348 lines
12 KiB
Python
348 lines
12 KiB
Python
import pandas as pd
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import requests
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import logging
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import time
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import json
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from sqlalchemy import create_engine
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from urllib.parse import quote_plus
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from datetime import datetime
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# 配置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s %(levelname)s %(name)s %(message)s'
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)
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# ====================== 全局配置 ======================
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# 数据库连接配置
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DB_CONFIG = {
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'host': 'eutsp-prod.mysql.germany.rds.aliyuncs.com',
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'port': 3306,
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'user': 'international_tsp_eu_r',
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'password': 'ZXhBgo1TB2XbF3kP',
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'database': 'chery_international_tsp_eu'
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}
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# 飞书多维表格配置 (多市场表格配置)
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FEISHU_APP_TOKEN = "T3QLbmpqma014ussjy9cgitqnSh" # 应用Token (恢复此关键变量)
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MARKET_TABLES = [
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{"name": "英国", "table_id": "tblbfEHrsojQ4D5w", "view_id": "vewBvcYDAa"}
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]
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# 通用字段映射
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VIN_FIELD_NAME = "车架号"
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ACTIVE_FIELD_NAME = "激活状态"
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VEHICLE_NAME_FIELD = "车型"
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# 飞书应用凭证
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APP_ID = "cli_a8b50ec0eed1500d"
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APP_SECRET = "ccxkE7ZCFQZcwkkM1rLy0ccZRXYsT2xK"
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# 飞书机器人配置
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WEBHOOK_URL = "https://open.feishu.cn/open-apis/bot/v2/hook/3bc45247-c469-47a0-bfe9-c62e46c5aca0"
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MULTI_TABLE_URL = "https://my-ichery.feishu.cn/base/T3QLbmpqma014ussjy9cgitqnSh?from=from_copylink"
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# ====================== 通用函数 ======================
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def get_access_token():
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"""获取飞书访问令牌"""
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api_token_url = "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal/"
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api_post_data = {"app_id": APP_ID, "app_secret": APP_SECRET}
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try:
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response = requests.post(api_token_url, json=api_post_data, timeout=10)
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response.raise_for_status()
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resp_data = response.json()
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if resp_data.get("code") == 0:
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return resp_data["tenant_access_token"]
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else:
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raise Exception(f"获取Token失败: {resp_data.get('msg')}")
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except Exception as e:
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logging.error(f"获取飞书Token异常: {e}")
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raise
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def send_feishu_message(message):
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"""发送飞书通知"""
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headers = {'Content-Type': 'application/json'}
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payload = {
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"msg_type": "interactive",
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"card": {
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"config": {"wide_screen_mode": True},
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"elements": [
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{
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"tag": "div",
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"text": {"content": message, "tag": "lark_md"}
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},
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{
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"tag": "action",
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"actions": [
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{
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"tag": "button",
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"text": {"content": "查看多维表格", "tag": "plain_text"},
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"type": "primary",
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"url": MULTI_TABLE_URL
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}
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]
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}
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],
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"header": {
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"title": {"content": "车辆状态同步报告", "tag": "plain_text"},
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"template": "blue"
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}
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}
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}
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try:
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response = requests.post(WEBHOOK_URL, headers=headers, json=payload, timeout=10)
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response.raise_for_status()
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return response.json()
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except Exception as e:
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logging.error(f"飞书消息发送失败: {str(e)}")
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return None
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def read_feishu_records(app_token, table_id, view_id, retry=3):
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"""从飞书多维表格读取车辆记录"""
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access_token = get_access_token()
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headers = {
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"Authorization": f"Bearer {access_token}",
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"Content-Type": "application/json; charset=utf-8",
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}
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url = f"https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records"
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params = {
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"page_size": 500,
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"view_id": view_id # 添加视图ID参数
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}
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all_records = []
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page_token = None
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while True:
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if page_token:
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params["page_token"] = page_token
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for attempt in range(retry):
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try:
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response = requests.get(url, headers=headers, params=params, timeout=30)
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response.raise_for_status()
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resp_data = response.json()
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if resp_data.get("code") != 0:
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raise Exception(f"API错误: {resp_data.get('msg')}")
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records = resp_data["data"]["items"]
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all_records.extend(records)
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has_more = resp_data["data"].get("has_more")
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page_token = resp_data["data"].get("page_token") if has_more else None
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break
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except Exception as e:
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logging.warning(f"读取多维表格失败(尝试 {attempt + 1}/{retry}): {e}")
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time.sleep(2 ** attempt)
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else:
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raise Exception("无法读取多维表格数据")
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if not page_token:
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break
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return all_records
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def fetch_activation_data():
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"""从数据库查询车辆激活状态和车型"""
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try:
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safe_password = quote_plus(DB_CONFIG['password'])
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engine = create_engine(
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f"mysql+pymysql://{DB_CONFIG['user']}:{safe_password}@{DB_CONFIG['host']}:{DB_CONFIG['port']}/{DB_CONFIG['database']}",
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pool_recycle=3600
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)
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sql_query = """
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SELECT
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v.VIN AS car_vins,
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CASE s.STATE
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WHEN 2 THEN 'active'
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ELSE 'no_active'
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END AS active_status,
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iv.`NAME` AS `车型`
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FROM v_vehicle_info v
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JOIN v_tbox_info t USING (VIN)
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JOIN v_sim_info s USING (SN)
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LEFT JOIN v_material_info m ON m.MATERIAL_ID = v.MATERIAL_ID
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LEFT JOIN v_outside_vehicle_type ov ON ov.TYPE_CODE = m.OUTSIDE_TYPE_CODE
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LEFT JOIN v_inside_vehicle_type iv ON iv.TYPE_CODE = ov.INSIDE_TYPE_CODE
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"""
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df = pd.read_sql(sql_query, engine)
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df = df.drop_duplicates(subset=['car_vins'], keep='first')
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expected = ['car_vins', 'active_status', VEHICLE_NAME_FIELD]
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missing = [c for c in expected if c not in df.columns]
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if missing:
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logging.error(f"查询结果缺少列: {missing}")
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raise KeyError(f"Missing columns: {missing}")
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df2 = df.set_index('car_vins')[['active_status', VEHICLE_NAME_FIELD]]
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return df2.to_dict(orient='index')
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except Exception as e:
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logging.error(f"数据库查询失败: {e}")
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raise
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def compare_and_update_records(app_token, table_id, view_id, activation_data):
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"""比较并更新飞书多维表格记录"""
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access_token = get_access_token()
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headers = {
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"Authorization": f"Bearer {access_token}",
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"Content-Type": "application/json; charset=utf-8",
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}
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feishu_records = read_feishu_records(app_token, table_id, view_id)
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logging.info(f"读取 {len(feishu_records)} 条多维表格记录完成")
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# 初始化计数器和待更新列表
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records_to_update = []
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activated_count = 0
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not_activated_count = 0
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# Streamline record processing and validation upfront
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valid_records = [
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record for record in feishu_records
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if record.get("fields", {}).get(VIN_FIELD_NAME)
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]
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logging.info(f"有效记录数: {len(valid_records)} (过滤无效记录)")
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for record in valid_records:
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record_id = record["record_id"]
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fields = record["fields"]
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vin = fields[VIN_FIELD_NAME]
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# 数据库信息匹配
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db_data = activation_data.get(vin)
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if not db_data:
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continue # 如果VIN不存在于数据库，则跳过
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db_status = db_data['active_status']
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db_name = db_data[VEHICLE_NAME_FIELD]
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current_status = fields.get(ACTIVE_FIELD_NAME, "").lower()
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current_name = fields.get(VEHICLE_NAME_FIELD, "")
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# 需要更新的记录
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if db_status != current_status or db_name != current_name:
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records_to_update.append({
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"record_id": record_id,
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"fields": {
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ACTIVE_FIELD_NAME: db_status,
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VEHICLE_NAME_FIELD: db_name
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}
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})
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if db_status == "active":
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activated_count += 1
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else:
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not_activated_count += 1
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total_updated = len(records_to_update)
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logging.info(f"准备更新 {total_updated} 条记录 (激活: {activated_count}, 未激活: {not_activated_count})")
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# 批量更新记录
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batch_size = 100
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url = f"https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/batch_update"
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def batch_update(batch):
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payload = {"records": batch}
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for attempt in range(3): # 网络重试机制
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try:
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response = requests.post(url, headers=headers, json=payload, timeout=30)
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if response.status_code == 200 and response.json().get("code") == 0:
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return True # 更新成功
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else:
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logging.warning(f"更新失败，第{attempt + 1}次尝试: {response.json().get('msg')}")
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except Exception as e:
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logging.warning(f"网络异常，第{attempt + 1}次尝试: {e}")
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time.sleep(2 ** attempt) # 指数级等待
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return False # 所有尝试均失败
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# 批次处理记录更新
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for i in range(0, total_updated, batch_size):
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batch = records_to_update[i:i + batch_size]
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if batch_update(batch):
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logging.info(f"批次 {i // batch_size + 1} 更新成功 ({len(batch)} 条记录)")
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else:
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logging.error(f"批次 {i // batch_size + 1} 更新失败 ({len(batch)} 条记录)")
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return total_updated, activated_count, not_activated_count
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# ====================== 多表格处理流程 ======================
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def sync_all_markets():
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"""执行所有市场的车辆激活状态同步"""
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start_time = time.time()
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all_results = []
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try:
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# 一次性获取所有激活数据（避免多次查询数据库）
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logging.info("开始获取数据库激活数据...")
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activation_data = fetch_activation_data()
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logging.info(f"获取到 {len(activation_data)} 条车辆激活数据")
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# 按市场依次处理
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for market in MARKET_TABLES:
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market_name = market["name"]
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table_id = market["table_id"]
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view_id = market["view_id"]
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logging.info(f"开始同步市场: {market_name} (表格ID: {table_id})")
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try:
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# 使用FEISHU_APP_TOKEN修复NameError问题 ⭐⭐关键修复
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updated, activated, not_activated = compare_and_update_records(
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FEISHU_APP_TOKEN,
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table_id,
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view_id,
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activation_data
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)
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result = {
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"market": market_name,
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"table_id": table_id,
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"total_updated": updated,
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"activated_count": activated,
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"not_activated_count": not_activated,
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"success": True
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}
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logging.info(f"{market_name}同步完成: 更新{updated}台 (✅激活{activated}台，❌未激活{not_activated}台)")
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except Exception as e:
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result = {
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"market": market_name,
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"table_id": table_id,
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"error": str(e),
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"success": False
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}
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logging.error(f"{market_name}同步失败: {str(e)}", exc_info=True)
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all_results.append(result)
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time.sleep(1) # 每个市场处理间隔
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# 统计总体数据
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total_elapsed = time.time() - start_time
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return {
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"success": True,
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"results": all_results,
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"elapsed_time": total_elapsed,
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"start_time": start_time
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}
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except Exception as e:
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logging.error(f"整体同步流程失败: {str(e)}", exc_info=True)
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return {
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"success": False,
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"error": str(e),
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"elapsed_time": time.time() - start_time
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}
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if __name__ == '__main__':
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# 执行多市场同步
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sync_result = sync_all_markets()
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current_time = datetime.now().strftime("%Y-%m-%d %H:%M")
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