2.install_opener(opener)	#给urllib2安装opener
response = urllib2.urlopen("http://www.baidu.com/")	#使用带有cookie的urllib2访问网页

三种方法的测试

import urllib2,cookielib

url = "http://www.baidu.com"
print "第一种方法"
response1 = urllib2.urlopen(url)
print response1.getcode()
print len(response1.read())

print "第二种方法"
request = urllib2.Request(url)
request.add_header('user-agent','Mozilla/5.0')
response2 = urllib2.urlopen(request)
print response2.getcode()
print len(response2.read())

print "第三种方法"
cj = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
urllib2.install_opener(opener)
response3 = urllib2.urlopen(url)
print response3.getcode()
print cj
print response3.read()

结果如下: ———-


  • 网页解析器:从网页中提取有价值数据的工具,Python的网页解析器一般有:正则表达式(模糊匹配)、html.parser(自带模块)、Beautiful Soup(第三方插件)、lxml(第三方插件),html.parser, Beautiful Soup和lxml为结构化解析(Document Object Model, DOM树),Dom树的结构如下:


Beautiful Soup 第三方库,用于从HTML或XML中提取数据。

安装:

python -m pip install beautifulsoup4

测试:

import bs4
print bs4

Beautiful Soup 的语法

测试代码:

# -*- coding: GBK-*-
from bs4 import BeautifulSoup
import re

html_doc = """
<html><head><title>The Dormouse's story</title></head>
<body>
<p class="title"><b>The Dormouse's story</b></p>

<p class="story">Once upon a time there were three little sisters; and their names were
<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>,
<a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and
<a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;
and they lived at the bottom of a well.</p>

<p class="story">...</p>
"""

soup = BeautifulSoup(html_doc,'html.parser',from_encoding = 'utf-8')

print '获取所有的链接'
links = soup.find_all('a')
for link in links:
    print link.name, link['href'],link.get_text()


print '获取lacie的链接'
link_node = soup.find('a',href = 'http://example.com/lacie')
print link_node.name,link_node['href'],link_node.get_text()

print "正则匹配"
link_node = soup.find('a',href=re.compile(r"ill"))
print link_node.name,link_node['href'],link_node.get_text()

print '获取P段落文字'
p_node = soup.find('p',class_="title")
print p_node.name,p_node.get_text()

结果:


Ref:[1] Python开发简单爬虫项目


上一篇 OpenGL Tutorials

下一篇 Python ClearWindow

Comments

Content