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     "end_time": "2025-09-15T06:38:10.678825Z",
     "start_time": "2025-09-15T06:38:10.523582Z"
    }
   },
   "source": [
    "from datetime import datetime, timezone, timedelta, date, UTC\n",
    "import holidays\n",
    "from config import Config\n",
    "import psycopg2\n",
    "import pandas as pd\n",
    "import pymysql\n",
    "from api import API\n",
    "from log_config import configure_task_logger, configure_error_task_logger\n",
    "\n",
    "\n",
    "def get_jcb_details():\n",
    "    \"\"\"\n",
    "    从固定的数据库中获取前几天的NGV明细。\n",
    "    参数 `days_back` 表示相对于今天的天数偏移量，默认为1（即前一天）。\n",
    "    返回包含NGV明细的pandas DataFrame。\n",
    "    \"\"\"\n",
    "    # 保存为CSV文件\n",
    "    output_dir = \"output\"  # 设置输出目录\n",
    "\n",
    "    # 创建输出目录（如果不存在）\n",
    "    import os\n",
    "    os.makedirs(output_dir, exist_ok=True)\n",
    "\n",
    "    try:\n",
    "        # 获得连接并创建游标\n",
    "        conn = pymysql.connect(\n",
    "            host=Config.BI_CONN_host,\n",
    "            database=Config.BI_CONN_INFO_database,\n",
    "            user=Config.BI_CONN_INFO_user,\n",
    "            password=Config.BI_CONN_INFO_password,\n",
    "            # charset='utf8mb4',  # 设置字符集以避免编码问题\n",
    "            # cursorclass=pymysql.cursors.DictCursor  # 返回字典形式的结果\n",
    "        )\n",
    "        cursor = conn.cursor()\n",
    "\n",
    "        # 获取指定天数前的日期\n",
    "        # now_time = datetime.now()\n",
    "        # target_time = now_time + timedelta(days=-days_back)\n",
    "        target_date_id = \"接车宝\"  # 获取目标日期\n",
    "\n",
    "        # SQL 查询语句\n",
    "        sql = f\"\"\"\n",
    "            SELECT * FROM jdy_hs_holo_dws_sales_magic_box_ngv_d;\n",
    "        \"\"\"\n",
    "\n",
    "        # 执行查询并获取结果\n",
    "        cursor.execute(sql)\n",
    "        rows = cursor.fetchall()  # pymysql 的 DictCursor 会返回字典列表\n",
    "        print(rows)\n",
    "    except:\n",
    "        pass\n",
    "\n",
    "get_jcb_details()"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "()\n"
     ]
    }
   ],
   "execution_count": 5
  }
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