{ "cells": [ { "metadata": {}, "cell_type": "markdown", "source": "## 小六提成", "id": "22585e957ada61dc" }, { "cell_type": "code", "execution_count": null, "id": "initial_id", "metadata": { "collapsed": true }, "outputs": [], "source": [ "# -*- coding: utf-8 -*-\n", "import pandas as pd\n", "import datetime\n", "from config import Config\n", "from api import API\n", "import pymysql # 使用 pymysql 替代 mysql.connector\n", "from back_ground_module import CommonModule\n", "from tqdm import tqdm\n", "\n", "start_time = datetime.datetime.now()\n", "api_instance = API()\n", "common_module = CommonModule()\n", "\n", "\n", "class ImportPerformanceData:\n", " \"\"\"\n", " 履约表数据支撑\n", " \"\"\"\n", "\n", " def __init__(self):\n", " self.staff_name_to_id = None\n", " self.staff_id_list = None\n", " self.performance_data_list = None\n", " self.field_mapping = {}\n", " self.fields()\n", "\n", " def load_all_data(self):\n", " \"\"\"加载所有数据\"\"\"\n", " payload = {\"api_key\": \"675b900991ad2491c69389ca\",\n", " \"entry_id\": \"68637c9818bc333fc14c30ad\", # 需要修改\n", " }\n", " performance_data = api_instance.entry_data_list(payload)\n", " self.performance_data_list = performance_data.get(\"data\") # 履约表\n", "\n", " # 获取简道云员工id\n", " payload = {\"api_key\": \"6694d3c4fcb69ca9a111a6c4\",\n", " \"entry_id\": \"6769204a1902c9341340a1bc\",\n", " }\n", " staff_id = api_instance.entry_data_list(payload)\n", " self.staff_id_list = staff_id.get(\"data\") # api请求格式，将数据封装在data字典里\n", "\n", " # 预处理员工姓名到ID的映射\n", " self.staff_name_to_id = {\n", " str(item[\"_widget_1734942794144\"]): item[\"_widget_1734942794145\"]\n", " for item in self.staff_id_list\n", " }\n", "\n", " def process_data(self, df):\n", " \"\"\"处理数据的主函数\"\"\"\n", " new_df = self.convert_to_utc(df)\n", " all_data = []\n", "\n", " # 预定义角色映射\n", " role_mapping = {\n", " '运营负责人': '运营负责人',\n", " '区域经理': '区域经理'\n", " }\n", "\n", " # 使用iterrows的替代方案itertuples更快，但需要确保列名是有效的Python标识符\n", " for row in tqdm(new_df.itertuples(index=False), total=len(new_df)):\n", " row_dict = row._asdict()\n", "\n", " # 成员字段替换\n", " for role, field in role_mapping.items():\n", " name = getattr(row, field, None)\n", " if name and str(name) in self.staff_name_to_id:\n", " row_dict[role] = self.staff_name_to_id[str(name)]\n", " else:\n", " row_dict[role] = None\n", "\n", " # 简道云字段替换\n", " data_dict = self.row_to_dict(row_dict, self.field_mapping)\n", " all_data.append(data_dict)\n", "\n", " return all_data\n", "\n", " def convert_to_utc(self, df):\n", " # 创建副本避免修改原DataFrame\n", " new_df = df.copy()\n", " time_columns = ['saas开户时间', '服务期起始时间', '下单支付成功时间', '操作时间',\n", " \"下单支付成功日期\", \"服务期结束时间\"]\n", "\n", " for col in tqdm(time_columns):\n", " if col in tqdm(new_df.columns): # 安全检查列是否存在\n", " try:\n", " # 1. 转换为datetime（自动推断格式，处理无效值为NaT）\n", " new_df[col] = pd.to_datetime(new_df[col], errors='coerce', utc=False)\n", "\n", " # 2. 时区转换（仅对有效日期操作）\n", " mask = new_df[col].notna() # 只处理非空值\n", " if mask.any(): # 如果有有效日期才转换\n", " # 本地化为北京时间，然后转换为UTC\n", " new_df.loc[mask, col + '_utc'] = (\n", " new_df.loc[mask, col]\n", " .dt.tz_localize('Asia/Shanghai', ambiguous='infer', nonexistent='shift_forward')\n", " .dt.tz_convert('UTC')\n", " .dt.strftime('%Y-%m-%dT%H:%M:%SZ')\n", " )\n", " else:\n", " new_df[col + '_utc'] = pd.NA # 全部为空时保持一致性\n", "\n", " except Exception as e:\n", " print(f\"处理列 {col} 时出错: {str(e)}\")\n", " new_df[col + '_utc'] = pd.NA # 出错时设为NA\n", "\n", " return new_df\n", "\n", " def main(self):\n", " self.load_all_data()\n", "\n", " task_start_time = datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n", " # Step1:获取履约表数据\n", " df = common_module.get_perforamnce_details()\n", " print(\"数据获取完成\")\n", "\n", " # Step2:清空现有数据\n", " id_list = [item[\"_id\"] for item in self.performance_data_list]\n", "\n", " delete_payload = {\n", " \"api_key\": \"675b900991ad2491c69389ca\",\n", " \"entry_id\": \"68637c9818bc333fc14c30ad\",\n", " \"data_ids\": id_list\n", " }\n", " api_instance.entry_data_batch_delete(delete_payload)\n", " print(\"数据删除完成\")\n", "\n", " # Step3:将数据写入简道云中\n", " all_data = self.process_data(df)\n", "\n", " # 分批处理，每批1000条\n", " batch_size = 1000\n", " for i in tqdm(range(0, len(all_data), batch_size)):\n", " batch = all_data[i:i + batch_size]\n", " payload = {\n", " \"api_key\": \"675b900991ad2491c69389ca\",\n", " \"entry_id\": \"68637c9818bc333fc14c30ad\",\n", " \"data_list\": batch\n", " }\n", " api_instance.entry_data_batch_create(payload)\n", "\n", " print(\"数据写入完成\")\n", " common_module.send_task_status(task_start_time, \"履约表数据支撑\")\n", "\n", " @staticmethod\n", " def row_to_dict(row, field_mapping):\n", " \"\"\"将一行数据转换为指定格式的字典\"\"\"\n", " result = {}\n", " for col_name, widget_id in field_mapping.items():\n", " if col_name in row:\n", " value = row[col_name]\n", " # 处理Timestamp类型\n", " if pd.isna(value):\n", " clean_value = None\n", " elif isinstance(value, pd.Timestamp):\n", " clean_value = value.strftime('%Y-%m-%dT%H:%M:%SZ')\n", " else:\n", " clean_value = value\n", " result[widget_id] = {\"value\": clean_value}\n", " return result\n", "\n", " def fields(self):\n", " self.field_mapping = {\n", " '公司名称': '_widget_1751350424090', '门店名称': '_widget_1751350424083',\n", " '门店编码': '_widget_1751350424084',\n", " '运营负责人': '_widget_1751350424085', '区域经理': '_widget_1751350424086',\n", " 'saas开户时间': '_widget_1751350424088', '服务期起始时间': '_widget_1751350424097',\n", " '下单支付成功时间': '_widget_1751350424101', '操作时间': '_widget_1751350424110',\n", " '下单支付成功日期': '_widget_1751350424115', '服务期结束时间': '_widget_1751350424098',\n", " '订单id': '_widget_1751350424075', 'f6订单编号': '_widget_1751350424076',\n", " '宜搭的实例id': '_widget_1751350424077', '商品id': '_widget_1751350424078',\n", " '商品名称': '_widget_1751350424079', '发布商品类型': '_widget_1751350424080',\n", " '发布商品类型描述': '_widget_1751350424081', '门店id': '_widget_1751350424082',\n", " '商户中心id': '_widget_1751350424087', '公司id': '_widget_1751350424089',\n", " '产生来源': '_widget_1751350424091', '产生来源描述': '_widget_1751350424092',\n", " '类型': '_widget_1751350424093', '类型描述': '_widget_1751350424094', '服务年份': '_widget_1751350424095',\n", " '订单服务期第几年': '_widget_1751350424096', '提成业务类型': '_widget_1751350424099',\n", " '提成类别': '_widget_1751350424100', '实付金额（元）': '_widget_1751350424102',\n", " '系统成本价（元）': '_widget_1751350424103', '版本费（元）': '_widget_1751350424104',\n", " '服务费（元）': '_widget_1751350424105', '介绍人员工ID': '_widget_1751350424106',\n", " '介绍业绩归属人员工ID': '_widget_1751350424107', '处理人ID employee_id': '_widget_1751350424108',\n", " '业绩归属人员工ID': '_widget_1751350424109', '处理人是否跟进,0: 未跟进，1: 已跟进': '_widget_1751350424111',\n", " '满意度评分': '_widget_1751350424112', '评价完成时间': '_widget_1751350424113',\n", " '介绍人用户类型': '_widget_1751350424114', '培训完成时间': '_widget_1751350424116',\n", " '订单所处阶段': '_widget_1751350424117', '日分区': '_widget_1751350424118',\n", " }\n", "\n", "\n", "if __name__ == '__main__':\n", " start = ImportPerformanceData()\n", " start.main()\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.6" } }, "nbformat": 4, "nbformat_minor": 5 }