spider_work/kaogujia_spider/kgj_spider.py

# -*- coding: utf-8 -*-
# Author    : Charley
# Python    : 3.10.8
# Date      : 2025/1/22 10:51
import json
import random
import time
import base64
import schedule
import urllib3
import requests
from typing import Dict
from loguru import logger
from urllib.parse import quote
from Crypto.Cipher import AES
from Crypto.Util.Padding import unpad
from datetime import datetime, timedelta
from mysq_pool import MySQLConnectionPool
from tenacity import retry, stop_after_attempt, wait_fixed

from request_live_detail import get_live_detail

urllib3.disable_warnings()

logger.remove()
logger.add("./logs/{time:YYYYMMDD}.log", encoding='utf-8', rotation="00:00",
           format="[{time:YYYY-MM-DD HH:mm:ss.SSS}] {level} {message}",
           level="DEBUG", retention="14 day")

MAX_PAGE = 100


def after_log(retry_state):
    """
    retry 回调
    :param retry_state: RetryCallState 对象
    """
    log = retry_state.args[0]  # 获取传入的 logger
    if retry_state.outcome.failed:
        log.warning(
            f"Function '{retry_state.fn.__name__}', Attempt {retry_state.attempt_number} Times")
    else:
        log.info(f"Function '{retry_state.fn.__name__}', Attempt {retry_state.attempt_number} succeeded")


@retry(stop=stop_after_attempt(5), wait=wait_fixed(1), after=after_log)
def get_proxys(log):
    """
    获取代理
    :return: 代理
    """
    # tunnel = "h991.kdltps.com:15818"
    # kdl_username = "t12136177769785"
    # kdl_password = "ety9bdi8"

    tunnel = "x371.kdltps.com:15818"
    kdl_username = "t13753103189895"
    kdl_password = "o0yefv6z"
    try:
        proxies = {
            "http": "http://%(user)s:%(pwd)s@%(proxy)s/" % {"user": kdl_username, "pwd": kdl_password, "proxy": tunnel},
            "https": "http://%(user)s:%(pwd)s@%(proxy)s/" % {"user": kdl_username, "pwd": kdl_password, "proxy": tunnel}
        }
        return proxies
    except Exception as e:
        log.error(f"Error getting proxy: {e}")
        raise e


def decimal_to_percent(decimal_value):
    if not decimal_value:
        return "0%"

    # 将小数转换为百分比并保留一位小数
    percentage = decimal_value * 100
    # 使用格式化去除末尾多余的零
    return f"{percentage:g}%"  # 'g' 格式会自动去掉不必要的零


def decimal_to_percent_with_dist(decimal_value):
    if not decimal_value:
        return "0%"

    # 将小数转换为百分比
    percentage = decimal_value * 100

    # 使用格式化字符串，最多保留两位小数，去掉不必要的零
    formatted_percentage = f"{percentage:.2f}".rstrip('0').rstrip('.')

    return f"{formatted_percentage}%"


def convert_seconds_to_hours_minutes(total_seconds: int):
    # 计算完整的小时数
    hours = total_seconds // 3600
    remaining_seconds_after_hours = total_seconds % 3600

    # 计算完整的分钟数
    minutes = remaining_seconds_after_hours // 60
    result = f"{hours}小时{minutes}分" if hours > 0 else f"{minutes}分" if minutes > 0 else "0分"
    return result


def get_date(offset):
    """
    获取指定偏移量的日期，格式为 YYYYMMDD。

    参数:
    offset (int): 日期偏移量，0 表示今天，-1 表示昨天，-6 表示6天前，-7 表示7天前

    返回:
    str: 格式为 YYYYMMDD 的日期字符串
    """
    today = datetime.today()
    target_date = today + timedelta(days=offset)
    return target_date.strftime('%Y%m%d')


def decrypt_data(log, par_url, encrypted_data) -> Dict[str, str]:
    """
    解密数据
    :param log:
    :param par_url:
    :param encrypted_data:
    :return:
    """
    log.info("开始解密数据 ->->->->->->->->->->->->->->->->->->->->->")
    if not isinstance(par_url, str):
        return {}

    # 对应原js中的str函数
    def transform_str(input_str):
        encoded = quote(input_str)
        return base64.b64encode(encoded.encode()).decode()

    str_result = transform_str(par_url) * 3
    org_key = str_result[:16]
    org_iv = str_result[12:28]

    # 使用Crypto库解析key和iv
    ikey = org_key.encode('utf-8')
    iiv = org_iv.encode('utf-8')

    # 解密
    cipher = AES.new(ikey, AES.MODE_CBC, iiv)
    decrypted_text = unpad(cipher.decrypt(base64.b64decode(encrypted_data)), AES.block_size).decode('utf-8')
    decrypted_text = json.loads(decrypted_text)
    # print(decrypted_text)

    return decrypted_text


def save_product_list(sql_pool, info_list):
    sql = """
        INSERT INTO kgj_product_list_record (product_id, title, price, price_str, cos_ratio, sales, live_sales, video_sales, other_sales, live_ratio, video_ratio, other_ratio, shop_id, shop_name, shop_cover, keyword)
        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
        """
    sql_pool.insert_all(sql, info_list)


def save_live_detail(sql_pool, info_list):
    """
    保存直播详情数据
    :param sql_pool: 数据库连接池对象
    :param info_list: info_list 列表
    """
    sql = """
        INSERT INTO kgj_live_detail_record (room_id, live_create_time, live_finish_time, duration, watch_users, avg_users, peak_users, through, exposed_num, stay_duration, new_fans_count, inc_fans_clubs, turn_ratio, interaction_ratio, gmv, sales, atv, explain_duration, sku_count, uv, cvr, rpm, promotion_id, product_id, product_title, product_cover, product_sales, product_putaway_time, product_sold_out_time)
        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
        """
    sql_pool.insert_all(sql, info_list)


def update_linked_live_state(sql_pool, param):
    """
    更新 kgj_linked_live_record 状态
    :param sql_pool: 数据库连接池对象
    :param param: sql_id
    """
    sql = f"UPDATE kgj_linked_live_record SET live_detail_state = 1 WHERE id = %s"
    sql_pool.update_one(sql, (param,))


def parse_product_list(log, resp_json: dict, sql_pool, keyword, stop_paging):
    log.info("开始解析 product_list 数据......................")
    items = resp_json.get("items", [])

    info_list = []
    for item in items:
        sales = item.get("stat", {}).get("sales")
        # 检查 sales 是否为 0 或 '0'
        if sales == 0 or sales == '0':
            stop_paging[0] = True  # 设置停止翻页的标志
            log.info("已到达销量为0的页码，停止当前产品列表的翻页..............")
            break  # 停止解析当前页面的产品列表

        product_id = item.get("product_id")

        # 20250523 删除根据 product_id 去重
        # if product_id in sql_product_id_list:
        #     log.debug(f"{product_id} 已存在，跳过..............")
        #     continue
        title = item.get("title")
        # 如果标题中 包含["卡夹", "卡砖", "卡膜", "鼠标垫"]中的任意一个，则将keyword设置为 "周边"
        if any(keyword in title for keyword in ["卡夹", "卡砖", "卡膜", "鼠标垫"]):
            log.debug(f"{title} 包含关键字，为周边产品..............")
            keyword = "周边"

        price = item.get("price")
        price_str = item.get("price_str")
        cos_ratio = item.get("cos_ratio")

        live_sales = item.get("stat", {}).get("live_sales")
        video_sales = item.get("stat", {}).get("video_sales")
        other_sales = item.get("stat", {}).get("other_sales")

        live_ratio = item.get("market_type", {}).get("live_ratio")
        live_ratio = decimal_to_percent(live_ratio) if live_ratio else "0%"

        video_ratio = item.get("market_type", {}).get("video_ratio")
        video_ratio = decimal_to_percent(video_ratio) if video_ratio else "0%"

        other_ratio = item.get("market_type", {}).get("other_ratio")
        other_ratio = decimal_to_percent(other_ratio) if other_ratio else "0%"

        shop_id = item.get("shop_id")
        shop_name = item.get("shop_name")
        shop_cover = item.get("shop_cover")

        info = (product_id, title, price, price_str, cos_ratio, sales, live_sales, video_sales, other_sales, live_ratio,
                video_ratio, other_ratio, shop_id, shop_name, shop_cover, keyword)
        info_list.append(info)
    if info_list:
        log.info(f"解析到 {len(info_list)} 条数据......................")
        save_product_list(sql_pool, info_list)
    else:
        log.info("没有解析到数据......................")


@retry(stop=stop_after_attempt(5), wait=wait_fixed(1), after=after_log)
def get_kgj_product_one_page(log, page, keyword, sql_pool, stop_paging, headers):
    url = "https://service.kaogujia.com/api/sku/search"
    params = {
        "limit": "50",
        "page": str(page),
        "sort_field": "sales",
        "sort": "0"
    }
    data = {
        "period": 7,
        "keyword": keyword
    }
    response = requests.post(url, headers=headers, params=params, json=data)
    # print(response.text)
    # print(response)
    response.raise_for_status()
    resp_json = response.json()
    if resp_json:
        if resp_json.get("code") == 200:
            enc_data = resp_json.get("data")
            par_url = '/api/sku/search'
            dec_data = decrypt_data(log, par_url, enc_data)
            # print(dec_data)
            parse_product_list(log, dec_data, sql_pool, keyword, stop_paging)
        else:
            log.warning(f"Error get_kgj_product_one_page: {resp_json.get('message')}")
    else:
        log.warning(f"Error resp_json")


def get_kgj_product_list(log, keyword, sql_pool, headers):
    stop_paging = [False]  # 使用列表来存储标志，以便在函数间传递
    for page in range(1, MAX_PAGE + 1):
        try:
            log.info(f"Getting kgj product list page {page}, keyword:{keyword}")
            get_kgj_product_one_page(log, page, keyword, sql_pool, stop_paging, headers)
        except Exception as e:
            log.error(f"Error getting kgj product list: {e}")
            time.sleep(random.randint(4, 6))
            continue

        time.sleep(random.randint(4, 6))

        if stop_paging[0]:  # 检查停止翻页的标志
            log.info("停止翻页，因为 sales 为 0 或 '0'")
            break


def save_product_overview(sql_pool, info_list):
    sql = """
        INSERT INTO kgj_product_overview_record (product_id, date_all, sales_str, live_sales_str, video_sales_str, other_sales_str, users_str, lives_str, videos_str, live_ratio, video_ratio, other_ratio)
        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
        """
    sql_pool.insert_all(sql, info_list)


def update_state(sql_pool, product_id, state_str, state_int):
    """
    更新 kgj_product_list_record 状态
    :param sql_pool: 数据库连接池对象
    :param product_id: 产品ID
    :param state_str: 状态字段名称
    :param state_int: 状态值
    """
    sql = f"UPDATE kgj_product_list_record SET {state_str} = %s WHERE product_id = %s"
    sql_pool.update_one(sql, (state_int, product_id))


def get_product_overview_percent(log, product_id, headers):
    log.info(f"Getting kgj product overview percent, product_id:{product_id}")
    url = "https://service.kaogujia.com/api/sku/overview/dist"
    data = {
        "product_id": product_id,
        "from_dt": get_date(-7),
        "to_dt": get_date(-1)
    }
    response = requests.post(url, headers=headers, json=data)
    response.raise_for_status()
    resp_json = response.json()

    if resp_json:
        if resp_json.get("code") == 200:
            enc_data = resp_json.get("data")
            par_url = '/api/sku/overview/dist'
            dec_data = decrypt_data(log, par_url, enc_data)
            # print(dec_data)
            sales_list = dec_data.get("sales")
            live_ratio = "0%"
            video_ratio = "0%"
            other_ratio = "0%"
            for sales in sales_list:
                if sales.get("name") == "直播带货":
                    live_ratio = sales.get("percent")
                    live_ratio = decimal_to_percent_with_dist(live_ratio) if live_ratio else "0%"
                if sales.get("name") == "视频带货":
                    video_ratio = sales.get("percent")
                    video_ratio = decimal_to_percent_with_dist(video_ratio) if video_ratio else "0%"
                if sales.get("name") == "商品卡":
                    other_ratio = sales.get("percent")
                    other_ratio = decimal_to_percent_with_dist(other_ratio) if other_ratio else "1%"

            return live_ratio, video_ratio, other_ratio

        else:
            log.warning(f"Error get_kgj_product_overview: {resp_json.get('message')}")
            # update_state(sql_pool, product_id, "product_state", 2)
            return "0%", "0%", "0%"
    else:
        log.warning(f"Error get_kgj_product_overview resp_json")
        # update_state(sql_pool, product_id, "product_state", 2)
        return "0%", "0%", "0%"


def parse_product_overview(log, sql_pool, resp_json: dict, product_id, headers):
    log.info("开始解析 product_overview 数据......................")
    trend_list = resp_json.get("trend_list", [])
    if not trend_list:
        log.debug(f"parse_product_overview trend_list is empty")
        update_state(sql_pool, product_id, "product_state", 2)
    else:
        # 获取商品概览页的占比信息
        live_ratio, video_ratio, other_ratio = get_product_overview_percent(log, product_id, headers)
        info_list = []
        for trend in trend_list:
            date_all = trend.get("date_all")
            sales_str = trend.get("sales_str")
            live_sales_str = trend.get("live_sales_str")
            video_sales_str = trend.get("video_sales_str")
            other_sales_str = trend.get("other_sales_str")
            users_str = trend.get("users_str")
            lives_str = trend.get("lives_str")
            videos_str = trend.get("videos_str")
            info = (
                product_id, date_all, sales_str, live_sales_str, video_sales_str, other_sales_str, users_str, lives_str,
                videos_str, live_ratio, video_ratio, other_ratio)
            info_list.append(info)
        save_product_overview(sql_pool, info_list)
        # sql = "UPDATE kgj_product_list_record SET product_state = 2 WHERE product_id = %s"
        update_state(sql_pool, product_id, "product_state", 1)


def get_kgj_product_overview(log, sql_pool, product_id, headers):
    url = f"https://service.kaogujia.com/api/sku/trend/{product_id}"
    params = {
        "begin": get_date(-7),
        # "begin": "20250115",
        # "end": "20250121"
        "end": get_date(-1)
    }
    response = requests.get(url, headers=headers, params=params)
    # print(response.text)
    response.raise_for_status()
    resp_json = response.json()

    if resp_json:
        if resp_json.get("code") == 200:
            enc_data = resp_json.get("data")
            par_url = f'/api/sku/trend/{product_id}'
            dec_data = decrypt_data(log, par_url, enc_data)
            # print(dec_data)
            parse_product_overview(log, sql_pool, dec_data, product_id, headers)
        else:
            log.warning(f"Error get_kgj_product_overview: {resp_json.get('message')}")
            update_state(sql_pool, product_id, "product_state", 2)
    else:
        log.warning(f"Error get_kgj_product_overview resp_json")
        update_state(sql_pool, product_id, "product_state", 2)


def save_linded_live(sql_pool, info_list):
    sql = """
        INSERT INTO kgj_linked_live_record (product_id, title, duration_str, pub_time_str, uid, nick_name, fans_count, price, price_str, sales, gmv, pi, room_id, date_code)
        VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
        """
    sql_pool.insert_all(sql, info_list)


def parse_linked_live(log, dec_data, sql_pool, product_id):
    log.info("开始解析 linked_live 数据......................")
    items = dec_data.get("items", [])
    if not items:
        log.debug(f"parse_linked_live items is empty")
        update_state(sql_pool, product_id, "live_state", 2)
    else:
        info_list = []
        for item in items:
            title = item.get("title")
            duration = item.get("duration")
            duration_str = convert_seconds_to_hours_minutes(duration)
            pub_time = item.get("pub_time")
            pub_time_str = datetime.fromtimestamp(pub_time).strftime('%Y-%m-%d %H:%M:%S') if pub_time else ""
            uid = item.get("uid")
            nick_name = item.get("nick_name")
            fans_count = item.get("fans_count")
            price = item.get("price")
            price_str = item.get("price_str")
            sales = item.get("sales")
            gmv = item.get("gmv")
            pi = item.get("pi")
            room_id = item.get("room_id")
            date_code = item.get("date_code")

            info = (
                product_id, title, duration_str, pub_time_str, uid, nick_name, fans_count, price, price_str, sales, gmv,
                pi, room_id, date_code)
            info_list.append(info)
        save_linded_live(sql_pool, info_list)
        update_state(sql_pool, product_id, "live_state", 1)


def get_linked_live(log, sql_pool, product_id, headers):
    url = "https://service.kaogujia.com/api/sku/live/list"
    params = {
        "limit": "10",
        "page": "1",
        "sort_field": "gmv",
        "sort": "0"
    }
    data = {
        "keyword": "",
        "min_time": get_date(-6),
        "max_time": get_date(0),
        "product_id": product_id
    }
    response = requests.post(url, headers=headers, params=params, json=data)
    # print(response.text)
    response.raise_for_status()
    resp_json = response.json()
    if resp_json:
        if resp_json.get("code") == 200:
            enc_data = resp_json.get("data")
            par_url = '/api/sku/live/list'
            dec_data = decrypt_data(log, par_url, enc_data)
            # print(dec_data)
            parse_linked_live(log, dec_data, sql_pool, product_id)
        else:
            log.warning(f"Error get_linked_live: {resp_json.get('message')}")
            update_state(sql_pool, product_id, "live_state", 2)
    else:
        log.warning(f"Error get_linked_live resp_json")
        update_state(sql_pool, product_id, "live_state", 2)


@retry(stop=stop_after_attempt(500), wait=wait_fixed(600), after=after_log)
def kgj_main(log):
    log.info("开始运行 kaogujia_spider 爬虫任务............................................................")
    sql_pool = MySQLConnectionPool(log=log)
    if not sql_pool:
        log.error("数据库连接失败")
        raise Exception("数据库连接失败")

    kgj_token = sql_pool.select_one("SELECT token FROM kgj_token")
    # kgj_token = ['Bearer eyJhbGciOiJIUzUxMiJ9.eyJhdWQiOiIxMDAwIiwiaXNzIjoia2FvZ3VqaWEuY29tIiwianRpIjoiZmRlOWYwYjUyMzE5NDZlYWFlY2RhODY3MDE3MTczYzQiLCJzaWQiOjU2OTY1ODQsImlhdCI6MTc0Nzk4Mjk2MSwiZXhwIjoxNzQ4NTg3NzYxLCJid2UiOjEsInR5cCI6MSwicF9id2UiOjB9._-jUtF8sjM-1NHTFlubgozYD5FgQe-bhgnbJ3Dyc_Rhkig1devg_10GtxiNtJv4aSHDs0w8T_LuRVzkeRep9Vg']
    # 195的账号
    KGJ_HEADERS = {
        "accept": "*/*",
        "accept-language": "en,zh-CN;q=0.9,zh;q=0.8",
        "authorization": kgj_token[0],
        "content-type": "application/json",
        "origin": "https://www.kaogujia.com",
        "priority": "u=1, i",
        "referer": "https://www.kaogujia.com/",
        "sec-ch-ua": "\"Not(A:Brand\";v=\"99\", \"Google Chrome\";v=\"133\", \"Chromium\";v=\"133\"",
        "sec-ch-ua-mobile": "?0",
        "sec-ch-ua-platform": "\"Windows\"",
        "sec-fetch-dest": "empty",
        "sec-fetch-mode": "cors",
        "sec-fetch-site": "same-site",
        "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36",
        "version_code": "3.1"
    }

    try:
        keyword_list = ["球星卡", "海贼王", "游戏王", "宝可梦"]
        log.info("开始获取 product_list 数据............................................................")
        # sql_product_id_list = sql_pool.select_all("SELECT DISTINCT product_id FROM kgj_product_list_record")
        # sql_product_id_list = [item[0] for item in sql_product_id_list]
        for keyword in keyword_list:
            try:
                get_kgj_product_list(log, keyword, sql_pool, KGJ_HEADERS)
            except Exception as e:
                log.error(f"Error main -> getting kgj product list: {e}")
                continue
        # sql_product_id_list.clear()
        log.info("product_list 数据获取完成............................................................")

        time.sleep(5)

        log.info("开始获取 product_overview 数据............................................................")
        product_id_list_for_product = sql_pool.select_all(
            "SELECT product_id FROM kgj_product_list_record WHERE product_state = 0")
        product_id_list = [item[0] for item in product_id_list_for_product]
        for product_id in product_id_list:
            try:
                log.info(f"开始获取 product_id: {product_id} 的 product_overview 数据............................")
                get_kgj_product_overview(log, sql_pool, product_id, KGJ_HEADERS)
            except Exception as e:
                log.error(f"Error main -> getting kgj product overview: {e}")
                time.sleep(random.randint(4, 6))
                continue
            time.sleep(random.randint(4, 6))
        log.info("product_overview 数据获取完成............................................................")

        time.sleep(5)
        log.info("开始获取 linked_live 数据............................................................")
        product_id_list_for_live = sql_pool.select_all(
            "SELECT product_id FROM kgj_product_list_record WHERE live_state = 0")
        product_id_list = [item[0] for item in product_id_list_for_live]
        for product_id in product_id_list:
            try:
                log.info(f"开始获取 product_id: {product_id} 的 linked_live 数据............................")
                get_linked_live(log, sql_pool, product_id, KGJ_HEADERS)
            except Exception as e:
                log.error(f"Error main -> getting kgj product overview: {e}")
                time.sleep(random.randint(4, 6))
                continue
            time.sleep(random.randint(4, 6))
        log.info("linked_live 数据获取完成............................................................")

        time.sleep(5)

        log.info("开始获取 live_detail 数据............................................................")
        sql_room_id_list = sql_pool.select_all(
            "SELECT id, uid, room_id, date_code FROM kgj_linked_live_record WHERE live_detail_state = 0 and uid is not null and room_id is not null and date_code is not null")
        sql_room_id_list = [item for item in sql_room_id_list]
        if sql_room_id_list:
            for sql_info in sql_room_id_list:
                try:
                    log.info(f"开始获取 room_id: {sql_info[2]} 的 live_detail 数据............................")
                    live_detail_info_list = get_live_detail(log, sql_info, KGJ_HEADERS)
                    save_live_detail(sql_pool, live_detail_info_list)
                    update_linked_live_state(sql_pool, sql_info[0])
                except Exception as e:
                    log.error(f"Error main -> getting kgj live_detail: {e}")
                    # update_linked_live_state(sql_pool, 3, sql_info[0])
                    time.sleep(random.randint(4, 6))
                    continue
                time.sleep(random.randint(4, 6))
        log.info("live_detail 数据获取完成............................................................")

    except Exception as e:
        log.error(e)
    finally:
        log.info("爬虫程序 kaogujia_spider 运行结束,等待下一轮的采集任务.............")


def schedule_task():
    """
    设置定时任务
    """
    # 立即运行一次任务
    # kgj_main(logger)

    # 设置定时任务   考古加  球星卡/海贼王/游戏王/宝可梦  都是一周循环  周六
    schedule.every().saturday.at("01:01").do(kgj_main, logger)
    while True:
        schedule.run_pending()
        time.sleep(1)


if __name__ == '__main__':
    # enc_data = "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"
    # # resss_data = decrypt_data(logger, '/api/sku/live/list', enc_data)
    # resss_data = decrypt_data(logger, '/api/sku/search', enc_data)
    # print(resss_data)

    schedule_task()
    # print(get_product_overview_percent(logger, 'ENXREbYqakqQQ'))