Python 爬取淘宝指定搜索商品评论 标题 销量 计算sign

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