# response = requests.get(url).content

# selector = html.formatstring(response)

# hrefs = selector.xpath('/html/body//div[@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//div[@class='feed-item _j_feed_item']/a/@href"):8 urls.append(i)9 return urls

1 # get title from a child's html(div[@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//div[@class='title']/text()7 a_title = selector.xpath("/html/body//div[@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div[@class='l-topic']和div[@class='p-section']中

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

'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