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  • Python 开发简单爬虫

    1. 目标:开发轻量级爬虫(不包括需登陆的 和 Javascript异步加载的)

      不需要登陆的静态网页抓取

    2. 内容:

      2.1 爬虫简介

      2.2 简单爬虫架构

      2.3 URL管理器

      2.4 网页下载器(urllib2)

      2.5 网页解析器(BeautifulSoup)

      2.6 完整实例:爬取百度百科Python词条相关的1000个页面数据

    3. 爬虫简介:一段自动抓取互联网信息的程序

      

      爬虫价值:互联网数据,为我所用。

      

    4. 简单爬虫架构:

      

      运行流程:   

      

    5. URL管理器:管理待抓取URL集合 和 已抓取URL集合

      - 防止重复抓取、防止循环抓取

      

      - 实现方式:

      

    6. 网页下载器:将互联网URL对应的网页下载到本地的工具

      

      - 分类:

      

      - urllib2 下载网页的方法:

        1. 最简洁方法: url ===> urllib2.urlopen(url)   

    import urllib2
    
    # 直接请求
    response = urllib2.urlopen('http://www.baidu.com')
    
    # 获取状态码,如果是200表示获取成功
    print response.getcode()
    
    # 读取内容
    cont = response.read()
    

        2. 添加data、http header: (url,data,header) ===> urllib2.Request ===> urllib2.urlopen(request)

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

        3. 添加特殊情景的处理器:

           

    import urllib2, cookielib
    
    # 创建cookie容器
    cj = cookielib.CookieJar()
    
    # 创建1个opener
    opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
    
    # 给urllib2安装opener
    urllib2.install_opener(opener)
    
    # 使用带有cookie的urllib2访问网页
    response = urllib2.urlopen(“http://www.baidu.com/”)
    

    7. urllib2 实例代码演示:

    # -*- coding: utf-8 -*-
    """
    Created on Tue Feb 14 10:31:06 2017
    
    @author: Wayne
    """
    import urllib2, cookielib
    
    url = "http://www.baidu.com"
    
    print "the 1st method"
    response1 = urllib2.urlopen(url)
    print response1.getcode()
    print len(response1.read())
    
    print "the 2nd method"
    request = urllib2.Request(url)
    request.add_header("user-agent", "Mozilla/5.0")
    response2 = urllib2.urlopen(request)
    print response2.getcode()
    print len(response2.read())
    
    print "the 3rd method"
    cj = cookielib.CookieJar()
    opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
    response3 = urllib2.urlopen(url)
    print response3.getcode()
    print cj
    print response3.read()
    

    8. 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:

      

      结构化解析 - DOM ( Document Object Model) 树:

      

    9. 网页解析器 - Beautiful Soup

      9.1 Beautiful Soup

        - Python 第三方库,用于从HTML或XML中提取数据

        - 官网:http://www.crummy.com/software/BeautifulSoup

      9.2 安装并测试 beautifulsoup4

        - 安装:pip install beautifulsoup4

        - 测试:import bs4

      9.3 Beautiful Soup语法

        

        

      9.4 创建 BeautifulSoup 对象

    from bs4 import BeautifulSoup
    # 根据 HTML 网页字符串创建 BeautifulSoup 对象
    soup = BeautifulSoup(
                         html_doc,                     # HTML文档字符串
                         'html.parser'                  # HTML解析器
                         from_encoding='utf-8'     # HTML文档的编码
                         )
    

      9.5 搜索节点(find_all, find)

    # 方法:find_all(name, attrs, string)
    # 查找所有标签为 a 的节点
    soup.find_all('a')
    
    # 查找所有标签为 a,链接符合 /view/123.htm 形式的节点
    soup.find_all('a', href='/view/123.htm')
    soup.find_all('a', href=re.compiler(r'/view/d+.htm'))
    
    # 查找所有标签为div, class为abc,文字为Python的节点
    soup.find_all('div', class_='abc', string='Python')
    

      9.6 访问节点信息

    # 得到节点: <a href='1.html'>Python</a>
    
    # 获取查找到的节点的标签名称
    node.name
    
    # 获取查找到的a节点的href属性
    node['href']
    
    # 获取查找到的a节点的链接文字
    node.get_text()
    

    10. BeautifulSoup 实例测试

    # -*- coding: utf-8 -*-
    """
    Created on Tue Feb 14 11:00:42 2017
    
    @author: Wayne
    """
    
    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='urf-8')
    
    print '
    ## Get all the links'
    links = soup.find_all('a')
    for link in links:
        print link.name, link['href'], link.get_text()
        
        
    print '
    ## Get the links include "lacie"'
    link_node = soup.find('a', href='http://example.com/lacie')
    print link_node.name, link_node['href'], link_node.get_text()
    
    
    print '
    ## RE matching'
    link_node = soup.find('a', href=re.compile(r"ill"))
    print link_node.name, link_node['href'], link_node.get_text()
    
    
    print '
    ## Get "P" Paragraph Text'
    p_node = soup.find('p', class_='title')
    print p_node.name, p_node.get_text()
    

        

      

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  • 原文地址:https://www.cnblogs.com/wnzhong/p/6397092.html
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