只需要替换原来的Cookie和token即可使用，自动计算对应链接地址的sign直接使用即可。需要注意是一个账号爬取过多会有验证码
import json
import hashlib
import random
import time
import pandas as pd
import requests
results = []
def fetch_review_list(datas, md5_hash,t):
url = "https://h5api.m.tmall.com/h5/mtop.alibaba.review.list.for.new.pc.detail/1.0/"
params = {
"jsv": "2.7.2",
"appKey": "12574478",
"t": t, # 使用当前时间戳
"sign": md5_hash, # 请替换为实际的签名值
"api": "mtop.alibaba.review.list.for.new.pc.detail",
"v": "1.0",
"isSec": "0",
"ecode": "0",
"timeout": "20000",
"ttid": "2022@taobao_litepc_9.17.0",
"AntiFlood": "true",
"AntiCreep": "true",
"preventFallback": "true",
"type": "jsonp",
"dataType": "jsonp",
"callback": "mtopjsonp6",
"data": datas
}
# 设置 headers
headers = {
"Cookie": "自己的"
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/125.0.0.0 Safari/537.36",
"Referer": "https://detail.tmall.com/",
"Accept": "*/*",
"Connection": "keep-alive"
}
response = requests.get(url, params=params, headers=headers)
print(response.text)
json_content = json.loads(response.text.replace("mtopjsonp6(", "").replace("})", "}"))
# 获取评论区
counten = json_content['data']['module']['reviewVOList']
rulist =[]
for i in counten:
pinglun = i['reviewWordContent']
rulist.append(pinglun)
return rulist
def taobao(sign, datas, appkey, t,coci):
# 构造 URL 和参数
url = "https://h5api.m.taobao.com/h5/mtop.relationrecommend.wirelessrecommend.recommend/2.0/"
params = {
"jsv": "2.7.0",
"appKey": appkey,
"t": t,
"sign": sign,
"api": "mtop.relationrecommend.WirelessRecommend.recommend",
"v": "2.0",
"H5Request": "true",
"preventFallback": "true",
"type": "jsonp",
"dataType": "jsonp",
"callback": "mtopjsonp2",
"data": datas
}
# 设置 headers
headers = {
"Cookie": coci,
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
"Referer": "https://h5.m.taobao.com/",
"Accept": "*/*",
"Connection": "keep-alive"
}
# 发起请求
response = requests.get(url, headers=headers, params=params)
# 确保请求成功
if response.status_code == 200:
content = response.text.replace("mtopjsonp2(", "").replace("})", "}")
# 检查响应内容是否为空
if content.strip():
# 解析JSON字符串
try:
json_content = json.loads(content)
# 获取指定的JSON内容
name = json_content['data']['itemsArray']
for list in range(len(name)):
# 商品链接
product_url = name[list]['auctionURL']
pic_path = name[list]['pic_path']
title = name[list]['title']
print(title)
price = name[list]['priceShow']['price']
# 标签
tag = name[list]['structuredShopInfo']['infoList'][0]['text']
# 销量
sales = name[list]['realSales']
time.sleep(random.randint(1, 5))
# 获取评论区
# 商品id
pl_id = name[list]['item_id']
pl_token = "自己的token"
pl_t = str(1718204461753)
pl_appKey = "12574478"
pl_data = '{"itemId":"' + str(pl_id) + '","bizCode":"ali.china.tmall","channel":"pc_detail","pageSize":20,"pageNum":1}'
md5_hash = md5_encrypt(pl_token + "&" + pl_t + "&" + pl_appKey + "&" + pl_data)
print("获取评论区")
pinglunqu = fetch_review_list(pl_data, md5_hash,pl_t)
results.append([pl_id,product_url, pic_path, title, price, tag, sales,pinglunqu])
time.sleep( random.randint(1, 5))
except json.JSONDecodeError as e:
print(f"JSON解析错误: {e}")
except KeyError as e:
print(f"键错误: {e}")
except IndexError as e:
print(f"索引错误: {e}")
else:
print("响应内容为空")
else:
print(f"请求失败，状态码: {response.status_code}")
def md5_encrypt(data):
"""对给定的数据进行MD5加密"""
md5_obj = hashlib.md5()
md5_obj.update(data.encode('utf-8')) # 确保数据是字节类型
return md5_obj.hexdigest() # 返回16进制格式的哈希值
if __name__ == '__main__':
keyword = "碎花裙"
token = "自己的token"
t = str(int(time.time() * 1000))
appKey = "12574478"
coci="自己的Cookie"
for page in range(30, 50):
data = '{"appId":"29859","params":"{\\"isBeta\\":\\"false\\",\\"grayHair\\":\\"false\\",\\"appId\\":\\"29859\\",\\"from\\":\\"\\",\\"brand\\":\\"HUAWEI\\",\\"info\\":\\"wifi\\",\\"index\\":\\"4\\",\\"ttid\\":\\"600000@taobao_android_10.7.0\\",\\"needTabs\\":\\"true\\",\\"rainbow\\":\\"\\",\\"areaCode\\":\\"CN\\",\\"vm\\":\\"nw\\",\\"schemaType\\":\\"auction\\",\\"elderHome\\":\\"false\\",\\"device\\":\\"HMA-AL00\\",\\"isEnterSrpSearch\\":\\"true\\",\\"newSearch\\":\\"false\\",\\"network\\":\\"wifi\\",\\"subtype\\":\\"\\",\\"hasPreposeFilter\\":\\"false\\",\\"client_os\\":\\"Android\\",\\"gpsEnabled\\":\\"false\\",\\"searchDoorFrom\\":\\"srp\\",\\"debug_rerankNewOpenCard\\":\\"false\\",\\"homePageVersion\\":\\"v7\\",\\"searchElderHomeOpen\\":\\"false\\",\\"style\\":\\"wf\\",\\"page\\":' + str(
page) + ',\\"n\\":\\"10\\",\\"q\\":\\"' + keyword + '\\",\\"search_action\\":\\"initiative\\",\\"sugg\\":\\"_4_1\\",\\"m\\":\\"h5\\",\\"sversion\\":\\"13.6\\",\\"prepositionVersion\\":\\"v2\\",\\"tab\\":\\"all\\",\\"channelSrp\\":\\"\\",\\"tagSearchKeyword\\":null,\\"sort\\":\\"_sale\\",\\"filterTag\\":\\"\\",\\"prop\\":\\"\\",\\"item_id\\":\\"\\\"}"}'
md5_hash = md5_encrypt(token + "&" + t + "&" + appKey + "&" + data)
print(page)
taobao(md5_hash, data, appKey, t,coci)
df = pd.DataFrame(results, columns=['商品id','商品链接', '图片路径', '标题', '价格', '标签', '销量','用户评论'])
df.to_excel('淘宝1.xlsx', index=False, engine='openpyxl')
# 根据销量高的产品来获取他们的评论
