Python开发简单爬虫

来源：互联网发布：杰拉德华莱士数据编辑：程序博客网时间：2024/05/01 05:54

简单爬虫框架：
　　爬虫调度器 -> URL管理器 -> 网页下载器(urllib2) -> 网页解析器(BeautifulSoup) -> 价值数据

Demo1：

# coding:utf8import urllib2,cookieliburl = "https://www.baidu.com"print '第一种方法'response1 = urllib2.urlopen(url)print response1.getcode() #返回状态码print len(response1.read()) #返回的网页内容的长度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() #返回状态码print cj    #返回cookieprint response3.read()  #返回网页内容

Python有哪几种网页解析器：
正则表达式、html.parser、Beautiful Soup、lxml

BeautifulSoup：
　　- Python第三方库，用于从HTML或XML中提取数据
　　- 官网：http://www.crummy.com/software/BeautifulSoup/bs4/doc/

安装并测试beautifulsoup4：
　　- 安装：pip install beautifulsoup4
　　- 测试：import bs4

如果PyCharm无法识别beautifulsoup4，则在设置里找到Python Intercepter这一项，改为python2.7版本即可。

Demo2:

# coding:utf-8import refrom bs4 import BeautifulSoup# 示例代码片段(来自beautifulsoup官网)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()

实战编写爬取百度百科页面:

目录结构：

注：mac osx下用alt+enter添加相应方法

(爬虫调度器)spider_main.py:

# coding=utf-8from baike_spider import url_manager,html_downloader,html_parser,html_outputerclass SpiderMain(object):    def __init__(self):        self.urls = url_manager.UrlManager()    #url管理器        self.downloader = html_downloader.HtmlDownloader()  #下载器        self.parser = html_parser.HtmlParser()  #解析器        self.outputer = html_outputer.HtmlOutputer()    #输出器    def craw(self, root_url):        count = 1 #判断当前爬取的是第几个url        self.urls.add_new_url(root_url)        while self.urls.has_new_url():      #循环,爬取所有相关页面,判断异常情况            try:                new_url = self.urls.get_new_url()   #取得url                print 'craw %d : %s' % (count, new_url) #打印当前是第几个url                html_cont = self.downloader.download(new_url)   #下载页面数据                new_urls, new_data = self.parser.parse(new_url,html_cont)    #进行页面解析得到新的url以及数据                self.urls.add_new_urls(new_urls) #添加新的url                self.outputer.collect_data(new_data) #收集数据                if count == 10:  # 此处10可以改为100甚至更多,代表循环次数                    break                count = count + 1            except:                print 'craw failed'        self.outputer.output_html()   #利用outputer输出收集好的数据if __name__=="__main__":    root_url = "http://baike.baidu.com/view/21087.htm"    obj_spider = SpiderMain()   # 创建    obj_spider.craw(root_url)   # craw方法启动爬虫

(url管理器)url_manager.py:

# coding=utf-8class UrlManager(object):    def __init__(self):         self.new_urls = set()  # 待爬取url         self.old_urls = set()  # 已爬取url    def add_new_url(self, url):    # 向管理器中添加一个新的url        if url is None:            return        if url not in self.new_urls and url not in self.old_urls:            self.new_urls.add(url)    def add_new_urls(self, urls): # 向管理器中添加新的更多的url        if urls is None or len(urls) == 0:            return        for url in urls:            self.add_new_url(url)    def has_new_url(self):  # 判断管理器是否有新的待爬取的url        return len(self.new_urls) != 0    def get_new_url(self):  # 从管理器中获取一个新的待爬取的url        new_url = self.new_urls.pop()        self.old_urls.add(new_url)        return new_url

(下载器)html_downloader.py:

import urllib2class HtmlDownloader(object):    def download(self, url):        if url is None:            return None        response = urllib2.urlopen(url)        if response.getcode() != 200:            return None        return response.read()

(解析器)html_parser.py:

import reimport urlparsefrom bs4 import BeautifulSoupclass HtmlParser(object):    def parse(self,page_url,html_cont):        if page_url is None or html_cont is None:            return        soup = BeautifulSoup(html_cont,'html.parser', from_encoding='utf-8')        new_urls = self._get_new_urls(page_url, soup)        new_data = self._get_new_data(page_url, soup)        return new_urls, new_data    def _get_new_urls(self, page_url, soup):        new_urls = set()        # /view/123.htm        links = soup.find_all('a', href=re.compile(r"/view/\d+\.htm"))        for link in links:            new_url = link['href']            new_full_url = urlparse.urljoin(page_url, new_url)            new_urls.add(new_full_url)        return new_urls    def _get_new_data(self, page_url, soup):        res_data = {}        # url        res_data['url'] = page_url        # <dd class="lemmaWgt-lemmaTitle-title"> <h1>Python</h1>        title_node = soup.find('dd',class_="lemmaWgt-lemmaTitle-title").find("h1")        res_data['title'] = title_node.get_text()        # <div class="lemma-summary" label-module="lemmaSummary">        summary_node = soup.find('div',class_="lemma-summary")        res_data['summary'] = summary_node.get_text()        return res_data

(数据输出)html_outputer.py:

# coding=utf-8class HtmlOutputer(object):    #初始化    def __init__(self):        self.datas = []    def collect_data(self, data):   #收集数据        if data is None:            return        self.datas.append(data)    def output_html(self):  #输出数据        fout = open('output.html', 'w')        fout.write("<html>")        fout.write("<head>")        fout.write("<meta charset= 'UTF-8'>")        fout.write("</head>")        fout.write("<body>")        fout.write("<table>")        # ASCII        for data in self.datas:            fout.write("<tr>")            fout.write("<td>%s</td>" % data['url'])            fout.write("<td>%s</td>" % data['title'].encode('utf-8'))            fout.write("<td>%s</td>" % data['summary'].encode('utf-8'))            fout.write("</tr>")        fout.write("</html>")        fout.write("</body>")        fout.write("</table>")        fout.close()

运行程序spider_main.py可进行爬取页面，最终文件输出为output.html,里面包含词条和词条解释，爬取完毕。

output.html:

这只是最简单的爬虫，如果想深入学习，还有登录、验证码、Ajax、服务器防爬虫、多线程、分布式等等。

GitHub:https://github.com/AbelSu131/baike_spider

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