Python爬虫爬取、解析数据操作示例
本文实例讲述了Python爬虫爬取、解析数据操作。分享给大家供大家参考,具体如下:
爬虫 当当网 http://search.dangdang.com/?key=python&act=input&page_index=1
- 获取书籍相关信息
- 面向对象思想
- 利用不同解析方式和存储方式
引用相关库
import requests import re import csv import pymysql from bs4 import BeautifulSoup from lxml import etree import lxml from lxml import html
类代码实现部分
class DDSpider(object): #对象属性 参数 关键字 页数 def __init__(self,key='python',page=1): self.url = 'http://search.dangdang.com/?key='+key+'&act=input&page_index={}' self.page = page self.headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.116 Safari/537.36'} #私有对象方法 def __my_url(self): my_url = [] if self.page < 1: my_page = 2 else: my_page = self.page+1 #循环遍历每一页 for i in range(1,my_page): my_url.append(self.url.format(i)) return my_url #私有对象方法 请求数据 def __my_request(self,url,parser_type): #循环遍历每一页 response = requests.get(url=url,headers=self.headers) if response.status_code == 200: return self.__my_parser(response.text,parser_type) else: return None #私有对象方法 解析数据 1 利用正则 2 bs4 3 xpath def __my_parser(self,html,my_type=1): if my_type == 1: pattern = re.compile('<p.*?class=[\'\"]name[\'\"].*?name=[\'\"]title[\'\"].*?<a.*?title=[\'\"](.*?)[\'\"].*?href=[\'\"](.*?)[\'\"].*?name=[\'\"]itemlist-title[\'\"].*?<p class=[\'\"]detail[\'\"].*?>(.*?)</p>.*?<span.*?class=[\'\"]search_now_price[\'\"].*?>(.*?)</span>.*?<p.*?class=[\'\"]search_book_author[\'\"].*?><span>.*?<a.*?name=[\'\"]itemlist-author[\'\"].*?title=[\'\"](.*?)[\'\"].*?</span>',re.S) result = re.findall(pattern,html) elif my_type == 2: soup = BeautifulSoup(html,'lxml') result = [] title_url = soup.find_all('a',attrs={'name':'itemlist-title'}) for i in range(0,len(title_url)): title = soup.find_all('a',attrs={'name':'itemlist-title'})[i].attrs['title'] url = soup.find_all('a',attrs={'name':'itemlist-title'})[i].attrs['href'] price = soup.find_all('span',attrs={'class':'search_now_price'})[i].get_text() author = soup.find_all('a',attrs={'name':'itemlist-author'})[i].attrs['title'] desc = soup.find_all('p',attrs={'class':'detail'})[i].get_text() my_tuple = (title,url,desc,price,author) result.append(my_tuple) else: html = etree.HTML(html) li_all = html.xpath('//div[@id="search_nature_rg"]/ul/li') result = [] for i in range(len(li_all)): title = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="name"]/a/@title'.format(i+1)) url = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="name"]/a/@href'.format(i+1)) price = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]//span[@class="search_now_price"]/text()'.format(i+1)) author_num = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="search_book_author"]/span[1]/a'.format(i+1)) if len(author_num) != 0: #有作者 a标签 author = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="search_book_author"]/span[1]/a[1]/@title'.format(i+1)) else: #没有作者 a标签 author = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="search_book_author"]/span[1]/text()'.format(i+1)) desc = html.xpath('//div[@id="search_nature_rg"]/ul/li[{}]/p[@class="detail"]/text()'.format(i+1)) my_tuple = (" ".join(title)," ".join(url)," ".join(desc)," ".join(price)," ".join(author)) result.append(my_tuple) return result #私有对象方法 存储数据 1 txt 2 csv 3 mysql def __my_save(self,data,save_type=1): #循环遍历 for value in data: if save_type == 1: with open('ddw.txt','a+',encoding="utf-8") as f: f.write('【名称】:{}【作者】:{}【价格】:{}【简介】:{}【链接】:{}'.format(value[0],value[4],value[3],value[2],value[1])) elif save_type == 2: with open('ddw.csv','a+',newline='',encoding='utf-8-sig') as f: writer = csv.writer(f) #转化为列表 存储 writer.writerow(list(value)) else: conn = pymysql.connect(host='127.0.0.1',user='root',passwd='',db='',port=3306,charset='utf8') cursor = conn.cursor() sql = '' cursor.execute(sql) conn.commit() cursor.close() conn.close() #公有对象方法 执行所有爬虫操作 def my_run(self,parser_type=1,save_type=1): my_url = self.__my_url() for value in my_url: result = self.__my_request(value,parser_type) self.__my_save(result,save_type)
调用爬虫类实现数据获取
if __name__ == '__main__': #实例化创建对象 dd = DDSpider('python',0) #参数 解析方式 my_run(parser_type,save_type) # parser_type 1 利用正则 2 bs4 3 xpath #存储方式 save_type 1 txt 2 csv 3 mysql dd.my_run(2,1)
==总结一下: ==
1. 总体感觉正则表达式更简便一些 , 代码也会更简便 , 但是正则部分相对复杂和困难
2. bs4和xpath 需要对html代码有一定了解 , 取每条数据多个值时相对较繁琐
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希望本文所述对大家Python程序设计有所帮助。
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