351 lines
15 KiB
Python
351 lines
15 KiB
Python
import os
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from datetime import datetime
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import pandas as pd
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from api import API
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from back_ground_module import CommonModule
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from log_config import configure_task_logger, configure_error_task_logger
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logger = configure_task_logger()
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error_task_logger = configure_error_task_logger()
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api_instance = API()
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common_module = CommonModule()
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output_dir = "output" # 设置输出目录
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os.makedirs(output_dir, exist_ok=True)
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class RenewalToDo:
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def __init__(self):
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self.province_staff_id_list = None
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self.json_list = None
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self.data_NGV = None
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self.staff_id_list = None
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self.NGV_data_list = None
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self.field_map = {
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"关联数据": "_widget_1764820541663",
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"公司名称": "_widget_1764820541616",
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"门店名称": "_widget_1764820541617",
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"门店编码": "_widget_1764820541661",
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"加盟商": "_widget_1764820541618",
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"过期日": "_widget_1764820541672",
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"Saas版本": "_widget_1764820541623",
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"上次购买价格": "_widget_1764820541624",
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"联系人": "_widget_1764820541621",
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"联系手机号": "_widget_1764820541622",
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"专属运营顾问": "_widget_1764820541625",
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"区域客服": "_widget_1764820541715",
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"运营专家": "_widget_1764820541678",
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"120天是否跟进": "_widget_1764820541628",
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"120天处理人": "_widget_1764820541634",
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"120天跟进时间": "_widget_1765352838631",
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"60天是否跟进": "_widget_1764820541630",
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"60天处理人": "_widget_1764820541635",
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"60天跟进时间": "_widget_1765352838632",
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"30天是否跟进": "_widget_1764820541632",
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"30天处理人": "_widget_1764820541636",
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"30天跟进时间": "_widget_1765352838633",
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"是否联系上客户": "_widget_1764820541638",
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"客户现阶段问题分类": "_widget_1764820541641",
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"未联系上原因字段": "_widget_1765330820509",
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"联系情况及问题说明": "_widget_1764820541653",
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"潜在商机": "_widget_1764820541657",
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"商机详情": "_widget_1764820541659",
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"门店续约意愿": "_widget_1764820541654",
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"不续约原因": "_widget_1764820541700",
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"产品原因": "_widget_1764820541707",
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"服务问题": "_widget_1764820541709",
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"门店原因": "_widget_1764820541711",
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"价格原因": "_widget_1764820541713",
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"不续约具体情况说明": "_widget_1764820541702",
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"回访完成方式": "_widget_1764820541697",
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"周期性增购": "_widget_1764820541717",
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"周期性增购.商品名称": "_widget_1764820541717._widget_1764820541719",
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"周期性增购.分母金额": "_widget_1764820541717._widget_1764820541720",
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"周期性增购.应续约日": "_widget_1764820541717._widget_1764820541721",
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"周期性增购.上次购买数量": "_widget_1764820541717._widget_1764820541722",
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"周期性增购.不续约原因": "_widget_1764820541717._widget_1764820541723",
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"周期性增购.是否愿意续约": "_widget_1764820541717._widget_1764820541724",
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"周期性增购.续约后订单编码": "_widget_1764820541717._widget_1764820541725",
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"订单编码": "_widget_1764820541674",
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"订单支付日期": "_widget_1764820541679",
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"本次-实付金额（元）": "_widget_1764820541676",
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"业务类型（续约、升级）": "_widget_1764820541680",
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"连锁门店待办同步处理": "_widget_1764820541681",
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"选择需要同步的门店名称": "_widget_1765330820391",
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"过期日后90天日期": "_widget_1764820541865",
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"当前所处节点": "_widget_1765352838609",
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"流程状态": "_widget_1765352838610",
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"提交人": "creator",
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"提交时间": "createTime",
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"更新时间": "updateTime"
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}
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self.cn_field_map = {
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"related_data": "关联数据",
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"group_name": "公司名称",
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"org_name": "门店名称",
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"org_code": "门店编码",
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"franchisee": "加盟商", # 新加字段
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"expiry_time": "过期日",
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"saas_edition_fmt": "Saas版本",
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"last_purchase_price": "上次购买价格", # 新加字段
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"contacts": "联系人",
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"contact_mobile": "联系手机号",
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"service_impl_principal": "专属运营顾问",
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"regional_customer_service": "区域客服", # 新加字段
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"technician": "运营专家",
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}
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def load_all_data(self):
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"""
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从各类来源加载数据上加载数据
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:return:
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"""
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# 获取NGV数据
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payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"}
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self.NGV_data_list = api_instance.entry_data_list(payload).get("data")
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# 获取简道云员工id
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payload = {"api_key": "6694d3c4fcb69ca9a111a6c4",
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"entry_id": "6769204a1902c9341340a1bc",
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}
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staff_id = api_instance.entry_data_list(payload)
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self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里
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# 省市区人员关系表
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payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"}
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json_dict = api_instance.entry_data_list(payload)
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if json_dict and "data" in json_dict:
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self.province_staff_id_list = json_dict.get("data")
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else:
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print("加载省市区人员关系表失败")
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self.province_staff_id_list = []
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# 数据库获取续约回访数据
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self.data_NGV = common_module.get_renewal_details()
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@staticmethod
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def replace_names_with_staff_ids(df, name_columns, staff_id_list):
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"""
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将 DataFrame 中多个姓名列替换为对应的员工ID。
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:param staff_id_list: 简道云获取到员工id
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:param df: pandas.DataFrame
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:param name_columns: list[str]，需要替换的姓名列名列表，例如 ["col1", "col2"]
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:return: 修改后的 DataFrame（原列被替换）
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"""
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# 1. 构建姓名 -> 员工ID 的映射字典（只做一次）
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name_to_id = {}
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for item in staff_id_list or []:
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name = item.get("_widget_1734942794144")
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staff_id = item.get("_widget_1734942794145")
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if name and staff_id:
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name_to_id[str(name).strip()] = str(staff_id)
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# 2. 对每个指定的列进行替换
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df = df.copy() # 避免修改原始数据
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for col in name_columns:
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if col not in df.columns:
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continue # 跳过不存在的列
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# 替换：姓名 → ID，找不到的保留原值（可改为 fillna(None)）
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df[col] = (
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df[col]
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.astype(str)
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.str.strip()
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.map(name_to_id)
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.fillna(df[col])
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)
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return df
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@staticmethod
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def row_to_dict(row, field_mapping):
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"""将一行数据转换为指定格式的字典"""
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result = {}
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for col_name, widget_id in field_mapping.items():
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if col_name in row:
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value = row[col_name]
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# 处理Timestamp类型
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if pd.isna(value):
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clean_value = None
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elif isinstance(value, pd.Timestamp):
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clean_value = value.strftime('%Y-%m-%dT%H:%M:%SZ')
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else:
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clean_value = value
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result[widget_id] = {"value": clean_value}
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return result
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@staticmethod
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def en_row_to_cn_row(en_row, en_to_cn_map):
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"""
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将英文字段的行数据转换为中文字段的行数据
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:param en_row: dict 或 pandas.Series，key 为英文字段
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:param en_to_cn_map: dict, 英文字段名 -> 中文字段名
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:return: dict，key 为中文字段名
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"""
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cn_row = {}
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for en_key, value in en_row.items():
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if en_key in en_to_cn_map:
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cn_key = en_to_cn_map[en_key]
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cn_row[cn_key] = value
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# 可选：忽略无法映射的字段，或记录警告
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return cn_row
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@staticmethod
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def get_customer_service_by_location(province_name, city_name, area_name, staff_id_list):
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"""
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直接遍历 self.staff_id_list，根据省市区匹配续约回访客服。
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:return: 客服用户名（str），未找到则返回提示信息
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"""
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if not all([province_name, city_name, area_name]):
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return "数据缺失: 省市区不完整"
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for item in staff_id_list or []:
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try:
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prov = item.get('_widget_1734677164861', '').strip()
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city = item.get('_widget_1734677164862', '').strip()
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area = item.get('_widget_1734677164863', '').strip()
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if (prov == province_name.strip() and
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city == city_name.strip() and
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area == area_name.strip()):
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# 提取客服用户名
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staff_info = item.get('_widget_1734677164869', {}) # 续约回访客服
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username = staff_info.get('username')
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return username if username else "数据缺失: 客服用户名为空"
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except Exception :
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continue # 跳过格式异常的记录
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return "数据缺失: 未找到对应的续约回访客服"
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def process_data(self):
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"""
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数据处理加工
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:return:
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"""
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data_NGV = self.data_NGV
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# data_NGV.to_csv(os.path.join(output_dir, "续约回访待办派发.csv"))
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# 日期字段替换为UTC时间
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time_columns = ['expiry_time']
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data_NGV[time_columns] = data_NGV[time_columns].apply(
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lambda col: pd.to_datetime(col, errors='coerce')
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.dt.tz_localize('Asia/Shanghai') # 假设原时间是北京时间
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.dt.tz_convert('UTC') # 转为 UTC
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.dt.strftime('%Y-%m-%d %H:%M:%S') # 格式化为字符串（无时区标记）
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)
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# 成员字段替换
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staff_name_cols = [
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"service_impl_principal",
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"technician",
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]
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data_NGV = self.replace_names_with_staff_ids(data_NGV, staff_name_cols, self.staff_id_list)
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return data_NGV
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def dispatch_task(self, data_NGV):
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"""
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一次性构建所有记录并派发（依赖 api_instance 内部的分批与容错）
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"""
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records = []
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no_customer_service_data = []
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for _, row in data_NGV.iterrows():
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NGV_data_id = None
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# 派发逻辑
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# step1:优先从 data_NGV 获取省市区信息
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province_name = row.get('province_name')
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city_name = row.get('city_name')
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area_name = row.get('area_name') if 'area_name' in row else row.get('district_name')
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# 检查省市区是否完整（省市区是一体的，任意一个缺失就需要从NGV获取）
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use_ngv_location = False
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if (not province_name or province_name in ['', 'None', 'NA'] or
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not city_name or city_name in ['', 'None', 'NA'] or
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not area_name or area_name in ['', 'None', 'NA']):
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use_ngv_location = True
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logger.info(f"门店 {row['org_code']} 的省市区信息不完整，将从NGV_data_list获取")
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# step2:获取关联数据
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for NGV_Data in self.NGV_data_list:
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# NGV_Data = NGV_Data.get("data")
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if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码
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NGV_data_id = NGV_Data.get("_id") # 数据id
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# 如果需要从 NGV_data_list 获取省市区信息
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if use_ngv_location:
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province_name = NGV_Data.get("_widget_1734062123090")
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city_name = NGV_Data.get("_widget_1734062123092")
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area_name = NGV_Data.get("_widget_1734062123094")
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logger.info(
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f"【从NGV获取省市区】门店 {row['org_code']}: {province_name}, {city_name}, {area_name}")
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# step3:根据省市区填充续约待办客服
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# 检查省市区是否都有值，如果有任何一个为空，则客服为空
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if (not province_name or province_name in ['', 'None', 'NA'] or
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not city_name or city_name in ['', 'None', 'NA'] or
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not area_name or area_name in ['', 'None', 'NA']):
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customer_service = None
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logger.warning(
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f"【省市区信息缺失】门店 {row['org_code']} 省市区信息不完整，续约回访客服设置为空")
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logger.warning(f"省: {province_name}, 市: {city_name}, 区: {area_name}")
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else:
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customer_service = self.get_customer_service_by_location(province_name, city_name, area_name,
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self.province_staff_id_list)
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logger.info(f"【派发客服】门店 {row['org_code']} 派发给客服: {customer_service}")
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# step4:非NGV字段添加到row中
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if NGV_data_id: # 关联数据
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row["related_data"] = NGV_data_id
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else:
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row["related_data"] = None
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logger.warning(f"未找到关联数据，请检查门店编码: {row['org_code']}")
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if customer_service: # 区域客服
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row["regional_customer_service"] = customer_service
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else:
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# 找不到省市区续约待办客服
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no_customer_service_data.append(row)
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row["regional_customer_service"] = None
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logger.warning(f"未找到区域客服，请检查门店编码: {row['org_code']}")
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# 列名替换为中文
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cn_row = self.en_row_to_cn_row(row, self.cn_field_map)
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# 简道云字段替换
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widget_dict = self.row_to_dict(cn_row, self.field_map)
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records.append(widget_dict)
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if not records:
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logger.info("无数据需要派发")
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return
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payload = {
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"api_key": "675b900991ad2491c69389ca",
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"entry_id": "6931063d64187eaf6b927557",
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"data_list": records
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}
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api_instance.entry_data_batch_create(payload)
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logger.info(f"已提交 {len(records)} 条数据进行派发")
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def main(self):
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task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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try:
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logger.info("任务开始")
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# step1: 获取数据
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self.load_all_data()
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logger.info("加载数据完成")
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# step2:数据处理
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data_NGV = self.process_data()
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# step3:数据派发
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self.dispatch_task(data_NGV)
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common_module.send_task_status(task_start_time, "续约回访待办")
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except Exception as e:
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error_task_logger.error(f"续约回访待办发生错误{e}")
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common_module.send_task_error(task_start_time, "续约回访待办", str(e))
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if __name__ == '__main__':
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RenewalToDo().main()
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