简单Python爬虫实例

来源：互联网发布：事业单位域名注册编辑：程序博客网时间：2024/06/07 09:12

简介：

阅读百度百科，可以发现每个词条页面都会有许多相关联的词条，所以编写一款爬虫程序用来爬某个词条页面的相关联的词条，输出起链接、词条名称和词条简介。此次程序目标为爬去“Python”词条百度百科的100条相关联词条。

分析：

目标：百度百科Python词条相关词条页面-标题和简介

入口页：http://baike.baidu.com/view/21087.html

URL格式：

-词条页面URL：/view/20965.htm

数据格式：

-标题:<ddclass="lemmaWgt-lemmaTitle-title"><h1>****</h1></dd>

-简介:<divclass="lemma-summary"><divclass="para">****</div></div>

页面编码：UTF-8

实现：

程序由一个主程序和4个工具类（URL管理类、HTML下载类、HTML解析类、HTML输出类）组成。

主程序

# coding:utf8import url_managerimport html_downloaderimport html_parserimport html_outputer# 目标：百度百科Python词条相关词条页面-标题和简介# 入口页：http://baike.baidu.com/view/21087.html# URL格式：# -词条页面URL：/view/20965.htm# 数据格式：# -标题:<dd class="lemmaWgt-lemmaTitle-title"><h1>****</h1></dd># -简介:<div class="lemma-summary"><div class="para">****</div></div># 页面编码：UTF-8class SpiderMain(object):def __init__(self):self.urls = url_manager.UrlManager()self.downloader = html_downloader.HtmlDownloader()self.parser = html_parser.HtmlParser()self.outputer = html_outputer.HtmlOutputer()def craw(self, root_url):count = 1self.urls.add_new_url(root_url)while self.urls.has_new_url():try:new_url = self.urls.get_new_url()print("craw %d : %s" %(count, new_url))html_cont = self.downloader.download(new_url)new_urls, new_data = self.parser.parse(new_url, html_cont)self.urls.add_new_urls(new_urls)self.outputer.collect_data(new_data)if count == 100:breakcount = count +1except:print("craw failed!")self.outputer.output_html()if __name__=="__main__":root_url = "http://baike.baidu.com/view/21087.html"obj_spider = SpiderMain()obj_spider.craw(root_url)

URL管理类

# coding:utf8class UrlManager(object):"""docstring for UrlManager"""def __init__(self):self.new_urls = set()self.old_urls = set()def add_new_url(self, url):if url is None:returnif url not in self.new_urls and url not in self.old_urls:self.new_urls.add(url)def add_new_urls(self, urls):if urls is None or len(urls) == 0:returnfor url in urls:self.add_new_url(url)def has_new_url(self):return len(self.new_urls) != 0def get_new_url(self):new_url = self.new_urls.pop()self.old_urls.add(new_url)return new_url

HTML下载类

# coding:utf8import urllib.requestclass HtmlDownloader(object):"""docstring for HtmlDownloader"""# def __init__(self, arg):# super(HtmlDownloader, self).__init__()# self.arg = argdef download(self, url):if url is None:return Noneresponse = urllib.request.urlopen(url)if response.getcode() != 200:return Nonereturn response.read()

HTML解析类

# coding:utf8from bs4 import BeautifulSoupimport reimport urllib.parseclass HtmlParser(object):"""docstring for HtmlParser"""# def __init__(self, arg):# super(HtmlParser, self).__init__()# self.arg = argdef _get_new_urls(self, page_url, soup):new_urls = set()links = soup.find_all('a', href=re.compile(r"/view/\d+\.htm"))for link in links:new_url = link['href']new_full_url = urllib.parse.urljoin(page_url, new_url)new_urls.add(new_full_url)return new_urlsdef _get_new_data(self, page_url, soup):res_data = {}res_data['url'] = page_urltitle_node = soup.find('dd', class_="lemmaWgt-lemmaTitle-title").find('h1')res_data['title'] = title_node.get_text()summary_node = soup.find('div', class_="lemma-summary")res_data['summary'] = summary_node.get_text()return res_datadef parse(self, page_url, html_cont):if page_url is None or html_cont is None:returnsoup = 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

HTML输出类

# coding:utf8class HtmlOutputer(object):"""docstring for HtmlOutputer"""def __init__(self):self.datas = []def collect_data(self, data):if data is None:returnself.datas.append(data)def output_html(self):fout = open('output.html', 'w' ,encoding='utf-8')fout.write("<!DOCTYPE html>")fout.write('<html lang="en">')fout.write("<head>")fout.write('<meta charset="UTF-8">')fout.write("<title>GrabPython百科</title>")fout.write("</head>")fout.write("<body>")fout.write("<table>")for data in self.datas:fout.write("<tr>")fout.write('<td><a href="%s">%s</a></td>' %(data['url'], data['url']))fout.write("<td>%s</td>" %(data['title']))fout.write("<td>%s</td>" %(data['summary']))fout.write("</tr>")fout.write("</table>")fout.write("</body>")fout.write("</html>")

程序运行流程：

将入口URL加入URL管理类》

从URL管理类获取一条URL并转发给HTML下载类》

HTML下载类处理获取HTML并转发给HTML解析类》

HTML解析类处理获得新的URLs和Data，并将URLs加入URL管理器类，将Data转发给HTML输出类存储数据

最后数据获取完后，由HTML输出类把获取的数据以html页面的形式输出

技术：

URL管理类用到了set的数据结构存储URL，其特点是不能有重复

HTML下载类用到了Python3自带的urllib.request库，可实现简单爬去网页的功能

HTML解析类用到了自带urllib.parse和re两个库分别处理url和匹配获取页面内容，还引用了一个第三方库BeautifulSoup，用于结构化存取HTML

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