python爬虫 可以跳过登录界面,成功爬取淘宝商品信息,就这么简单!!!

修改request的headers属性,可以跳过登录界面,成功爬取淘宝商品信息

备注:先安装Python3.X以上开发环境,在执行下面步骤 (百度有很多安装环境文章)

功能描述:目标:获取淘宝搜索页面信息,提取其中商品的名称、价格、图片链接、商品地址、付款人数生成csv格式导出数据

技术路线:Requests-Re

接口描述:

搜索接口:https://s.taobao.com/search?q=短裙

翻页接口:第二页 https://s.taobao.com/search?q=短裙&s=44×2

第三页 https://s.taobao.com/search?q=短裙&s=44×3

程序结构设计:

步骤1:提交商品请求,循环获取页面

步骤2:对于每一个页面,提取其中商品的名称、价格、图片链接、商品地址、付款人数

步骤3:将数据信息输出到csv文件

代码实现:

用爬虫爬淘宝,得到的页面是登录页面,需要“假登录”,获取头部headers信息,作为参数传给requests.get(url,headers = header),获取方法如下

详细步骤:以Google浏览器为例

1.登录淘宝,进入搜索页,F12

2.选择Network,刷新一下,找到最上方以search?开头的文件,鼠标右键

3.选择copy,copy as cURL(bush)

4.在curl.trillworks.com/,将上一步复制的内容粘贴到curl command窗口

5.复制右侧的headers内容,在程序中用以变量header保存,作为参数传给requests.get(url,headers=header)

关键部分上代码:

#获取淘宝商品信息

import requests

import csv

import os

import pandas as pd

import time

import re

def getHtmlText(url):

try:

header = {

‘authority’: ‘s.taobao.com‘,

‘cache-control’: ‘max-age=0’,

‘sec-ch-ua’: ‘”Chromium”;v=”92″, ” Not A;Brand”;v=”99″, “Google Chrome”;v=”92″‘,

‘sec-ch-ua-mobile’: ‘?0’,

‘upgrade-insecure-requests’: ‘1’,

‘user-agent’: ‘Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.159 Safari/537.36’,

‘accept’: ‘text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9’,

‘sec-fetch-site’: ‘same-origin’,

‘sec-fetch-mode’: ‘navigate’,

‘sec-fetch-user’: ‘?1’,

‘sec-fetch-dest’: ‘document’,

‘referer’: ,

‘accept-language’: ‘zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7’,

‘cookie’: ,

}#隐去了cookie信息和referer信息,你可以登陆淘宝账号获取方法在文章代码实现步骤4

param = (

(‘q’, ‘\u77ED\u88D9’),

(‘imgfile’, ”),

(‘js’, ‘1’),

(‘stats_click’, ‘search_radio_all:1’),

(‘initiative_id’, ‘staobaoz_20211012’),

(‘ie’, ‘utf8’),

)

r = requests.get(url, headers = header, params = param)

r.raise_for_status()

r.encoding = r.apparent_encoding

return r.text

except:

print(“爬取失败”)

return “”

def parsePage(ilist,html):

try:

plt = re.findall(r’\”view_price\”:\”\d+\.\d*\”‘,html)

tlt = re.findall(r’\”raw_title\”:\”.*?\”‘,html)

loc = re.findall(r’\”item_loc\”\:\”.*?\”‘,html)

sale = re.findall(r’\”view_sales\”\:\”[\d\.]*.*?\”‘,html)

img = re.findall(r’\”pic_url\”\:\”.*?\”‘, html)

# imgd = re.findall(r’\”detail_url\”\:\”.*?\”‘, html)

# print(img)

# print(len(plt))

for i in range(len(plt)):

price = eval(plt[i].split(‘\”‘)[3])

title = tlt[i].split(‘\”‘)[3]

location = eval(loc[i].split(‘:’)[1])

sales = eval(sale[i].split(‘:’)[1])

image = img[i].split(“:”)[1]

# imaged = imgd[i].split(“:”)[1]

ilist.append([title,price,image,location,sales])

# print(ilist)

except:

print(“解析出错”)

def printGoodsList(ilist,num,goods,depth):

tplt = “{0:<3}\t{1:<30}\t{2:>6}”

print(tplt.format(“序号”,”商品名称”,”价格”))

count = 0

# 二维数组首位添加元素

ilist.insert(0,[“商品名称”,”价格”,”图片URL”,”地址”,”付款数”])

# 数据导出

for i in range(len(ilist)):

f = open(str(goods)+str(depth)+’.csv’, ‘a+’,newline=”)

writer = csv.writer(f)

writer.writerow(ilist[i])

f.close()

print(“写入成功”)

def main():

goods = “连衣裙”

depth = 2

start_url = “s.taobao.com/search?“+goods

infoList = []

num = 20

for i in range(depth):

try:

url = start_url + ‘&S=’ + str(44*i)

html = getHtmlText(url)

parsePage(infoList,html)

except:

continue

printGoodsList(infoList,num,goods,depth)

main()

得出数据如图:

备注:要配只好本地开发环境哦