requests和lxml实现爬虫的方法

如下所示：

# 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//div[@class='feed-item _j_feed_item']/a/@href')

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

# python 2.7
import requests
from lxml import html
import os

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

# get title from a child's html(div[@class='title'])
def get_page_a_title(url):
 '''url is ziyouxing's a@href'''
 response = requests.get(url).content
 selector = html.fromstring(response)
 # get xpath by chrome's tool --> /html/body//div[@class='title']/text()
 a_title = selector.xpath("/html/body//div[@class='title']/text()")
 return a_title

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

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

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

# 获取图片的标题

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

# 下载图片

def downloadimages(selector,number):
 '''number是用来计数的'''
 urls = get_image_urls()
 num = 2
 amount = len(urls)
 for url in urls:
   image_title = get_image_title(selector, num)
   filename = "/home/WorkSpace/tour/words/result"+number+"/+"image_title+".jpg"
   if not os.path.exists(filename):
     os.makedirs(filename)
   print('downloading ％s image ％s' ％(number, image_title))
   with open(filename, 'wb') as f:
     f.write(requests.get(url).content)
   num += 1
 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 = 'https://www.mafengwo.cn/gonglve/ziyouxing/2033.html'
 urls = get_page_urls(url)
 # turn to get response from html
 number = 1
 for i in urls:
   selector = get_selector(i)
   # download images
   downloadimages(selector,number)
   # get text and write into a file
   page_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