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python爬虫爬取淘宝商品信息(selenum+phontomjs)

时间:2021-01-17 01:03     来源/作者:开心果汁

本文实例为大家分享了python爬虫爬取淘宝商品的具体代码,供大家参考,具体内容如下

1、需求目标

进去淘宝页面,搜索耐克关键词,抓取 商品的标题,链接,价格,城市,旺旺号,付款人数,进去第二层,抓取商品的销售量,款号等。

python爬虫爬取淘宝商品信息(selenum+phontomjs)

python爬虫爬取淘宝商品信息(selenum+phontomjs)

python爬虫爬取淘宝商品信息(selenum+phontomjs)

2、结果展示

python爬虫爬取淘宝商品信息(selenum+phontomjs)

3、源代码

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# encoding: utf-8
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import time
import pandas as pd
time1=time.time()
from lxml import etree
from selenium import webdriver
#########自动模拟
driver=webdriver.phantomjs(executable_path='d:/python27/scripts/phantomjs.exe')
import re
 
#################定义列表存储#############
title=[]
price=[]
city=[]
shop_name=[]
num=[]
link=[]
sale=[]
number=[]
 
#####输入关键词耐克(这里必须用unicode)
keyword="%e8%80%90%e5%85%8b"
 
 
for i in range(0,1):
 
  try:
    print "...............正在抓取第"+str(i)+"页..........................."
 
    url="https://s.taobao.com/search?q=%e8%80%90%e5%85%8b&imgfile=&js=1&stats_click=search_radio_all%3a1&initiative_id=staobaoz_20170710&ie=utf8&bcoffset=4&ntoffset=4&p4ppushleft=1%2c48&s="+str(i*44)
    driver.get(url)
    time.sleep(5)
    html=driver.page_source
 
    selector=etree.html(html)
    title1=selector.xpath('//div[@class="row row-2 title"]/a')
    for each in title1:
      print each.xpath('string(.)').strip()
      title.append(each.xpath('string(.)').strip())
 
 
    price1=selector.xpath('//div[@class="price g_price g_price-highlight"]/strong/text()')
    for each in price1:
      print each
      price.append(each)
 
 
    city1=selector.xpath('//div[@class="location"]/text()')
    for each in city1:
      print each
      city.append(each)
 
 
    num1=selector.xpath('//div[@class="deal-cnt"]/text()')
    for each in num1:
      print each
      num.append(each)
 
 
    shop_name1=selector.xpath('//div[@class="shop"]/a/span[2]/text()')
    for each in shop_name1:
      print each
      shop_name.append(each)
 
 
    link1=selector.xpath('//div[@class="row row-2 title"]/a/@href')
    for each in link1:
      kk="https://" + each
 
 
      link.append("https://" + each)
      if "https" in each:
        print each
 
        driver.get(each)
      else:
        print "https://" + each
        driver.get("https://" + each)
      time.sleep(3)
      html2=driver.page_source
      selector2=etree.html(html2)
 
      sale1=selector2.xpath('//*[@id="j_detailmeta"]/div[1]/div[1]/div/ul/li[1]/div/span[2]/text()')
      for each in sale1:
        print each
        sale.append(each)
 
      sale2=selector2.xpath('//strong[@id="j_sellcounter"]/text()')
      for each in sale2:
        print each
        sale.append(each)
 
      if "tmall" in kk:
        number1 = re.findall('<ul id="j_attrul">(.*?)</ul>', html2, re.s)
        for each in number1:
          m = re.findall('>*号: (.*?)</li>', str(each).strip(), re.s)
          if len(m) > 0:
            for each1 in m:
              print each1
              number.append(each1)
 
          else:
            number.append("null")
 
      if "taobao" in kk:
        number2=re.findall('<ul class="attributes-list">(.*?)</ul>',html2,re.s)
        for each in number2:
          h=re.findall('>*号: (.*?)</li>', str(each).strip(), re.s)
          if len(m) > 0:
            for each2 in h:
              print each2
              number.append(each2)
 
          else:
            number.append("null")
 
      if "click" in kk:
        number.append("null")
 
  except:
    pass
 
 
print len(title),len(city),len(price),len(num),len(shop_name),len(link),len(sale),len(number)
 
# #
# ######数据框
data1=pd.dataframe({"标题":title,"价格":price,"旺旺":shop_name,"城市":city,"付款人数":num,"链接":link,"销量":sale,"款号":number})
print data1
# 写出excel
writer = pd.excelwriter(r'c:\\taobao_spider2.xlsx', engine='xlsxwriter', options={'strings_to_urls': false})
data1.to_excel(writer, index=false)
writer.close()
 
time2 = time.time()
print u'ok,爬虫结束!'
print u'总共耗时:' + str(time2 - time1) + 's'
####关闭浏览器
driver.close()

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持服务器之家。

原文链接:http://blog.csdn.net/u013421629/article/details/74960278

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