274 lines
12 KiB
Python
274 lines
12 KiB
Python
"""
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客户相关后台任务模块
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本模块包含客户相关的后台任务，包括：
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- 客户信息批量修改
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这些任务在后台线程中执行，不会阻塞主请求。
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"""
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import logging
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import requests
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import pandas as pd
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import time
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import re
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from typing import Dict, Any, Optional
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from app.tasks.common import update_jiandaoyun, approve_workflow
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logger = logging.getLogger('app')
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def modify_customer_info_background(data: Dict[str, Any], cookies: Dict[str, str], df: pd.DataFrame, save_path: str):
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"""
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修改客户信息后台任务
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在后台线程中批量修改客户信息，从 Excel 文件中读取客户手机号和修改信息。
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执行完成后会更新简道云表单并自动提交工作流。
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Args:
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data: 包含表单ID(api_key)、表单ID(entry_id)、数据ID(data_id)的字典
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cookies: 用户登录 F6 系统的 cookies 信息
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df: Excel 文件读取的内容，DataFrame 格式，第一列为客户手机号
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save_path: Excel 文件保存的地址，执行完成后会删除此文件
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Returns:
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None
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注意:
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- 根据客户手机号匹配客户信息
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- 执行完成后会自动删除上传的文件
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- 执行结果会更新到简道云表单
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"""
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df = df.where(pd.notnull(df), None)
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params = {
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'pageSize': 100,
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'pageNo': '1',
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}
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res = requests.get(
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'https://yunxiu.f6car.cn/member/customer/listForPermission',
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params=params,
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cookies=cookies,
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)
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total = int(res.json().get("data").get("total"))
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total_pages = (total // params["pageSize"]) + (1 if total % params["pageSize"] > 0 else 0)
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print(f"总计{total_pages}页")
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all_customers = []
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max_retries = 10
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retry_count = 0
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for page in range(1, total_pages + 1):
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print(f"正在请求第 {page} 页...")
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params["pageNo"] = page
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while retry_count < max_retries:
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response = requests.get(
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'https://yunxiu.f6car.cn/member/customer/listForPermission',
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params=params,
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cookies=cookies,
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timeout=10
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)
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time.sleep(1)
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if response.status_code == 200:
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suppliers = response.json().get("data", {}).get("data", [])
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all_customers.extend(suppliers)
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break
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else:
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retry_count += 1
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print(f"请求第 {page} 页失败，正在重试（第 {retry_count} 次）...")
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time.sleep(3)
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# 获取专属运营顾问列表
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json_data = {
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'includeStopedEmployee': False,
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'pageSize': 1000,
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'filterNullUser': False,
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'keyword': '',
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'idOwnOrgList': [],
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}
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response = requests.post(
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'https://yunxiu.f6car.cn/hive/employee/searchStaffInGroup',
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cookies=cookies,
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json=json_data,
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)
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staff_list = response.json().get("data").get("list")
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name_to_userid = {
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emp['name']: emp['userId']
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for emp in staff_list
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if emp['userId'] is not None
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}
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df['userId'] = df['专属运营顾问'].map(name_to_userid)
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def extract_province_city_district(address: Optional[str]) -> Dict[str, Optional[str]]:
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"""安全解析省市区信息，所有返回值都可能为None"""
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if not address:
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return {'省': None, '市': None, '区': None}
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try:
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pattern = r'(?P<省>(?:[\u4e00-\u9fa5]+(?:省|自治区|特别行政区))?)' \
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r'(?P<市>(?:[\u4e00-\u9fa5]+(?:市|自治州|地区|盟))?)' \
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r'(?P<区>(?:[\u4e00-\u9fa5]+区|[\u4e00-\u9fa5]+县|[\u4e00-\u9fa5]+旗)?)'
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match = re.match(pattern, address.strip())
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return {k: v if v else None for k, v in match.groupdict().items()} if match else {'省': None, '市': None,
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'区': None}
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except Exception:
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return {'省': None, '市': None, '区': None}
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def safe_get(d: Optional[Dict], *keys, default=None):
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"""多层字典安全获取值，始终返回可能为None的值"""
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if not isinstance(d, dict):
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return default
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for key in keys:
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d = d.get(key, {})
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if not isinstance(d, dict):
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break
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return d if d != {} else default
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def convert_to_request_data(original_data: Optional[Dict[str, Any]], df: pd.DataFrame) -> Dict[str, Any]:
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"""
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完全安全的字典转换函数
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特点：
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1. 每个字段的值都可能为None
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2. 不会因为任何字段为空而报错
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3. 不使用任何默认值，完全保留原始数据的空值状态
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"""
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customer_info = safe_get(original_data, 'data', 'customerInfo') if original_data else None
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address_parts = extract_province_city_district(
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safe_get(customer_info, 'provinceCityAreaName') if customer_info else None
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)
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cell_phone = safe_get(customer_info, 'cellPhone')
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exclusive_info = None
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df_row = None
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if cell_phone and not df.empty:
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matched_rows = df[df['客户手机号'] == cell_phone]
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if not matched_rows.empty:
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df_row = matched_rows.iloc[0]
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exclusive_info = {
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'userId': df_row.get('userId'),
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'name': df_row.get('专属运营顾问')
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}
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request_data = {
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"pkId": safe_get(customer_info, 'idCustomer'),
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"idCustomer": safe_get(customer_info, 'idCustomer'),
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"name": df_row.get('客户姓名') if df_row is not None and pd.notna(df_row.get('客户姓名')) else safe_get(
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customer_info, 'name'),
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"sex": safe_get(customer_info, 'sex'),
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"customerType": df_row.get('客户类型') if df_row is not None and pd.notna(
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df_row.get('客户类型')) else safe_get(
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customer_info, 'customerType'),
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"customerSource": safe_get(customer_info, 'customerSource'),
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"customerSourceName": df_row.get('客户来源') if df_row is not None and pd.notna(
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df_row.get('客户来源')) else safe_get(customer_info, 'customerSourceName'),
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"companyName": df_row.get('单位名称') if df_row is not None and pd.notna(
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df_row.get('单位名称')) else safe_get(
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customer_info, 'companyName'),
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"cellPhone": cell_phone,
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"wechart": safe_get(customer_info, 'wechart'),
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"qq": safe_get(customer_info, 'qq'),
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"contacts": safe_get(customer_info, 'contacts'),
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"contactTelephone": safe_get(customer_info, 'contactTelephone'),
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"province": safe_get(customer_info, 'province'),
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"city": safe_get(customer_info, 'city'),
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"area": safe_get(customer_info, 'area'),
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"street": safe_get(customer_info, 'street'),
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"address": safe_get(customer_info, 'address'),
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"detailAddress": safe_get(customer_info, 'detailAddress'),
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"pId": safe_get(customer_info, 'province'),
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"cId": safe_get(customer_info, 'city'),
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"aId": safe_get(customer_info, 'area'),
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"provinceName": address_parts.get('省'),
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"cityName": address_parts.get('市'),
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"areaName": address_parts.get('区'),
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"provinceCityAreaName": safe_get(customer_info, 'provinceCityAreaName'),
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"birthday": safe_get(customer_info, 'birthday'),
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"creationtime": safe_get(customer_info, 'creationtime'),
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"modifiedtime": safe_get(customer_info, 'modifiedtime'),
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"creator": safe_get(customer_info, 'creator'),
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"creatorName": safe_get(customer_info, 'creatorName'),
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"modifier": safe_get(customer_info, 'modifier'),
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"idOwnOrg": safe_get(customer_info, 'idOwnOrg'),
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"idOwnGroup": safe_get(customer_info, 'idOwnGroup'),
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"insuranceCompany": safe_get(customer_info, 'insuranceCompany'),
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"maritalStatus": safe_get(customer_info, 'maritalStatus'),
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"monthlyIncome": safe_get(customer_info, 'monthlyIncome'),
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"idNumber": safe_get(customer_info, 'idNumber'),
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"personHobby": safe_get(customer_info, 'personHobby'),
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"credentialsType": safe_get(customer_info, 'credentialsType'),
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"points": safe_get(customer_info, 'points'),
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"maxAccountAmount": safe_get(customer_info, 'maxAccountAmount'),
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"pointsEnable": safe_get(customer_info, 'pointsEnable'),
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"level": safe_get(customer_info, 'level'),
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"memberCardNo": safe_get(customer_info, 'memberCardNo'),
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"customerLevel": safe_get(customer_info, 'customerLevel'),
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"exclusiveConsultantId": exclusive_info['userId'] if exclusive_info else safe_get(customer_info,
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'exclusiveConsultantId'),
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"exclusiveConsultantName": exclusive_info['name'] if exclusive_info else safe_get(customer_info,
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'exclusiveConsultantName'),
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"exclusiveOrgId": safe_get(customer_info, 'exclusiveOrgId'),
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"exclusiveOrgName": safe_get(customer_info, 'exclusiveOrgName'),
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"customerMemo": df_row.get('客户备注') if df_row is not None and pd.notna(
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df_row.get('客户备注')) else safe_get(
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customer_info, 'customerMemo'),
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"isDel": safe_get(customer_info, 'isDel'),
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"idFrom": safe_get(customer_info, 'idFrom'),
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"mnemonic": safe_get(customer_info, 'mnemonic'),
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"idOrgSource": safe_get(customer_info, 'idOrgSource'),
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"firstArrivalIdSourceBill": safe_get(customer_info, 'firstArrivalIdSourceBill'),
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"lastArrivalIdSourceBill": safe_get(customer_info, 'lastArrivalIdSourceBill'),
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"customerInfoType": safe_get(customer_info, 'customerInfoType'),
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"customerInfoCompleteDate": safe_get(customer_info, 'customerInfoCompleteDate'),
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"customerInfoCompleteType": safe_get(customer_info, 'customerInfoCompleteType'),
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"xczUserId": safe_get(customer_info, 'xczUserId'),
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"xczUuid": safe_get(customer_info, 'xczUuid'),
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"idWxbCustomer": safe_get(customer_info, 'idWxbCustomer'),
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"promoteEmployeeId": safe_get(customer_info, 'promoteEmployeeId'),
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"promoteEmployeeName": safe_get(customer_info, 'promoteEmployeeName'),
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"promoteMemberId": safe_get(customer_info, 'promoteMemberId'),
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"promoteMemberName": safe_get(customer_info, 'promoteMemberName'),
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"driverExpiryDate": safe_get(customer_info, 'driverExpiryDate'),
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"crmDeleteExclusiveFlag": safe_get(customer_info, 'crmDeleteExclusiveFlag'),
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"totalObtainPoints": safe_get(customer_info, 'totalObtainPoints'),
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"totalUsedPoints": safe_get(customer_info, 'totalUsedPoints'),
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"orgName": safe_get(customer_info, 'orgName'),
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"weChatFollower": safe_get(customer_info, 'weChatFollower'),
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"pointsEnableConfig": safe_get(customer_info, 'pointsEnableConfig'),
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"personalPointsEnableConfig": safe_get(customer_info, 'personalPointsEnableConfig'),
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"pointsButtonStatus": safe_get(customer_info, 'pointsButtonStatus'),
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"tmallInstallMember": safe_get(customer_info, 'tmallInstallMember'),
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"corpId": safe_get(customer_info, 'corpId'),
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"thirdCorpId": safe_get(customer_info, 'thirdCorpId'),
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}
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return request_data
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for customer in all_customers:
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phone = customer.get("cellPhone")
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if phone in df["客户手机号"].tolist():
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print("开始修改")
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cus_id = customer.get("idCustomer", {})
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cus_response = requests.get(f'https://yunxiu.f6car.cn/member/customer/{cus_id}', cookies=cookies)
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original_data = cus_response.json()
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final_json_data = convert_to_request_data(original_data, df)
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response = requests.post(
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'https://yunxiu.f6car.cn/member/customer/modifyCustomer',
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cookies=cookies,
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json=final_json_data,
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)
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print("修改完成")
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time.sleep(1)
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msg = update_jiandaoyun(data, f'修改完成')
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if msg.get('msg'):
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approve_workflow(data)
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print('表单已自动提交至下一步')
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