# requests模块来请求页面
# lxml模块的html构建selector选择器(格式化响应response)
# from lxml import html
# import requests

# response = requests.get(url).content

# selector = html.formatstring(response)

# hrefs = selector.xpath('/html/body//p[@class='feed-item _j_feed_item']/a/@href')

# 以url = 'https://www.mafengwo.cn/gonglve/ziyouxing/2033.html'为例子

# python 2.7import requestsfrom lxml import htmlimport os

1 # 获取首页中子页的url链接2 def get_page_urls(url):3     response = requests.get(url).content4     # 通过lxml的html来构建选择器5     selector = html.fromstring(response)6     urls = []7     for i in selector.xpath("/html/body//p[@class='feed-item _j_feed_item']/a/@href"):8         urls.append(i)9     return urls

1 # get title from a child's html(p[@class='title'])2 def get_page_a_title(url):3     '''url is ziyouxing's a@href'''4     response = requests.get(url).content5     selector = html.fromstring(response)6     # get xpath by chrome's tool  -->  /html/body//p[@class='title']/text()7     a_title = selector.xpath("/html/body//p[@class='title']/text()")8     return a_title

 1 # 获取页面选择器(通过lxml的html构建) 2 def get_selector(url): 3     response = requests.get(url).content 4     selector = html.fromstring(response) 5     return selector

# 通过chrome的开发者工具分析html页面结构后发现，我们需要获取的文本内容主要显示在p[@class='l-topic']和p[@class='p-section']中

1  # 获取所需的文本内容2  def get_page_content(selector):3      # /html/body/p[2]/p[2]/p[1]/p[@class='l-topic']/p/text()4      page_title = selector.xpath("//p[@class='l-topic']/p/text()")5      # /html/body/p[2]/p[2]/p[1]/p[2]/p[15]/p[@class='p-section']/text()6      page_content = selector.xpath("//p[@class='p-section']/text()")7      return page_title,page_content

1 # 获取页面中的图片url地址2 def get_image_urls(selector):3     imagesrcs = selector.xpath("//img[@class='_j_lazyload']/@src")4     return imagesrcs

  # 获取图片的标题

1 def get_image_title(selector, num)2     # num 是从2开始的3     url = "/html/body/p[2]/p[2]/p[1]/p[2]/p["+num+"]/span[@class='img-an']/text()"4     if selector.xpath(url) is not None:5         image_title = selector.xpath(url)6     else:7         image_title = "map"+str(num) # 没有就起一个8     return image_title

  # 下载图片

 1 def downloadimages(selector,number): 2     '''number是用来计数的''' 3     urls = get_image_urls() 4     num = 2 5     amount = len(urls) 6     for url in urls: 7         image_title = get_image_title(selector, num) 8         filename = "/home/WorkSpace/tour/words/result"+number+"/+"image_title+".jpg" 9         if not os.path.exists(filename):10             os.makedirs(filename)11         print('downloading %s image %s' %(number, image_title))12         with open(filename, 'wb') as f:13             f.write(requests.get(url).content)14         num += 115     print "已经下载了%s张图" %num

# 入口，启动并把获取的数据存入文件中if __name__ =='__main__':    url = ''urls = get_page_urls(url)# turn to get response from htmlnumber = 1for i in urls:        selector = get_selector(i)# download images      downloadimages(selector,number)# get text and write into a filepage_title, page_content = get_page_content(selector)        result = page_title+'\n'+page_content+'\n\n'path = "/home/WorkSpace/tour/words/result"+num+"/"if not os.path.exists(filename):            os.makedirs(filename)        filename = path + "num"+".txt"with open(filename,'wb') as f:            f.write(result)print result

到此就结束了该爬虫，爬取页面前一定要认真分析html结构，有些页面是由js生成，该页面比较简单，没涉及到js的处理，日后的随笔中会有相关分享