207 lines
7.7 KiB
Python
207 lines
7.7 KiB
Python
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import pandas as pd
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import requests
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import json
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from datetime import datetime
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from sqlalchemy import create_engine
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from urllib.parse import quote_plus
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import logging
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# 配置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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def get_access_token():
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"""获取飞书访问令牌[1,7](@ref)"""
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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": "cli_a8b50ec0eed1500d", "app_secret": "ccxkE7ZCFQZcwkkM1rLy0ccZRXYsT2xK"}
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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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if response.json().get("code") == 0:
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return response.json()["tenant_access_token"]
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else:
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raise Exception(f"获取Token失败: {response.text}")
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except Exception as e:
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logging.error(f"获取飞书Token异常: {str(e)}")
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raise
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def overwrite_data(spreadsheet_token, values, access_token=None):
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"""覆盖写入数据到飞书多维表格[1,6](@ref)"""
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if not access_token:
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access_token = get_access_token()
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url = f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{spreadsheet_token}/values"
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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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row_count = len(values) + 1
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range_str = f"46ea20!A1:B{row_count}"
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post_data = {
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"valueRange": {
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"range": range_str,
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"values": values
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}
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}
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try:
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response = requests.put(url, json=post_data, headers=headers, timeout=15)
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response.raise_for_status()
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return response
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except Exception as e:
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logging.error(f"写入飞书表格失败: {str(e)}")
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raise
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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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# 创建SQLAlchemy引擎（解决pandas警告问题）
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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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pool_pre_ping=True,
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pool_size=5,
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max_overflow=10
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)
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def fetch_data_from_db():
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"""从数据库执行SQL查询获取数据（使用SQLAlchemy引擎）"""
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try:
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sql_query = """
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SELECT
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v_vehicle_info.VIN AS car_vins,
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CASE v_sim_info.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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v_vehicle_info.MATERIAL_ID as MATERIAL,
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v_vehicle_info.SALES_TERRITORY as Area,
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v_sim_info.ACTIVATION_DATE as active_date
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FROM v_vehicle_info
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JOIN v_tbox_info USING (VIN)
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JOIN v_sim_info USING (SN);
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"""
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return pd.read_sql(sql_query, engine)
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except Exception as e:
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logging.error(f"数据库查询失败: {str(e)}")
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raise
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def send_feishu_message(webhook_url, message, spreadsheet_token=None, retry=2):
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"""
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通过Webhook发送飞书消息，支持添加多维表格链接[2,8](@ref)
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:param webhook_url: 机器人Webhook地址
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:param message: 要发送的文本内容
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:param spreadsheet_token: 多维表格ID（可选）
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:param retry: 重试次数
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"""
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headers = {'Content-Type': 'application/json'}
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# 如果有提供多维表格ID，添加表格链接按钮
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if spreadsheet_token:
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spreadsheet_url = f"https://my-ichery.feishu.cn/sheets/{spreadsheet_token}"
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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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"actions": [{
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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": spreadsheet_url
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}],
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"tag": "action"
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}
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],
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"header": {
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"title": {"content": "数据同步完成通知", "tag": "plain_text"},
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"template": "green"
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}
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}
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}
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else:
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payload = {"msg_type": "text", "content": {"text": message}}
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for attempt in range(retry):
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try:
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response = requests.post(webhook_url, headers=headers, data=json.dumps(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.warning(f"飞书消息发送失败(尝试 {attempt + 1}/{retry}): {str(e)}")
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if attempt < retry - 1:
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time.sleep(2) # 等待后重试
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raise Exception(f"飞书消息发送失败，重试{retry}次后仍不成功")
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if __name__ == '__main__':
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# 配置参数
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SPREADSHEET_ID = "MIqssvuB3h3XmgtkI26cBX7Angc"
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WEBHOOK_URL = "https://open.feishu.cn/open-apis/bot/v2/hook/d82e4ada-8f78-40ae-b98e-75af0c448c95"
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try:
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logging.info("开始数据同步流程...")
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# 1. 从数据库获取数据
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df = fetch_data_from_db()
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logging.info(f"成功获取{len(df)}条车辆数据")
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# 2. 处理数据
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df['active_date'] = pd.to_datetime(df['active_date'], errors='coerce')
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active_df = df[df['active_status'] == 'active']
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logging.info(f"有效激活数据: {len(active_df)}条")
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# 3. 按天统计激活数
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daily_count = active_df.groupby(active_df['active_date'].dt.date).size().reset_index(name='active_count')
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values = [[str(d), str(c)] for d, c in daily_count.values.tolist()] # 确保值为字符串类型
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logging.info(f"生成{len(values)}条日期统计记录")
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# 4. 覆盖写入多维表格
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response = overwrite_data(SPREADSHEET_ID, values)
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if response.status_code == 200:
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logging.info("数据成功写入飞书多维表格")
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# 5. 构建通知消息
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current_time = datetime.now().strftime("%Y-%m-%d %H:%M")
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today_count = daily_count[daily_count['active_date'] == datetime.now().date()]
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weekly_count = daily_count[daily_count['active_date'] >= (datetime.now() - pd.Timedelta(days=7)).date()]
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stats_summary = f"• 今日激活车辆: {today_count['active_count'].values[0] if not today_count.empty else 0}\n"
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stats_summary += f"• 本周激活车辆: {weekly_count['active_count'].sum()}\n"
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stats_summary += f"• 累计激活车辆: {len(active_df)}"
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message = f"🚗 车辆数据同步完成 ✅\n"
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message += f"⏰ 时间: {current_time}\n"
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message += f"📊 统计摘要:\n{stats_summary}\n"
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# 6. 发送包含多维表格链接的通知
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result = send_feishu_message(WEBHOOK_URL, message, SPREADSHEET_ID)
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logging.info(f"飞书消息发送成功: {result}")
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else:
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error_msg = f"表格写入失败: {response.status_code} - {response.text}"
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logging.error(error_msg)
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error_message = f"❌ 数据同步失败\n{error_msg}"
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send_feishu_message(WEBHOOK_URL, error_message)
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except Exception as e:
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error_message = f"❌ 数据同步异常: {str(e)}"
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logging.exception("程序执行异常")
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send_feishu_message(WEBHOOK_URL, error_message)
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