1020 lines
58 KiB
Plaintext
1020 lines
58 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"jupyter": {
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"is_executing": true
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},
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"ExecuteTime": {
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"start_time": "2025-06-19T03:11:41.874106Z"
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}
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},
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"source": [
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"import os\n",
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"import time\n",
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"import requests\n",
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"import pandas as pd\n",
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"import datetime\n",
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"import re\n",
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"from api import API\n",
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"from back_ground_module import CommonModule\n",
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"from log_config import configure_task_logger, configure_error_task_logger\n",
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"\n",
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"api_instance = API()\n",
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"common_module = CommonModule()\n",
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"logger = configure_task_logger()\n",
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"error_task_logger = configure_error_task_logger()\n",
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"\n",
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"\n",
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"class RenewServicesRevisit:\n",
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" \"\"\"用于处理续约服务回访的类。\"\"\"\n",
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"\n",
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" def __init__(self):\n",
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" # 初始化所有数据属性\n",
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" self.index = None\n",
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" self.data_NGV = None\n",
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" self.date_list = None\n",
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" self.Smart_detection = None\n",
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" self.service_remind = None\n",
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" self.json_list = []\n",
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" self.NGV_data_list = None\n",
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" self.permissions_table = None\n",
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" self.staff_id_list = None\n",
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" self.get_feature_usage = None\n",
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" self.policy_recognition = None\n",
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" self.widget_list = None\n",
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" self.private_domain = None\n",
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" self.public_domain = None\n",
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" self.public_domain_list = None\n",
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" self.different_industries = None\n",
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" self.different_industries_list = None\n",
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" self.groupnotification = None\n",
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" self.date_one = None\n",
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" self.all_data = []\n",
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"\n",
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" def calculate_date_one(self, start_offset=0):\n",
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" \"\"\"\n",
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" 计算从当前日期（或指定偏移量的日期）开始，往前遍历遇到date_list中日期的次数。\n",
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"\n",
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" 参数:\n",
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" - start_offset: 从当前日期起始的天数偏移量，默认为0（即今天）。负数表示过去，正数表示未来。\n",
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"\n",
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" 返回:\n",
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" - date_one: 遍历到date_list中日期的次数。\n",
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" \"\"\"\n",
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" now_time = datetime.datetime.now() + datetime.timedelta(days=start_offset)\n",
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" date_one = 1\n",
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" logger.info(f\"当前日期：{now_time.strftime('%Y-%m-%d')}\")\n",
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"\n",
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" if now_time.strftime(\"%Y-%m-%d\") in self.date_list:\n",
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" date_one = 0\n",
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" logger.info(f\"开始次数：{date_one}\")\n",
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" else:\n",
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" for i in range(1, 10):\n",
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" new_date = now_time + datetime.timedelta(days=-i)\n",
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" new_date_str = new_date.strftime(\"%Y-%m-%d\")\n",
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" if new_date_str in self.date_list:\n",
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" date_one += 1\n",
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" logger.info(f\"节假日期：{new_date_str}\")\n",
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" else:\n",
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" break\n",
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" logger.info(f\"遍历次数：{date_one}\")\n",
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" return date_one\n",
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"\n",
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" @staticmethod\n",
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" def download_url_content(url, save_path):\n",
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" \"\"\"下载指定URL的内容并保存到本地文件。\"\"\"\n",
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" try:\n",
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" response = requests.get(url, stream=True)\n",
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" response.raise_for_status()\n",
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" os.makedirs(os.path.dirname(save_path), exist_ok=True)\n",
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" with open(save_path, 'wb') as file:\n",
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" for chunk in response.iter_content(chunk_size=8192):\n",
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" if chunk:\n",
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" file.write(chunk)\n",
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" logger.info(f\"文件已成功保存到 {save_path}\")\n",
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" except requests.exceptions.RequestException as e:\n",
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" logger.error(f\"下载失败: {e}\")\n",
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" except Exception as e:\n",
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" logger.error(f\"发生错误: {e}\")\n",
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"\n",
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" def load_all_data(self):\n",
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" \"\"\"加载所有必要的数据表\"\"\"\n",
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" # 省市区人员关系表\n",
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" payload = {\"api_key\": \"675b900991ad2491c69389ca\", \"entry_id\": \"676512ac3e54dc3159460c0a\"}\n",
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" self.json_list = api_instance.entry_data_list(payload).get(\"data\", [])\n",
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"\n",
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" # 获取简道云员工id\n",
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" payload = {\"api_key\": \"6694d3c4fcb69ca9a111a6c4\", \"entry_id\": \"6769204a1902c9341340a1bc\"}\n",
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" self.staff_id_list = api_instance.entry_data_list(payload).get(\"data\", [])\n",
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"\n",
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" # 获取权限表信息\n",
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" payload = {\"api_key\": \"675b900991ad2491c69389ca\", \"entry_id\": \"675b96c14e839f90fef1647c\"}\n",
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" self.permissions_table = api_instance.entry_data_list(payload).get(\"data\", [])\n",
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"\n",
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" # 获取NGV数据\n",
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" payload = {\"api_key\": \"675b900991ad2491c69389ca\", \"entry_id\": \"675bb02bd2d53c2034c665e4\"}\n",
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" self.NGV_data_list = api_instance.entry_data_list(payload).get(\"data\", [])\n",
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"\n",
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" # 其他数据表加载...\n",
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" # [此处保持原有数据加载逻辑不变]\n",
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"\n",
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" @staticmethod\n",
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" def build_index(json_list):\n",
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" \"\"\"构建省市区人员索引\"\"\"\n",
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" index = {}\n",
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" for json_item in json_list:\n",
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" try:\n",
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" key = (json_item['_widget_1734677164861'],\n",
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" json_item['_widget_1734677164862'],\n",
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" json_item['_widget_1734677164863'])\n",
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" if '_widget_1734677164871' not in json_item:\n",
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" raise KeyError(\"缺少'日常回访客服'键\")\n",
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" index[key] = json_item\n",
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" except KeyError as e:\n",
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" logger.warning(f\"{e}，跳过该条记录: {json_item}\")\n",
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" continue\n",
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" return index\n",
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"\n",
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" @staticmethod\n",
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" def find_customer_service(province_name, city_name, area_name, index):\n",
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" \"\"\"根据省市区查找客服\"\"\"\n",
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" key = (province_name, city_name, area_name)\n",
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" return index.get(key, \"数据缺失: 未找到对应的日常回访客服\")\n",
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"\n",
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" @staticmethod\n",
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" def get_staff_id(row_item, name):\n",
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" \"\"\"根据姓名获取员工ID\"\"\"\n",
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" if str(row_item[\"_widget_1734942794144\"]) == str(name):\n",
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" return row_item[\"_widget_1734942794145\"]\n",
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" return None\n",
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"\n",
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" def assign_customer_service(self, province_name, city_name, area_name, index):\n",
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" \"\"\"根据省市区派发给日常回访客服\"\"\"\n",
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" try:\n",
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" customer_service_info = self.find_customer_service(province_name, city_name, area_name, index)\n",
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"\n",
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" def safe_get_username(data, key):\n",
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" if isinstance(data, dict):\n",
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" return data.get(key, {}).get('username', \"\")\n",
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" return \"\"\n",
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"\n",
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" relationship_manager = safe_get_username(customer_service_info, '_widget_1734677164864')\n",
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" customer_service = safe_get_username(customer_service_info, '_widget_1734677164871')\n",
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" technician = safe_get_username(customer_service_info, '_widget_1734677164866')\n",
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" area_manager = safe_get_username(customer_service_info, '_widget_1734677164865')\n",
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" return relationship_manager, customer_service, technician, area_manager\n",
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" except Exception as e:\n",
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" logger.error(f\"Error finding customer service: {e}\")\n",
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" return \"分配失败，请检查\", \"分配失败，请检查\", \"分配失败，请检查\"\n",
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"\n",
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" def prepare_data(self):\n",
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" \"\"\"准备基础数据\"\"\"\n",
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" # Step 1: 加载所有数据表\n",
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" self.load_all_data()\n",
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"\n",
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" # Step 2: 获取节假日列表\n",
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" self.date_list = common_module.get_holiday_list()\n",
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"\n",
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" # Step 3: 获取NGV数据\n",
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" self.data_NGV = common_module.get_ngv_details(days_back=1).astype(str)\n",
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"\n",
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" # Step 4: 计算日期偏移\n",
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" self.date_one = self.calculate_date_one(start_offset=0)\n",
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"\n",
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" # Step 5: 构建索引\n",
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" self.index = self.build_index(self.json_list)\n",
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"\n",
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" logger.info(\"数据准备完成\")\n",
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"\n",
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" def filter_and_process_data(self):\n",
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" \"\"\"过滤和处理数据\"\"\"\n",
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" # Step 1: 准备数据\n",
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" self.prepare_data()\n",
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"\n",
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" logger.info(\"开始运行主流程\")\n",
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"\n",
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" # 获取原始NGV数据\n",
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" data_NGV = self.data_NGV.copy()\n",
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" # 数据清洗\n",
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" data_NGV = data_NGV.apply(lambda series: series.apply(\n",
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" lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x))\n",
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" \n",
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" # 日期列转换\n",
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" data_NGV['A'] = pd.to_datetime(data_NGV['expiry_time'])\n",
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" data_NGV['B'] = pd.to_datetime(data_NGV['renew_date'])\n",
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" \n",
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"\n",
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" # 定义优先级顺序\n",
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" edition_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']\n",
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" customer_type_order = [\"F\", \"E\", \"D\", \"C\", \"B\", \"A\"]\n",
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" group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）']\n",
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"\n",
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" # 创建映射字典\n",
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" edition_map = {edition: idx for idx, edition in enumerate(edition_order)}\n",
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" customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)}\n",
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" group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)}\n",
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"\n",
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" # 添加排序列\n",
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" data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(int)\n",
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" data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int)\n",
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" data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int)\n",
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"\n",
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" # 找到最佳值\n",
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" best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin()\n",
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" best_edition_rows = data_NGV.loc[best_edition_idx]\n",
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" best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt']\n",
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"\n",
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" best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin()\n",
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" best_customer_type_rows = data_NGV.loc[best_customer_type_idx]\n",
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" best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply(\n",
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" lambda x: customer_type_order[x])\n",
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"\n",
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" best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin()\n",
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" best_group_grade_rows = data_NGV.loc[best_group_grade_idx]\n",
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" best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade']\n",
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"\n",
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" # 合并最佳值\n",
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" best_values = (\n",
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" best_edition_rows[['id_own_group', 'max_saas_edition']]\n",
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" .merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group', how='outer')\n",
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" .merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer')\n",
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" )\n",
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" data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left')\n",
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"\n",
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" # 主店过期过滤\n",
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" condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件\n",
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"\n",
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" ngvv2 = data_NGV[condition]\n",
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"\n",
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" data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中\n",
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" data_NGV_V2['条件'] = ((data_NGV_V2['org_type'] == \"一般\") & (data_NGV_V2['org_status'] == '留存') &\n",
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" (data_NGV_V2['area_manager'] != '殷昊') & (data_NGV_V2['area_manager'] != '孙玉蕾') & (data_NGV_V2['is_main_org'] != 1))\n",
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" data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2[\"条件\"]]\n",
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" # 步骤4: 过滤存在的记录\n",
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" data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group'])\n",
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" filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']]\n",
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"\n",
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" fixed_order = ['皇冠版', '至尊版', '尊享版', '旗舰版', '标准版', '进阶版', '基础版', '入门版']\n",
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" # sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x))\n",
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"\n",
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" fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)}\n",
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" filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map)\n",
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" filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1)\n",
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"\n",
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" result = filtered_data.drop_duplicates(subset='id_own_group', keep='first')\n",
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"\n",
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" data_NGV['条件'] = (data_NGV['org_type'] == \"一般\") & (data_NGV['org_status'] == '留存') & (\n",
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" data_NGV['area_manager'] != '殷昊') & (\n",
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" data_NGV['area_manager'] != '孙玉蕾') & (\n",
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" data_NGV['is_main_org'] == 1)\n",
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" data_NGV = pd.concat([data_NGV, result], axis=0)\n",
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" # data_NGV.to_csv(\"dayin1.csv\")\n",
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" data_details = data_NGV.copy()\n",
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" # data_details.to_excel(r\"C:\\Users\\admin\\Downloads\\1.xlsx\")\n",
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"\n",
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" # 重置索引\n",
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" data_details = data_details.reset_index(drop=True)\n",
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" # data_details.to_csv(\"dayin.csv\")\n",
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" # 判断A列的日期是否大于B列的日期730天，如果是的话，将B列的值设置为1\n",
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" data_details['条件'] = data_details.apply(\n",
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" lambda row: (\n",
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" (pd.to_datetime(row['A']) - pd.to_datetime(row['B'])).days\n",
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" if pd.to_datetime(row['A']) - pd.to_datetime(row['B']) >= pd.Timedelta(days=730)\n",
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" else 0\n",
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" ),\n",
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" axis=1\n",
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" )\n",
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" data_details = data_details.loc[data_details[\"条件\"] > 0]\n",
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"\n",
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"\n",
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" # 定义一个函数，用于将数字除以365并取整数\n",
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" def divide_by_365(x):\n",
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" if isinstance(x, (int, float)):\n",
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" return int(x / 365)\n",
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" else:\n",
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" return x\n",
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"\n",
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" # 使用applymap()函数将divide_by_365函数应用到DataFrame的每个元素\n",
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" data_details['年'] = data_details['条件'].apply(divide_by_365)\n",
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" # 重置索引\n",
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" data_details = data_details.reset_index(drop=True)\n",
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" # data_details.to_excel(r\"C:\\Users\\admin\\Downloads\\2.xlsx\")\n",
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" # 创建一个新的空的DataFrame\n",
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" new_df = pd.DataFrame()\n",
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" # 遍历原始DataFrame的每一行\n",
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" from datetime import datetime\n",
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" for index, row in data_details.iterrows():\n",
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" # 根据A列的值来决定复制的次数\n",
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" if row[\"renew_date\"] != \"2024-02-29\":\n",
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" for i_new in range(1, row['年']):\n",
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" # 修改日期\n",
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" row_new = row.copy()\n",
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" c = row_new[\"renew_date\"]\n",
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" date_obj = datetime.strptime(c, \"%Y-%m-%d\")\n",
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" new_year = date_obj.year + i_new\n",
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" new_date_obj = date_obj.replace(year=new_year)\n",
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" new_c = new_date_obj.strftime(\"%Y-%m-%d\")\n",
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" row_new[\"renew_date\"] = new_c\n",
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" # 将当前行添加到新的DataFrame中\n",
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" # new_df = new_df.append(row_new, ignore_index=True)\n",
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" new_df = pd.concat([new_df, pd.DataFrame([row_new])], ignore_index=True)\n",
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" # 合并两个DataFrame\n",
|
||
" # new_df.to_excel(r\"C:\\Users\\admin\\Downloads\\3.xlsx\")\n",
|
||
" merged_df = pd.concat([data_NGV, new_df], axis=0, ignore_index=True)\n",
|
||
" data_details = merged_df.copy() # 替换名称\n",
|
||
"\n",
|
||
" data_details_not_null = data_details[data_details['renew_date'].notnull()]\n",
|
||
" # data_details_not_null = data_details_not_null[data_details_not_null['renew_date'].str.contains('2023')]\n",
|
||
" # data_details_not_null = data_details_not_null.sort_values(by='renew_date', ascending=True).drop_duplicates(\n",
|
||
" # subset='id_own_group') 重置索引\n",
|
||
" data_details_not_null = data_details_not_null.reset_index(drop=True)\n",
|
||
" data_details = data_details_not_null.copy() # 替换名称 v2\n",
|
||
" data_details['saas_create_time'] = data_details['saas_create_time'].str[:4] # 截取前10位\n",
|
||
" data_details['renew_date_new'] = data_details['renew_date'].str[:4] # 截取前10位\n",
|
||
" data_details = data_details[\n",
|
||
" data_details['saas_create_time'] != data_details['renew_date_new']] # 过滤掉等于renew_date的行\n",
|
||
"\n",
|
||
" data_details = data_details.reset_index(drop=True)\n",
|
||
"\n",
|
||
"\n",
|
||
" import datetime\n",
|
||
" start_time = datetime.datetime.now()\n",
|
||
"\n",
|
||
" date_90 = 83\n",
|
||
" date_120 = 113\n",
|
||
" date_180 = 173\n",
|
||
" # self.date_one = 1\n",
|
||
" now_time = start_time.replace()\n",
|
||
"\n",
|
||
" if now_time.strftime(\"%Y-%m-%d\") in self.date_list:\n",
|
||
" self.date_one = 0\n",
|
||
" print(\"开始次数：\", self.date_one)\n",
|
||
" print(\"当前日期：\", now_time)\n",
|
||
"\n",
|
||
" # 处理每个日期偏移\n",
|
||
" for i in range(0, self.date_one):\n",
|
||
" print(f\"这是第{i}次遍历\")\n",
|
||
" import datetime\n",
|
||
" now_time = datetime.datetime.now() + datetime.timedelta(days=-(i + 1))\n",
|
||
"\n",
|
||
" today = now_time + datetime.timedelta(days=-date_90)\n",
|
||
" formatted_today_90 = today.strftime(\"%Y-%m-%d\")\n",
|
||
" today = now_time + datetime.timedelta(days=-date_120)\n",
|
||
" formatted_today_120 = today.strftime(\"%Y-%m-%d\")\n",
|
||
" today = now_time + datetime.timedelta(days=-date_180)\n",
|
||
" formatted_today_180 = today.strftime(\"%Y-%m-%d\")\n",
|
||
" # print(formatted_today_90, formatted_today_120, formatted_today_180)\n",
|
||
" logger.info(f\"续约回访日期：{formatted_today_90}，{formatted_today_180}\")\n",
|
||
"\n",
|
||
" # 过滤90天回访记录\n",
|
||
" data_details_90 = data_details.copy()\n",
|
||
" data_details_90['条件'] = (\n",
|
||
" (data_details_90['renew_date'] == formatted_today_90) &\n",
|
||
" (data_details_90['group_grade'] != \"普通客户（VIP）\"))\n",
|
||
" data_details_90 = data_details_90.loc[data_details_90[\"条件\"]]\n",
|
||
" data_details_90[\"跟进阶段\"] = \"续约后90天回访\"\n",
|
||
" data_details_90[\"主要目的\"] = \"关怀使用情况，促进更多功能使用，提升系统使用深度。\"\n",
|
||
"\n",
|
||
" # 过滤180天回访记录\n",
|
||
" data_details_180 = data_details.copy()\n",
|
||
" data_details_180['条件'] = (data_details_180['renew_date'] == formatted_today_180)\n",
|
||
" data_details_180 = data_details_180.loc[data_details_180[\"条件\"]]\n",
|
||
" data_details_180[\"跟进阶段\"] = \"续约后180天回访\"\n",
|
||
" data_details_180[\"主要目的\"] = \"关怀使用情况，促进增购商机转化，识别潜在风险，及时提报。\"\n",
|
||
"\n",
|
||
" # 合并回访记录（排除120天回访）\n",
|
||
" data_result = pd.concat([data_details_90, data_details_180], ignore_index=True)\n",
|
||
" logger.info(f\"续约回访人数：{len(data_result)}\")\n",
|
||
"\n",
|
||
" # 处理每个门店数据\n",
|
||
" self.process_shop_data(data_result)\n",
|
||
"\n",
|
||
" def process_shop_data(self, data_NGV):\n",
|
||
" \"\"\"处理每个门店的数据\"\"\"\n",
|
||
"\n",
|
||
" for index_num, row in data_NGV.iterrows():\n",
|
||
" try:\n",
|
||
" payload_dict = {}\n",
|
||
" saas_use_year = re.findall(r'第([0-9]+)年', row[\"saas_use_year\"])[0]\n",
|
||
"\n",
|
||
" # 获取员工ID\n",
|
||
" NGV_roles = {\n",
|
||
" 'relationship_manager': row['service_impl_principal'],\n",
|
||
" 'area_manager': row['area_manager'],\n",
|
||
" 'technician': row['technician'],\n",
|
||
" 'salesmen': row['salesmen'],\n",
|
||
" }\n",
|
||
"\n",
|
||
" for role, name in NGV_roles.items():\n",
|
||
" for row_item in self.staff_id_list:\n",
|
||
" staff_id = self.get_staff_id(row_item, name)\n",
|
||
" if staff_id:\n",
|
||
" NGV_roles[role] = staff_id\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" NGV_roles[role] = None\n",
|
||
"\n",
|
||
" # 分配回访人员\n",
|
||
" if int(saas_use_year) < 4:\n",
|
||
" relationship_manager, area_manager, technician, salesmen = [\n",
|
||
" NGV_roles[role] for role in ['relationship_manager', 'area_manager', 'technician', 'salesmen']\n",
|
||
" ]\n",
|
||
"\n",
|
||
" if not relationship_manager or not technician:\n",
|
||
" relationship_manager, _, technician, _ = self.assign_customer_service(\n",
|
||
" row['province_name'], row['city_name'], row['area_name'], self.index\n",
|
||
" )\n",
|
||
"\n",
|
||
" if row[\"group_grade\"] in [\"普通客户（VIP）\", \"重要客户（SVIP）\"]:\n",
|
||
" payload_dict[\"_widget_1734590278288\"] = {\"value\": relationship_manager}\n",
|
||
" else:\n",
|
||
" payload_dict[\"_widget_1734590278288\"] = {\"value\": technician}\n",
|
||
" else:\n",
|
||
" salesmen = NGV_roles['salesmen']\n",
|
||
" relationship_manager, customer_service, technician, area_manager = self.assign_customer_service(\n",
|
||
" row['province_name'], row['city_name'], row['area_name'], self.index\n",
|
||
" )\n",
|
||
"\n",
|
||
" if row[\"group_grade\"] in [\"普通客户（VIP）\", \"重要客户（SVIP）\"]:\n",
|
||
" payload_dict[\"_widget_1734590278288\"] = {\"value\": customer_service}\n",
|
||
" else:\n",
|
||
" payload_dict[\"_widget_1734590278288\"] = {\"value\": technician}\n",
|
||
"\n",
|
||
" # 其他成员字段赋值\n",
|
||
" payload_dict.update({\n",
|
||
" \"_widget_1734590278289\": {\"value\": relationship_manager},\n",
|
||
" \"_widget_1734590278290\": {\"value\": area_manager},\n",
|
||
" \"_widget_1734590278291\": {\"value\": technician},\n",
|
||
" \"_widget_1735290738545\": {\"value\": salesmen}\n",
|
||
" })\n",
|
||
"\n",
|
||
" # 特殊逻辑处理\n",
|
||
" if payload_dict.get(\"_widget_1734590278288\") == \"02414917880947\":\n",
|
||
" payload_dict[\"_widget_1734590278288\"] = {\"value\": \"051612246035720178\"}\n",
|
||
"\n",
|
||
" # 获取权限信息\n",
|
||
" group_grade = re.sub(r'（[^）]*）', '', row['max_group_grade'])\n",
|
||
" if not row['saas_customer_type'] or row['saas_customer_type'] in ['NA', 'None']:\n",
|
||
" row['saas_customer_type'] = \"F\"\n",
|
||
"\n",
|
||
" NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type']\n",
|
||
" logger.info(f\"权限唯一值：{NGV_store_level_key}\")\n",
|
||
"\n",
|
||
" # 处理权限表逻辑\n",
|
||
" Billing = None\n",
|
||
" for item in self.permissions_table:\n",
|
||
" if NGV_store_level_key == item.get(\"_widget_1734056507963\"): # 合并（等级-类型-分层）\n",
|
||
" print(\"该门店开单的权限是：\", item.get(\"_widget_1734055617039\"))\n",
|
||
" Billing = item.get(\"_widget_1734055617039\") # 开单\n",
|
||
" Service_Alerts = item.get(\"_widget_1734055617040\") # 服务提醒\n",
|
||
" membership = item.get(\"_widget_1734055617041\") # 会员卡\n",
|
||
" SMS = item.get(\"_widget_1734055617042\") # 短信\n",
|
||
" Public_domain_applets = item.get(\"_widget_1734055617043\") # 公域小程序\n",
|
||
" Private_domain_applets = item.get(\"_widget_1734055617044\") # 私域小程序\n",
|
||
" Test_sheet = item.get(\"_widget_1734055617045\") # 检测单\n",
|
||
" AI_poster = item.get(\"_widget_1734055617046\") # AI海报\n",
|
||
" Business_wallets = item.get(\"_widget_1734055617047\") # 企业钱包\n",
|
||
" Precision_marketing = item.get(\"_widget_1734055617049\") # 精准营销\n",
|
||
" Paid_memberships = item.get(\"_widget_1734055617051\") # 付费会员\n",
|
||
" business_WeCom = item.get(\"_widget_1734055617052\") # 企业微信\n",
|
||
" Insurance_policy_identification = item.get(\"_widget_1734055617053\") # 保险单识别\n",
|
||
" Insurance_bots = item.get(\"_widget_1734055617054\") # 保险机器人\n",
|
||
" Camera_pick_up = item.get(\"_widget_1734055617055\") # 摄像头接车\n",
|
||
" Camera_billing = item.get(\"_widget_1734055617056\") # 摄像头开单\n",
|
||
" Transparent_workshop = item.get(\"_widget_1734055617057\") # 透明车间\n",
|
||
" Cross_industry_cooperation = item.get(\"_widget_1734055617058\") # 异业合作\n",
|
||
" BI_Insights = item.get(\"_widget_1734055617059\") # BI洞察\n",
|
||
" payload_dict.update(\n",
|
||
" {\n",
|
||
" \"_widget_1734073342350\": {\"value\": Billing},\n",
|
||
" \"_widget_1735004315757\": {\"value\": Service_Alerts},\n",
|
||
" \"_widget_1735004315756\": {\"value\": membership},\n",
|
||
" \"_widget_1735004315755\": {\"value\": SMS},\n",
|
||
" \"_widget_1735004315754\": {\"value\": Public_domain_applets},\n",
|
||
" \"_widget_1735004315753\": {\"value\": Private_domain_applets},\n",
|
||
" \"_widget_1735004315752\": {\"value\": Test_sheet},\n",
|
||
" \"_widget_1735004315751\": {\"value\": AI_poster},\n",
|
||
" \"_widget_1735004315750\": {\"value\": Business_wallets},\n",
|
||
" \"_widget_1735004315749\": {\"value\": Precision_marketing},\n",
|
||
" \"_widget_1735004315748\": {\"value\": Paid_memberships},\n",
|
||
" \"_widget_1735004315747\": {\"value\": business_WeCom},\n",
|
||
" \"_widget_1735004315746\": {\"value\": Insurance_policy_identification},\n",
|
||
" \"_widget_1735004315745\": {\"value\": Insurance_bots},\n",
|
||
" \"_widget_1735004315744\": {\"value\": Camera_pick_up},\n",
|
||
" \"_widget_1735004315743\": {\"value\": Camera_billing},\n",
|
||
" \"_widget_1735004315742\": {\"value\": Transparent_workshop},\n",
|
||
" \"_widget_1735004315741\": {\"value\": Cross_industry_cooperation},\n",
|
||
" \"_widget_1734073342352\": {\"value\": BI_Insights},\n",
|
||
"\n",
|
||
" }\n",
|
||
" )\n",
|
||
"\n",
|
||
" feature_dict = {\n",
|
||
" \"开单\": \"_widget_1734073342350\",\n",
|
||
" \"服务提醒\": \"_widget_1735004315757\",\n",
|
||
" \"会员卡\": \"_widget_1735004315756\",\n",
|
||
" \"短信\": \"_widget_1735004315755\",\n",
|
||
" \"公域小程序\": \"_widget_1735004315754\",\n",
|
||
" \"私域小程序\": \"_widget_1735004315753\",\n",
|
||
" \"检测单\": \"_widget_1735004315752\",\n",
|
||
" \"AI海报\": \"_widget_1735004315751\",\n",
|
||
" \"企业钱包\": \"_widget_1735004315750\",\n",
|
||
" \"精准营销\": \"_widget_1735004315749\",\n",
|
||
" \"付费会员\": \"_widget_1735004315748\",\n",
|
||
" \"企业微信\": \"_widget_1735004315747\",\n",
|
||
" \"保险单识别\": \"_widget_1735004315746\",\n",
|
||
" \"保险机器人\": \"_widget_1735004315745\",\n",
|
||
" \"摄像头接车\": \"_widget_1735004315744\",\n",
|
||
" \"摄像头开单\": \"_widget_1735004315743\",\n",
|
||
" \"透明车间\": \"_widget_1735004315742\",\n",
|
||
" \"异业合作\": \"_widget_1735004315741\",\n",
|
||
" \"BI洞察\": \"_widget_1734073342352\",\n",
|
||
"\n",
|
||
" }\n",
|
||
" # _widget_1735527329557 下次是否推荐\n",
|
||
" for new_item in self.get_feature_usage:\n",
|
||
" for feature_module, feature_value in feature_dict.items(): # 模块\n",
|
||
" if new_item.get(\"_widget_1735268263079\") == feature_module and new_item.get(\n",
|
||
" \"_widget_1735527329557\") == \"否\" and new_item.get(\n",
|
||
" \"_widget_1735280720550\") == \\\n",
|
||
" row[\"id_own_org\"]: # 下次是否推荐 功能使用情况表\n",
|
||
" print(f\"{feature_value}进行了更改\")\n",
|
||
" payload_dict.update({f\"{feature_value}\": {\"value\": \"×\"}})\n",
|
||
"\n",
|
||
" if new_item.get(\"_widget_1735268263079\") == feature_module and new_item.get(\n",
|
||
" \"_widget_1736414617462\") == \"否\" and new_item.get(\n",
|
||
" \"_widget_1735280720550\") == \\\n",
|
||
" row[\"id_own_org\"]: # 下次是否跟进\n",
|
||
" print(f\"{feature_value}进行了更改\")\n",
|
||
" payload_dict.update({f\"{feature_value}\": {\"value\": \"×\"}})\n",
|
||
"\n",
|
||
" fields_to_check = {\n",
|
||
" \"_widget_1735004315763\": Billing, # 开单\n",
|
||
" \"_widget_1735106258016\": Service_Alerts, # 服务提醒\n",
|
||
" \"_widget_1735106258036\": membership, # 会员卡\n",
|
||
" \"_widget_1735106258086\": SMS, # 短信\n",
|
||
" \"_widget_1735106258112\": Public_domain_applets, # 公域小程序\n",
|
||
" \"_widget_1735106258141\": Private_domain_applets, # 私域小程序\n",
|
||
" \"_widget_1735107354648\": Test_sheet, # 检测单\n",
|
||
" \"_widget_1735107354725\": AI_poster, # AI海报\n",
|
||
" \"_widget_1735107354811\": Business_wallets, # 企业钱包\n",
|
||
" \"_widget_1735107354906\": Precision_marketing, # 精准营销\n",
|
||
" \"_widget_1735107354980\": Paid_memberships, # 付费会员\n",
|
||
" \"_widget_1735107355093\": business_WeCom, # 企业微信\n",
|
||
" \"_widget_1735107355143\": Insurance_policy_identification, # 保险单识别\n",
|
||
" \"_widget_1735107355235\": Insurance_bots, # 保险机器人\n",
|
||
" \"_widget_1735107355333\": Camera_pick_up, # 摄像头接车\n",
|
||
" \"_widget_1735107355392\": Camera_billing, # 摄像头开单\n",
|
||
" \"_widget_1735107355502\": Transparent_workshop, # 透明车间\n",
|
||
" \"_widget_1735107355618\": Cross_industry_cooperation, # 异业合作\n",
|
||
" \"_widget_1735107355740\": BI_Insights # BI洞察\n",
|
||
" }\n",
|
||
"\n",
|
||
" # 遍历每个字段，检查其值并更新payload_dict\n",
|
||
" for widget_id, field_name in fields_to_check.items():\n",
|
||
" if field_name == \"√\":\n",
|
||
" payload_dict.update({widget_id: {\"value\": \"是\"}})\n",
|
||
"\n",
|
||
" break\n",
|
||
"\n",
|
||
" if not Billing:\n",
|
||
" print(f\"权限表请求失败或者权限表无对应关系,权限唯一值是：{NGV_store_level_key}\")\n",
|
||
" \n",
|
||
" # 使用情况\n",
|
||
" if row[\"active_status_fmt\"] == \"活跃\": # 开单 是否使用\n",
|
||
" payload_dict.update({\"_widget_1735004315765\": {\"value\": \"是\"}})\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735004315765\": {\"value\": \"否\"}})\n",
|
||
" try:\n",
|
||
" if row[\"saas_edition_fmt\"] not in [\"基础版\", \"入门版\"]: # 会员卡 是否拥有\n",
|
||
" payload_dict.update({\"_widget_1735106258036\": {\"value\": \"是\"}})\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258036\": {\"value\": \"否\"}})\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"会员卡识别：Error finding customer service: {e}\")\n",
|
||
" try:\n",
|
||
" if row[\"card_bill_day_count_last_30_day\"] != \"0\": # 会员卡 是否使用\n",
|
||
" payload_dict.update({\"_widget_1735106258038\": {\"value\": \"是\"}})\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258038\": {\"value\": \"否\"}})\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"会员卡识别：Error finding customer service: {e}\")\n",
|
||
" # print(self.service_remind.get(\"_widget_1735112637045\"))\n",
|
||
" payload_dict[\"_widget_1735106258018\"] = {\"value\": \"否\"}\n",
|
||
"\n",
|
||
" for item in self.service_remind:\n",
|
||
" if row[\"id_own_group\"] == item.get(\"_widget_1735112637043\"):\n",
|
||
" if int(item.get(\"_widget_1735112637045\")) < 180 and int(\n",
|
||
" item.get(\"_widget_1735112637046\")) == 1: # 服务提醒 是否使用\n",
|
||
" payload_dict.update({\"_widget_1735106258018\": {\"value\": \"是\"}})\n",
|
||
" break\n",
|
||
" elif int(item.get(\"_widget_1735112637048\")) > 0:\n",
|
||
" payload_dict.update({\"_widget_1735106258018\": {\"value\": \"是\"}})\n",
|
||
" break\n",
|
||
"\n",
|
||
" keys_to_check = [\n",
|
||
" \"_widget_1735113110155\"\n",
|
||
" ] # 智能检测 是否使用\n",
|
||
"\n",
|
||
" # 初始化默认值为\"否\"\n",
|
||
" payload_dict[\"_widget_1735107354650\"] = {\"value\": \"否\"}\n",
|
||
"\n",
|
||
" # 检查每个键，如果有一个大于0，则更新为\"是\"并停止检查\n",
|
||
" for key in keys_to_check:\n",
|
||
" for item in self.Smart_detection:\n",
|
||
" if row[\"id_own_org\"] == item.get(\"_widget_1735113110147\"):\n",
|
||
" if int(item.get(key, 0)) > 0: # 使用get方法并提供默认值0防止键不存在的情况\n",
|
||
" payload_dict[\"_widget_1735107354650\"][\"value\"] = \"是\"\n",
|
||
" break\n",
|
||
"\n",
|
||
" # 近30天业务单量=0 则其它所有模块均不推荐\n",
|
||
" try:\n",
|
||
" for feature_module, feature_value in feature_dict.items(): # 模块\n",
|
||
" if row[\"bill_count_last_30_day\"] == '0' and payload_dict[feature_value][\"value\"] == '△':\n",
|
||
" payload_dict.update({f\"{feature_value}\": {\"value\": \"×\"}})\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"不开单识别：Error finding customer service: {e}\")\n",
|
||
" # 保单识别：从系统中抽取目标门店，针对门店抽取修改是否推荐\n",
|
||
" try:\n",
|
||
" if row[\"org_code\"] in self.widget_list:\n",
|
||
" payload_dict.update({'_widget_1735004315746': {\"value\": \"△\"}})\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"保单识别：Error finding customer service: {e}\")\n",
|
||
"\n",
|
||
" # 私域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有\n",
|
||
" try:\n",
|
||
" for item in self.private_domain:\n",
|
||
" if row[\"id_own_group\"] == item.get(\"_widget_1742795002375\"): # 公司id\n",
|
||
" if int(item.get(\"_widget_1742795002379\")) > 0: # 上架商品数\n",
|
||
" payload_dict.update({\"_widget_1735106258143\": {\"value\": \"是\"}}) # DX:是否拥有\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258143\": {\"value\": \"否\"}}) # DX:是否拥有\n",
|
||
" break\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"私域小程序：Error finding customer service: {e}\")\n",
|
||
" try:\n",
|
||
" high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版']\n",
|
||
" if row[\"saas_edition_fmt\"] in high_version:\n",
|
||
" payload_dict.update({'_widget_1735106258141': {\"value\": \"是\"}}) # SYXCX:是否拥有\n",
|
||
" else:\n",
|
||
" payload_dict.update({'_widget_1735106258141': {\"value\": \"否\"}}) # SYXCX:是否拥有\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"私域小程序：Error finding customer service: {e}\")\n",
|
||
"\n",
|
||
" # 公域小程序：根据是否开通微信小程序判断是否使用，旗舰版及以上算拥有\n",
|
||
" try:\n",
|
||
" for item in self.public_domain:\n",
|
||
" if row[\"id_own_org\"] == item.get(\"_widget_1742784257506\"): # 门店id\n",
|
||
" if int(item.get(\"_widget_1742784257509\")) == 1: # 发布商品数量\n",
|
||
" payload_dict.update({\"_widget_1735106258114\": {\"value\": \"是\"}}) # GYXCX:是否使用\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258114\": {\"value\": \"否\"}}) # GYXCX:是否使用\n",
|
||
" break\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"公域小程序：Error finding customer service: {e}\")\n",
|
||
" try:\n",
|
||
" if row[\"id_own_org\"] in self.public_domain_list:\n",
|
||
" payload_dict.update({'_widget_1735106258112': {\"value\": \"是\"}}) # GYXCX:是否拥有\n",
|
||
" else:\n",
|
||
" payload_dict.update({'_widget_1735106258112': {\"value\": \"否\"}}) # GYXCX:是否拥有\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"公域小程序：Error finding customer service: {e}\")\n",
|
||
"\n",
|
||
" # 异业合作：根据是否存在判断是否拥有，过滤条件 商品名称包含异业两个字\n",
|
||
" try:\n",
|
||
" if row[\"id_own_org\"] in self.different_industries_list:\n",
|
||
" payload_dict.update({'_widget_1735107355618': {\"value\": \"是\"}}) # YYHZ:是否拥有\n",
|
||
" else:\n",
|
||
" payload_dict.update({'_widget_1735107355618': {\"value\": \"否\"}}) # YYHZ:是否拥有\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"异业合作：Error finding customer service: {e}\")\n",
|
||
"\n",
|
||
" # 短信：根据是否启动短信功能判断是否拥有,根据\n",
|
||
" try:\n",
|
||
" for item in self.groupnotification:\n",
|
||
" if row[\"id_own_group\"] == item.get(\"_widget_1743065201885\"): # 公司id\n",
|
||
" if int(item.get(\"_widget_1743065201886\")) == 1: # 是否启动短信功能\n",
|
||
" payload_dict.update({\"_widget_1735106258086\": {\"value\": \"是\"}}) # DX:是否拥有\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258086\": {\"value\": \"否\"}}) # DX:是否拥有\n",
|
||
" break\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"短信：Error finding customer service: {e}\")\n",
|
||
" try:\n",
|
||
" for item in self.groupnotification:\n",
|
||
" if row[\"id_own_group\"] == item.get(\"_widget_1743065201885\"): # 公司id\n",
|
||
" if int(item.get(\"_widget_1743065201889\")) > 0: # 累计发送成功总人数\n",
|
||
" payload_dict.update({\"_widget_1735106258088\": {\"value\": \"是\"}}) # DX:是否使用\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" payload_dict.update({\"_widget_1735106258088\": {\"value\": \"否\"}}) # DX:是否使用\n",
|
||
" break\n",
|
||
" except Exception as e:\n",
|
||
" print(f\"短信：Error finding customer service: {e}\")\n",
|
||
" NGV_data_id = None\n",
|
||
" # 获取关联数据\n",
|
||
" for NGV_Data in self.NGV_data_list:\n",
|
||
" # NGV_Data = NGV_Data.get(\"data\")\n",
|
||
" if row[\"org_code\"] == NGV_Data.get(\"_widget_1734062123071\"): # 门店编码\n",
|
||
" NGV_data_id = NGV_Data.get(\"_id\")\n",
|
||
" print(NGV_data_id)\n",
|
||
" try:\n",
|
||
" png_url = NGV_Data.get('_widget_1742890765211', {})[0].get('url', \"\")\n",
|
||
" except:\n",
|
||
" png_url = \"\"\n",
|
||
" print(png_url)\n",
|
||
" if not NGV_data_id:\n",
|
||
" print(\"未找到数据ID\")\n",
|
||
"\n",
|
||
" distribution_date = datetime.datetime.now(datetime.timezone.utc)\n",
|
||
" distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z'\n",
|
||
"\n",
|
||
" upload_key = None\n",
|
||
" UUid = time.strftime(\"%Y%m%d%H%M%S\", time.localtime())\n",
|
||
" if png_url:\n",
|
||
" save_dir = \"sampleCloud\" # 设置输出目录\n",
|
||
"\n",
|
||
" # 创建输出目录（如果不存在）\n",
|
||
" import os\n",
|
||
"\n",
|
||
" os.makedirs(save_dir, exist_ok=True)\n",
|
||
"\n",
|
||
" save_path = fr'{save_dir}\\png\\{time.strftime(\"%Y%m%d%H%M%S\", time.localtime())}.png'\n",
|
||
"\n",
|
||
" RenewServicesRevisit.download_url_content(png_url, save_path)\n",
|
||
"\n",
|
||
" up_data = api_instance.get_upload_token(\n",
|
||
" {\"api_key\": \"675b900991ad2491c69389ca\", \"entry_id\": \"675b9c63925cd404038a6b86\",\n",
|
||
" \"transaction_id\": UUid})\n",
|
||
" upload_url = up_data.get(\"upload_url\")\n",
|
||
" upload_token = up_data.get(\"upload_token\")\n",
|
||
"\n",
|
||
" upload_result = api_instance.upload_file(\n",
|
||
" {\"upload_url\": upload_url, \"upload_token\": upload_token, \"file_path\": save_path})\n",
|
||
" upload_key = upload_result.get(\"key\")\n",
|
||
"\n",
|
||
" payload_dict.update({\n",
|
||
" \"_widget_1734590278279\": {\"value\": row[\"group_name\"]}, # 公司名称\n",
|
||
" \"_widget_1735112931760\": {\"value\": row[\"id_own_group\"]}, # 公司id\n",
|
||
" \"_widget_1735112931761\": {\"value\": row[\"id_own_org\"]}, # 门店id\n",
|
||
" \"_widget_1734590278281\": {\"value\": row['org_name']}, # 门店名称\n",
|
||
" \"_widget_1734590278292\": {\"value\": row[\"跟进阶段\"]}, # 跟进阶段\n",
|
||
" \"_widget_1734321349021\": {\"value\": NGV_data_id}, # 关data_get联数据\n",
|
||
" \"_widget_1742548684369\": {\"value\": row['主要目的']}, # 主要目的\n",
|
||
" \"_widget_1734590278266\": {\"value\": row['region_name']}, # 大区\n",
|
||
" \"_widget_1734590278285\": {\"value\": row['branch_name']}, # 小区\n",
|
||
" \"_widget_1734590278284\": {\"value\": row['province_name']}, # 省\n",
|
||
" \"_widget_1734590278283\": {\"value\": row['city_name']}, # 市\n",
|
||
" \"_widget_1734590278282\": {\"value\": row['area_name']}, # 区\n",
|
||
" \"_widget_1734590278278\": {\"value\": row['saas_customer_type']}, # 门店分层\n",
|
||
" \"_widget_1734590278277\": {\"value\": row['group_grade']}, # 公司等级\n",
|
||
" \"_widget_1734590278276\": {\"value\": row['limit_user_type']}, # 限制账户类型\n",
|
||
" \"_widget_1734590278275\": {\"value\": row['active_user_type']}, # 有效账户类型\n",
|
||
" \"_widget_1734590278274\": {\"value\": row['saas_version']}, # ERP操作模式\n",
|
||
" \"_widget_1734590278273\": {\"value\": row['saas_use_year']}, # 使用时长\n",
|
||
" \"_widget_1734590278272\": {\"value\": row['org_stage']}, # 门店阶段\n",
|
||
" \"_widget_1734590278271\": {\"value\": row['manage_model']}, # 经营模式\n",
|
||
" \"_widget_1734590278267\": {\"value\": row['contacts']}, # 联系人\n",
|
||
" \"_widget_1734590278287\": {\"value\": row['contact_mobile']}, # 联系手机号\n",
|
||
" \"_widget_1734590278286\": {\"value\": row['saas_edition_fmt']}, # SaaS版本\n",
|
||
" \"_widget_1734590278280\": {\"value\": row['org_code']}, # 门店编码\n",
|
||
" # \"_widget_1735287791875\": {\"value\": row['salesmen']}, # 销售负责人\n",
|
||
" \"_widget_1735096489244\": {\"value\": distribution_date}, # 派发时间\n",
|
||
" \"_widget_1742895342914\": {\"value\": row['business_scope_fmt']}, # 经营范围\n",
|
||
" \"_widget_1742895342915\": {\"value\": row['station_number']}, # 工位数\n",
|
||
" \"_widget_1742895342916\": {\"value\": [upload_key]} # 门头照片\n",
|
||
" })\n",
|
||
"\n",
|
||
" routine_follow_up_payload = {\n",
|
||
" \"api_key\": \"675b900991ad2491c69389ca\",\n",
|
||
" \"entry_id\": \"675b9c63925cd404038a6b86\",\n",
|
||
" \"is_start_workflow\": \"true\",\n",
|
||
" \"data\": payload_dict,\n",
|
||
" \"transaction_id\": UUid\n",
|
||
" }\n",
|
||
"\n",
|
||
" print(routine_follow_up_payload)\n",
|
||
"\n",
|
||
" res = api_instance.data_batch_create(routine_follow_up_payload)\n",
|
||
" logger.info(f\"创建结果：{res}\")\n",
|
||
" \n",
|
||
"\n",
|
||
" except Exception as e:\n",
|
||
" error_task_logger.error(f\"处理门店数据时出错: {e}\")\n",
|
||
" continue\n",
|
||
" \n",
|
||
"\n",
|
||
" def main(self):\n",
|
||
" \"\"\"主入口方法\"\"\"\n",
|
||
" task_start_time = datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n",
|
||
" # try:\n",
|
||
" self.filter_and_process_data()\n",
|
||
" common_module.send_task_status(task_start_time, \"续约客户回访\")\n",
|
||
" logger.info(\"任务执行成功\")\n",
|
||
" # except Exception as e:\n",
|
||
" # error_task_logger.error(f\"任务执行失败: {e}\")\n",
|
||
" df = pd.DataFrame(self.all_data)\n",
|
||
" df.to_csv(\"all_data.csv\")\n",
|
||
"\n",
|
||
"\n",
|
||
"if __name__ == '__main__':\n",
|
||
" start = RenewServicesRevisit()\n",
|
||
" start.main()\n"
|
||
],
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"已获取 100 条数据\n",
|
||
"已获取 200 条数据\n",
|
||
"已获取 300 条数据\n",
|
||
"已获取 400 条数据\n",
|
||
"已获取 500 条数据\n",
|
||
"已获取 600 条数据\n",
|
||
"已获取 700 条数据\n",
|
||
"已获取 800 条数据\n",
|
||
"已获取 900 条数据\n",
|
||
"已获取 1000 条数据\n",
|
||
"已获取 1100 条数据\n",
|
||
"已获取 1200 条数据\n",
|
||
"已获取 1300 条数据\n",
|
||
"已获取 1400 条数据\n",
|
||
"已获取 1500 条数据\n",
|
||
"已获取 1600 条数据\n",
|
||
"已获取 1700 条数据\n",
|
||
"已获取 1800 条数据\n",
|
||
"已获取 1900 条数据\n",
|
||
"已获取 2000 条数据\n",
|
||
"已获取 2100 条数据\n",
|
||
"已获取 2200 条数据\n",
|
||
"已获取 2300 条数据\n",
|
||
"已获取 2400 条数据\n",
|
||
"已获取 2500 条数据\n",
|
||
"已获取 2600 条数据\n",
|
||
"已获取 2700 条数据\n",
|
||
"已获取 2800 条数据\n",
|
||
"已获取 2900 条数据\n",
|
||
"已获取 3000 条数据\n",
|
||
"已获取 3100 条数据\n",
|
||
"已获取 3200 条数据\n",
|
||
"已获取 3300 条数据\n",
|
||
"已获取 3400 条数据\n",
|
||
"已获取 3500 条数据\n",
|
||
"已获取 3600 条数据\n",
|
||
"已获取 3667 条数据\n",
|
||
"已获取 100 条数据\n",
|
||
"已获取 140 条数据\n",
|
||
"已获取 100 条数据\n",
|
||
"已获取 192 条数据\n",
|
||
"已获取 100 条数据\n",
|
||
"已获取 200 条数据\n",
|
||
"已获取 300 条数据\n",
|
||
"已获取 400 条数据\n",
|
||
"已获取 500 条数据\n",
|
||
"已获取 600 条数据\n",
|
||
"已获取 700 条数据\n",
|
||
"已获取 800 条数据\n",
|
||
"已获取 900 条数据\n",
|
||
"已获取 1000 条数据\n",
|
||
"已获取 1100 条数据\n",
|
||
"已获取 1200 条数据\n",
|
||
"已获取 1300 条数据\n",
|
||
"已获取 1400 条数据\n",
|
||
"已获取 1500 条数据\n",
|
||
"已获取 1600 条数据\n",
|
||
"已获取 1700 条数据\n",
|
||
"已获取 1800 条数据\n",
|
||
"已获取 1900 条数据\n",
|
||
"已获取 2000 条数据\n",
|
||
"已获取 2100 条数据\n",
|
||
"已获取 2200 条数据\n",
|
||
"已获取 2300 条数据\n",
|
||
"已获取 2400 条数据\n",
|
||
"已获取 2500 条数据\n",
|
||
"已获取 2600 条数据\n",
|
||
"已获取 2700 条数据\n",
|
||
"已获取 2800 条数据\n",
|
||
"已获取 2900 条数据\n",
|
||
"已获取 3000 条数据\n",
|
||
"已获取 3100 条数据\n",
|
||
"已获取 3200 条数据\n",
|
||
"已获取 3300 条数据\n",
|
||
"已获取 3400 条数据\n",
|
||
"已获取 3500 条数据\n",
|
||
"已获取 3600 条数据\n",
|
||
"已获取 3700 条数据\n",
|
||
"已获取 3800 条数据\n",
|
||
"已获取 3900 条数据\n",
|
||
"已获取 4000 条数据\n",
|
||
"已获取 4100 条数据\n",
|
||
"已获取 4200 条数据\n",
|
||
"已获取 4300 条数据\n",
|
||
"已获取 4400 条数据\n",
|
||
"已获取 4500 条数据\n",
|
||
"已获取 4600 条数据\n",
|
||
"已获取 4700 条数据\n",
|
||
"已获取 4800 条数据\n",
|
||
"已获取 4900 条数据\n",
|
||
"已获取 5000 条数据\n",
|
||
"已获取 5100 条数据\n",
|
||
"已获取 5200 条数据\n",
|
||
"已获取 5300 条数据\n",
|
||
"已获取 5400 条数据\n",
|
||
"已获取 5500 条数据\n",
|
||
"已获取 5600 条数据\n",
|
||
"已获取 5700 条数据\n",
|
||
"已获取 5800 条数据\n",
|
||
"已获取 5900 条数据\n",
|
||
"已获取 6000 条数据\n",
|
||
"已获取 6100 条数据\n",
|
||
"已获取 6200 条数据\n",
|
||
"已获取 6300 条数据\n",
|
||
"已获取 6400 条数据\n",
|
||
"已获取 6500 条数据\n",
|
||
"已获取 6600 条数据\n",
|
||
"已获取 6700 条数据\n",
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"已获取 7500 条数据\n",
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"已获取 7600 条数据\n",
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"已获取 7700 条数据\n",
|
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"已获取 7800 条数据\n",
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"已获取 7900 条数据\n",
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"已获取 8000 条数据\n",
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"已获取 8200 条数据\n",
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"已获取 8300 条数据\n",
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"已获取 8900 条数据\n",
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"已获取 9000 条数据\n",
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"已获取 9100 条数据\n",
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"已获取 9200 条数据\n",
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"已获取 9300 条数据\n",
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"已获取 9400 条数据\n",
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"已获取 9500 条数据\n",
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"已获取 9600 条数据\n",
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"已获取 10000 条数据\n",
|
||
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"已获取 10200 条数据\n",
|
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"已获取 10300 条数据\n",
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"已获取 10500 条数据\n",
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"已获取 10600 条数据\n",
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||
"已获取 10700 条数据\n",
|
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"已获取 10800 条数据\n",
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||
"已获取 10900 条数据\n",
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|
||
]
|
||
}
|
||
],
|
||
"execution_count": null
|
||
}
|
||
],
|
||
"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
|
||
}
|