python爬虫学习hellow world

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慕课网《python开发简单爬虫》代码记录

一、url下载器部分

#encoding=utf-8import cookielibimport urllib2import urllibimport osimport BeautifulSoupurl = "http://www.baidu.com"print '测试第一种方法'response1 = urllib2.urlopen(url)    #获取的内容返回给对象print response1.getcode()  #状态码是否为200，判断是否成功print len(response1.read()) #网页内容长度 read方法读取内容print '测试第二种方法' #伪装成浏览器request = urllib2.Request(url)  #生成request对象request.add_header("user-agent","Mozilla/5.0") #将爬虫伪装成一个浏览器response2 = urllib2.urlopen(request)    #提交网页下载请求print response2.getcode()print len(response2.read())print '测试第三种方法' #引入cookie增加处理情景的能力cj = cookielib.CookieJar() #建立个cookie的容器opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))#以容器作为参数创建一个handler，作为opener的参数urllib2.install_opener(opener)  #增强处理能力，给urllib2安装openerresponse3 = urllib2.urlopen(url)print response3.getcode()print cjprint response3.read()

二、网页解析器部分—beautiful soup

#encoding=utf-8from bs4 import BeautifulSoupimport rehtml_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>  """ #根据HTML网页字符中创建BeautifulSoup对象soup = BeautifulSoup( html_doc, 'html.parser', from_encoding = 'utf8' )   #HTML文档字串， HTML解析器，HTML文档的编码print '获取所有链接'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()

三、python编写爬虫实例

制订抓取策略

目标：百度百科python词条相关词条网页——标题和简介
入口页：https://baike.baidu.com/item/Python
URL格式：
-词条页面URL:/view/125370.htm(非完整URL)
数据格式：
页面编码：UTF-8

代码部分

url管理器

# coding:utf8class UrlManager(object):  # 维护两个Url列表    def __init__(self):        self.new_urls = set()        self.old_urls = set()    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):  # 向管理器中添加批量Url        if urls is None or len(urls) == 0:            return        for url in urls:            self.add_new_url(url)    def has_new_url(self):  # 判断管理器中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

html下载器

# coding:utf8import urllib2class HtmlDownloader(object):    def download(self, url):        if url is None:            return None        response = urllib2.urlopen(url)     # 由于要爬取内容简单，此处使用urllib2最简单的方法        if response.getcode() != 200:            return None        return response.read()

url解析器

# coding:utf8import reimport urlparsefrom bs4 import BeautifulSoupclass HtmlParser(object):    def _get_new_urls(self, page_url, soup):    # 获取页面中所有其他词条的Url        new_urls = set()        # 获取所有的连接 /view/123.htm        links = soup.find_all('a', href=re.compile(r"/item"))        for link in links:            new_url = link['href']            new_full_url = urlparse.urljoin(page_url, new_url)  # 按照page_url的格式，拼接成完全的url            new_urls.add(new_full_url)        return new_urls    def _get_new_data(self, page_url, soup):  # 解析数据 title summery        res_data = {}          # 建立字典存储数据        # url放入数据中，便于后续使用        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">        summary_node = soup.find('div', class_="lemma-summary")        res_data['summary'] = summary_node.get_text()        return res_data    def parse(self, page_url, html_cont):  # 从cont中解析出两个数据，新的url列表和数据        if page_url is None or html_cont is None:            return        soup = BeautifulSoup(html_cont, 'html.parser', from_encoding='utf-8') # 将cont加载近soup        # 两个链接        new_urls = self._get_new_urls(page_url, soup)        new_data = self._get_new_data(page_url, soup)        return new_urls, new_data

html输出器

# coding:utf8class HtmlOutputer(object):    def __init__(self):        self.datas = []    def collect_data(self, data):        if data is None:            return        self.datas.append(data)    def output_html(self):        fout = open('output.html', 'w')   # 建立文件输出对象        # 标签        fout.write("<html>")        fout.write("<head><meta charset=\"utf-8\"></head>")        fout.write("<body>")        fout.write("<table>") # 以表格的形式输出        #ascii        for data in self.datas:            fout.write("<tr>")#行的开始标签            fout.write("<td>%s</td>" % data['url'])            fout.write("<td>%s</td>" % data['title'].encode('utf-8').decode("utf-8"))            fout.write("<td>%s</td>" % data['summary'].encode('utf-8').decode("utf-8"))            fout.write("</tr>")        #闭合标签        fout.write("</table>")        fout.write("</body>")        fout.write("</html>")        fout.close()

main

# coding:utf8import url_manager, html_downloader, html_parser, html_outputerclass 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):  # 爬虫的调度程序        count = 1 # 记录当前爬取的Url        self.urls.add_new_url(root_url)        while self.urls.has_new_url():  # url管理器中有待爬取的Url时            try:    # 有的网页无要爬取内容                new_url = self.urls.get_new_url()   # 获取一个                print 'craw %d : %s ' % (count, new_url)                html_cont = self.downloader.download(new_url)  # 下载页面，结果存储                new_urls, new_data = self.parser.parse(new_url, html_cont)  # 解析器，得到新的Url列表以及新的数据                self.urls.add_new_urls(new_urls)    # 添加进Url管理器（批量）                self.outputer.collect_data(new_data)  # 收集数据                if count == 20:                    break                count = count + 1            except:                print 'craw failed'        self.outputer.output_html()if __name__ == "__main__":    root_url = "https://baike.baidu.com/view/21087.htm"    obj_spider = SpiderMain()    obj_spider.craw(root_url)

注：
匹配形式需随网站的url形式的改变调整。

附：
python 正则表达式
http://www.runoob.com/python/python-reg-expressions.html
http://www.cnblogs.com/huxi/archive/2010/07/04/1771073.htm
pycharm快捷键
http://www.cnblogs.com/littleseven/p/5599019.html
解决爬取网站内容乱码问题
http://blog.csdn.net/github_35160620/article/details/52529435

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