from api import API from back_ground_module import CommonModule import datetime import re import pandas as pd from log_config import configure_task_logger, configure_error_task_logger api_instance = API() common_module = CommonModule() start_time = datetime.datetime.now() # 获取已经配置好的常规日志记录器 logger = configure_task_logger() # 获取已经配置好的错误任务日志记录器 error_task_logger = configure_error_task_logger() class KeyCustomerRevisit: """大客户回访""" def __init__(self): self.index = None self.data_NGV = None self.date_list = None self.Smart_detection = None self.service_remind = None self.json_list = [] self.NGV_data_list = None self.permissions_table = None self.staff_id_list = None self.get_feature_usage = None self.policy_recognition = None self.widget_list = None self.private_domain = None self.public_domain = None self.public_domain_list = None self.different_industries = None self.different_industries_list = None def load_all_data(self): """加载所有必要的数据表""" # 省市区人员关系表 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676512ac3e54dc3159460c0a"} json_dict = api_instance.entry_data_list(payload) self.json_list = json_dict.get("data") # 获取简道云员工id payload = {"api_key": "6694d3c4fcb69ca9a111a6c4", "entry_id": "6769204a1902c9341340a1bc", } staff_id = api_instance.entry_data_list(payload) self.staff_id_list = staff_id.get("data") # api请求格式，将数据封装在data字典里 # 获取权限表信息 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675b96c14e839f90fef1647c"} self.permissions_table = api_instance.entry_data_list(payload).get("data") # 获取NGV数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "675bb02bd2d53c2034c665e4"} self.NGV_data_list = api_instance.entry_data_list(payload).get("data") # print("NGV获取后的类型：", type(self.NGV_data_list)) # 获取服务提醒-数据支持表单数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb7bda3029720f1083e99"} self.service_remind = api_instance.entry_data_list(payload).get("data") # 获取智能检测-数据支持表单数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "676bb99649ab3ac975af6e39"} self.Smart_detection = api_instance.entry_data_list(payload).get("data") # 获取功能使用情况表 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6763bbf657bd8fb76fcb41b2"} self.get_feature_usage = api_instance.entry_data_list(payload).get("data", []) # 获取保单识别表 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "6773a60d30ed87ff9f68d3c5"} self.policy_recognition = api_instance.entry_data_list(payload).get("data") # 提取 _widget_1735632397600 的值并存储在列表中 self.widget_list = [item['_widget_1735632397600'] for item in self.policy_recognition] # 获取私域小程序-数据支持表单数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0f0fae622896749ba5087"} self.private_domain = api_instance.entry_data_list(payload).get("data", []) # 提取 _widget_1742795002375 的值并存储在列表中 self.private_domain = [item['_widget_1742795002375'] for item in self.private_domain] # 获取公域小程序-数据支持表单数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e0c702c8f603b997980999"} self.public_domain = api_instance.entry_data_list(payload).get("data", []) # 提取 _widget_1742784257506 的值并存储在列表中 self.public_domain_list = [item['_widget_1742784257506'] for item in self.private_domain] # 获取异业合作-数据支持表单数据 payload = {"api_key": "675b900991ad2491c69389ca", "entry_id": "67e24fdd8dfcfa918e17c30b"} self.different_industries = api_instance.entry_data_list(payload).get("data", []) # 提取 _widget_1742784257506 的值并存储在列表中 self.different_industries_list = [item['_widget_1742784257506'] for item in self.different_industries] @staticmethod def remove_parentheses(text: str) -> str: # 使用正则表达式匹配并去除括号及其内容 # \s* 表示匹配零个或多个空白字符（处理括号前后可能存在的空格） # $ 和 $ 分别表示匹配左括号和右括号 # 中间的 .*? 表示非贪婪地匹配任意数量的字符（包括没有字符的情况） cleaned_text = re.sub(r'\s*$.*?$\s*', '', text) # 为了确保同时处理中文括号，再进行一次替换 cleaned_text = re.sub(r'\s*（.*?）\s*', '', cleaned_text) return cleaned_text.strip() # 去除两端多余的空白字符 @staticmethod def get_staff_id(row_item, name): """辅助函数，用于获取员工ID""" if str(row_item["_widget_1734942794144"]) == str(name): # 检查姓名是否匹配 return row_item["_widget_1734942794145"] # 返回员工ID return None def main(self): task_start_time =datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") self.load_all_data() self.date_list = common_module.get_holiday_list() # 获取一年中的节假日 self.data_NGV = common_module.get_ngv_details(days_back=1) # 获取data_NGV 并转为str # self.index = self.build_index(self.json_list) data_NGV = self.data_NGV.copy() def replace_values(series): # 使用条件判断来进行替换 return series.apply(lambda x: '' if pd.isna(x) or x in ['NA', 'None', ''] else x) # 对整个DataFrame的所有列应用替换函数 data_NGV = data_NGV.apply(replace_values) # data_NGV.to_csv("dayinNGV.csv") # 定义优先级顺序 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'] customer_type_order = ["F", "E", "D", "C", "B", "A"] # 索引越小优先级越高 group_grade_order = ['全国KA（FMVP）', '区域KA（MVP）', '重要客户（SVIP）', '普通客户（VIP）'] # 创建映射字典，并为不在列表中的值设置默认值 edition_map = {edition: idx for idx, edition in enumerate(edition_order)} customer_type_map = {ctype: idx for idx, ctype in enumerate(customer_type_order)} group_grade_map = {grade: idx for idx, grade in enumerate(group_grade_order)} # 添加用于排序的新列，并处理不在映射字典中的值 data_NGV['edition_rank'] = data_NGV['saas_edition_fmt'].map(edition_map).fillna(0).astype(int) # 缺失值用最高优先级填充 data_NGV['customer_type_rank'] = data_NGV['saas_customer_type'].map(customer_type_map).fillna(0).astype(int) data_NGV['group_grade_rank'] = data_NGV['group_grade'].map(group_grade_map).fillna(0).astype(int) # data_NGV.to_csv("88855.csv") # 找到每组中 edition_rank 最小值对应的行 best_edition_idx = data_NGV.groupby('id_own_group')['edition_rank'].idxmin() best_edition_rows = data_NGV.loc[best_edition_idx] best_edition_rows['max_saas_edition'] = best_edition_rows['saas_edition_fmt'] # 找到每组中 customer_type_rank 最小值对应的行 best_customer_type_idx = data_NGV.groupby('id_own_group')['customer_type_rank'].idxmin() best_customer_type_rows = data_NGV.loc[best_customer_type_idx] best_customer_type_rows['max_saas_customer_type'] = best_customer_type_rows['customer_type_rank'].apply( lambda x: customer_type_order[x]) # 找到每组中 group_grade_rank 最小值对应的行 best_group_grade_idx = data_NGV.groupby('id_own_group')['group_grade_rank'].idxmin() best_group_grade_rows = data_NGV.loc[best_group_grade_idx] best_group_grade_rows['max_group_grade'] = best_group_grade_rows['group_grade'] # 合并最佳值回到原数据集 best_values = ( best_edition_rows[['id_own_group', 'max_saas_edition']] .merge(best_customer_type_rows[['id_own_group', 'max_saas_customer_type']], on='id_own_group', how='outer') .merge(best_group_grade_rows[['id_own_group', 'max_group_grade']], on='id_own_group', how='outer') ) # 将最佳值合并回原数据集 data_NGV = data_NGV.merge(best_values, on='id_own_group', how='left') condition = (data_NGV['is_main_org'] == 1) & (data_NGV['org_status'] == '过期') # 步骤2: 过滤条件 ngvv2 = data_NGV[condition] # ngvv2.to_excel(r"C:\Users\Administrator.DESKTOP-7IC2USJ\Desktop\NGVV2.xlsx") data_NGV_V2 = data_NGV.copy() # 步骤3: 检查id_own_group是否存在于ngvv2中 data_NGV_V2['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & ( data_NGV['group_grade'].isin(['全国KA（FMVP）', '区域KA（MVP）'])) & (data_NGV['is_main_org'] != 1) data_NGV_V2 = data_NGV_V2.loc[data_NGV_V2["条件"]] # 步骤4: 过滤存在的记录 data_NGV_V2['exists_in_ngvv2'] = data_NGV_V2['id_own_group'].isin(ngvv2['id_own_group']) filtered_data = data_NGV_V2[data_NGV_V2['exists_in_ngvv2']] 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'] # sorted_items = sorted(filtered_data, key=lambda x: fixed_order.index(x)) fixed_order_map = {edition: index for index, edition in enumerate(fixed_order)} filtered_data['sort_key'] = filtered_data['saas_edition_fmt'].map(fixed_order_map) filtered_data = filtered_data.sort_values(by='sort_key').drop('sort_key', axis=1) result = filtered_data.drop_duplicates(subset='id_own_group', keep='first') data_NGV['条件'] = (data_NGV['org_type'] == "一般") & (data_NGV['org_status'] == '留存') & ( data_NGV['group_grade'].isin(['全国KA（FMVP）', '区域KA（MVP）'])) & (data_NGV['is_main_org'] == 1) data_NGV = data_NGV.loc[data_NGV["条件"]] data_NGV = pd.concat([data_NGV, result], axis=0) # 重置索引 data_NGV = data_NGV.reset_index(drop=True) print(f'读取NGV大客户回访 {len(data_NGV)} 条数据！') # data_NGV.to_csv("大客户回访数据.csv") data_NGV = data_NGV.copy() for index_num, row in data_NGV.iterrows(): # 对过滤后的每一条进行派发 print(row["org_code"]) # 数据验证 print(row["service_impl_principal"]) print(row["area_manager"]) print(row["technician"]) print(row["group_grade"]) payload_dict = {} # saas_use_year = re.findall(r'第([0-9]+)年', row["saas_use_year"])[0] NGV_roles = { 'relationship_manager': row['service_impl_principal'], # 运营负责人 # 'relationship_manager': "张阳", # 运营负责人 'area_manager': row['area_manager'], # 区域经理 'technician': row['technician'], # 技术专家 'salesmen': row['salesmen'], # 技术专家 } for role, name in NGV_roles.items(): for row_item in self.staff_id_list: staff_id = self.get_staff_id(row_item, name) if staff_id: NGV_roles[role] = staff_id break # 找到后退出循环 else: NGV_roles[role] = None # 如果没有找到对应的员工ID relationship_manager, area_manager, technician, salesmen = [NGV_roles[role] for role in ['relationship_manager', 'area_manager', 'technician', 'salesmen']] payload_dict.update({ "_widget_1734590278288": {"value": technician} # 跟进人是技术专家 }) payload_dict.update({ "_widget_1734590278289": {"value": relationship_manager}, # 运营负责人 "_widget_1734590278290": {"value": area_manager}, # 区域经理 "_widget_1734590278291": {"value": technician}, # 技术专家 "_widget_1735290738545": {"value": salesmen}} # 销售负责人 ) # 输出结果 print("SaaS开户回访人员：", relationship_manager or "未分配") print("SaaS技术专家：", technician or "未分配") print("SaaS区域经理：", area_manager or "未分配") # 判断权限唯一值 pattern = r'(.+)\（' match = re.search(pattern, row['max_group_grade']) group_grade = match.group(1) if not row['saas_customer_type'] or row['saas_customer_type'] == 'NA' or row[ 'saas_customer_type'] == 'None': row['saas_customer_type'] = "F" NGV_store_level_key = group_grade + row['max_saas_edition'] + row['max_saas_customer_type'] print("权限唯一值：", NGV_store_level_key) data_NGV.at[index_num, 'NGV_store_level_key'] = NGV_store_level_key Billing = None for item in self.permissions_table: if NGV_store_level_key == item.get("_widget_1734056507963"): # 合并（等级-类型-分层） print("该门店开单的权限是：", item.get("_widget_1734055617039")) Billing = item.get("_widget_1734055617039") # 开单 Service_Alerts = item.get("_widget_1734055617040") # 服务提醒 membership = item.get("_widget_1734055617041") # 会员卡 SMS = item.get("_widget_1734055617042") # 短信 Public_domain_applets = item.get("_widget_1734055617043") # 公域小程序 Private_domain_applets = item.get("_widget_1734055617044") # 私域小程序 Test_sheet = item.get("_widget_1734055617045") # 检测单 AI_poster = item.get("_widget_1734055617046") # AI海报 Business_wallets = item.get("_widget_1734055617047") # 企业钱包 Precision_marketing = item.get("_widget_1734055617049") # 精准营销 Paid_memberships = item.get("_widget_1734055617051") # 付费会员 business_WeCom = item.get("_widget_1734055617052") # 企业微信 Insurance_policy_identification = item.get("_widget_1734055617053") # 保险单识别 Insurance_bots = item.get("_widget_1734055617054") # 保险机器人 Camera_pick_up = item.get("_widget_1734055617055") # 摄像头接车 Camera_billing = item.get("_widget_1734055617056") # 摄像头开单 Transparent_workshop = item.get("_widget_1734055617057") # 透明车间 Cross_industry_cooperation = item.get("_widget_1734055617058") # 异业合作 BI_Insights = item.get("_widget_1734055617059") # BI洞察 payload_dict.update( { "_widget_1734073342350": {"value": Billing}, "_widget_1735004315757": {"value": Service_Alerts}, "_widget_1735004315756": {"value": membership}, "_widget_1735004315755": {"value": SMS}, "_widget_1735004315754": {"value": Public_domain_applets}, "_widget_1735004315753": {"value": Private_domain_applets}, "_widget_1735004315752": {"value": Test_sheet}, "_widget_1735004315751": {"value": AI_poster}, "_widget_1735004315750": {"value": Business_wallets}, "_widget_1735004315749": {"value": Precision_marketing}, "_widget_1735004315748": {"value": Paid_memberships}, "_widget_1735004315747": {"value": business_WeCom}, "_widget_1735004315746": {"value": Insurance_policy_identification}, "_widget_1735004315745": {"value": Insurance_bots}, "_widget_1735004315744": {"value": Camera_pick_up}, "_widget_1735004315743": {"value": Camera_billing}, "_widget_1735004315742": {"value": Transparent_workshop}, "_widget_1735004315741": {"value": Cross_industry_cooperation}, "_widget_1734073342352": {"value": BI_Insights}, } ) feature_dict = { "开单": "_widget_1734073342350", "服务提醒": "_widget_1735004315757", "会员卡": "_widget_1735004315756", "短信": "_widget_1735004315755", "公域小程序": "_widget_1735004315754", "私域小程序": "_widget_1735004315753", "检测单": "_widget_1735004315752", "AI海报": "_widget_1735004315751", "企业钱包": "_widget_1735004315750", "精准营销": "_widget_1735004315749", "付费会员": "_widget_1735004315748", "企业微信": "_widget_1735004315747", "保险单识别": "_widget_1735004315746", "保险机器人": "_widget_1735004315745", "摄像头接车": "_widget_1735004315744", "摄像头开单": "_widget_1735004315743", "透明车间": "_widget_1735004315742", "异业合作": "_widget_1735004315741", "BI洞察": "_widget_1734073342352", } # _widget_1735527329557 下次是否推荐 for new_item in self.get_feature_usage: for feature_module, feature_value in feature_dict.items(): # 模块 if new_item.get("_widget_1735268263079") == feature_module and new_item.get( "_widget_1735527329557") == "否" and new_item.get("_widget_1735280720550") == \ row["id_own_org"]: # 下次是否推荐 功能使用情况表 print(f"{feature_value}进行了更改") payload_dict.update({f"{feature_value}": {"value": "×"}}) if new_item.get("_widget_1735268263079") == feature_module and new_item.get( "_widget_1736414617462") == "否" and new_item.get("_widget_1735280720550") == \ row["id_own_org"]: # 下次是否跟进 print(f"{feature_value}进行了更改") payload_dict.update({f"{feature_value}": {"value": "×"}}) fields_to_check = { "_widget_1735004315763": Billing, # 开单 "_widget_1735106258016": Service_Alerts, # 服务提醒 "_widget_1735106258036": membership, # 会员卡 "_widget_1735106258086": SMS, # 短信 "_widget_1735106258112": Public_domain_applets, # 公域小程序 "_widget_1735106258141": Private_domain_applets, # 私域小程序 "_widget_1735107354648": Test_sheet, # 检测单 "_widget_1735107354725": AI_poster, # AI海报 "_widget_1735107354811": Business_wallets, # 企业钱包 "_widget_1735107354906": Precision_marketing, # 精准营销 "_widget_1735107354980": Paid_memberships, # 付费会员 "_widget_1735107355093": business_WeCom, # 企业微信 "_widget_1735107355143": Insurance_policy_identification, # 保险单识别 "_widget_1735107355235": Insurance_bots, # 保险机器人 "_widget_1735107355333": Camera_pick_up, # 摄像头接车 "_widget_1735107355392": Camera_billing, # 摄像头开单 "_widget_1735107355502": Transparent_workshop, # 透明车间 "_widget_1735107355618": Cross_industry_cooperation, # 异业合作 "_widget_1735107355740": BI_Insights # BI洞察 } # 遍历每个字段，检查其值并更新payload_dict for widget_id, field_name in fields_to_check.items(): if field_name == "√": payload_dict.update({widget_id: {"value": "是"}}) break if row["active_status_fmt"] == "活跃": # 开单 是否使用 payload_dict.update({"_widget_1735004315765": {"value": "是"}}) else: payload_dict.update({"_widget_1735004315765": {"value": "否"}}) try: if row["card_bill_day_count_last_30_day"] != "0": # 会员卡 是否使用 payload_dict.update({"_widget_1735106258038": {"value": "是"}}) else: payload_dict.update({"_widget_1735106258038": {"value": "否"}}) except Exception as e: print(f"会员卡识别：Error finding customer service: {e}") # print(self.service_remind.get("_widget_1735112637045")) payload_dict["_widget_1735106258018"] = {"value": "否"} for item in self.service_remind: if row["id_own_group"] == item.get("_widget_1735112637043"): if int(item.get("_widget_1735112637045")) < 180 and int( item.get("_widget_1735112637046")) == 1: # 服务提醒 是否使用 payload_dict.update({"_widget_1735106258018": {"value": "是"}}) break elif int(item.get("_widget_1735112637048")) > 0: payload_dict.update({"_widget_1735106258018": {"value": "是"}}) break keys_to_check = [ "_widget_1735113110155" ] # 智能检测 是否使用 # 初始化默认值为"否" payload_dict["_widget_1735107354650"] = {"value": "否"} # 检查每个键，如果有一个大于0，则更新为"是"并停止检查 for key in keys_to_check: for item in self.Smart_detection: if row["id_own_org"] == item.get("_widget_1735113110147"): 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 payload_dict["_widget_1735107354650"]["value"] = "是" break # 近30天业务单量=0 则其它所有模块均不推荐 try: for feature_module, feature_value in feature_dict.items(): # 模块 if row["bill_count_last_30_day"] == '0' and payload_dict[feature_value]["value"] == '△': payload_dict.update({f"{feature_value}": {"value": "×"}}) except Exception as e: print(f"不开单识别：Error finding customer service: {e}") # 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 try: if row["org_code"] in self.widget_list: payload_dict.update({'_widget_1735004315746': {"value": "△"}}) except Exception as e: print(f"保单识别：Error finding customer service: {e}") # 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 try: if row["id_own_group"] in self.private_domain: payload_dict.update({'_widget_1735106258143': {"value": "是"}}) # SYXCX:是否使用 else: payload_dict.update({'_widget_1735106258143': {"value": "否"}}) # SYXCX:是否使用 except Exception as e: print(f"私域小程序：Error finding customer service: {e}") try: high_version = ['皇冠版', '至尊版', '尊享版', '旗舰版'] if row["saas_edition_fmt"] in high_version: payload_dict.update({'_widget_1735106258141': {"value": "是"}}) # SYXCX:是否拥有 else: payload_dict.update({'_widget_1735106258141': {"value": "否"}}) # SYXCX:是否拥有 except Exception as e: print(f"私域小程序：Error finding customer service: {e}") # 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 try: for item in self.public_domain: if row["id_own_org"] == item.get("_widget_1742784257506"): # 门店id if int(item.get("_widget_1742784257509")) > 0 : # 发布商品数量 payload_dict.update({"_widget_1735106258114": {"value": "是"}}) # GYXCX:是否使用 break else : payload_dict.update({"_widget_1735106258114": {"value": "否"}}) # GYXCX:是否使用 break except Exception as e: print(f"公域小程序：Error finding customer service: {e}") try: if row["id_own_org"] in self.public_domain_list: payload_dict.update({'_widget_1735106258112': {"value": "是"}}) # GYXCX:是否拥有 else: payload_dict.update({'_widget_1735106258112': {"value": "否"}}) # GYXCX:是否拥有 except Exception as e: print(f"公域小程序：Error finding customer service: {e}") # 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 try: if row["id_own_org"] in self.different_industries_list: payload_dict.update({'_widget_1735107355618': {"value": "是"}}) # YYHZ:是否拥有 else: payload_dict.update({'_widget_1735107355618': {"value": "否"}}) # YYHZ:是否拥有 except Exception as e: print(f"异业合作：Error finding customer service: {e}") NGV_data_id = None # 获取关联数据 for NGV_Data in self.NGV_data_list: # NGV_Data = NGV_Data.get("data") if row["org_code"] == NGV_Data.get("_widget_1734062123071"): # 门店编码 NGV_data_id = NGV_Data.get("_id") print(NGV_data_id) if not NGV_data_id: print("未找到数据ID") distribution_date = datetime.datetime.now(datetime.timezone.utc) distribution_date = distribution_date.strftime('%Y-%m-%dT%H:%M:%S.%f')[:-3] + 'Z' payload_dict.update({ "_widget_1734590278279": {"value": row["group_name"]}, # 公司名称 "_widget_1735112931760": {"value": row["id_own_group"]}, # 公司id "_widget_1735112931761": {"value": row["id_own_org"]}, # 门店id "_widget_1734590278281": {"value": row['org_name']}, # 门店名称 "_widget_1734590278292": {"value": "2025第一季度大客户回访"}, # 跟进阶段 "_widget_1734321349021": {"value": NGV_data_id}, # 关data_get联数据 "_widget_1742548684369": {"value": "定期维护，了解业务变化，保持客户满意度的同时挖掘增购机会。"}, # 主要目的 "_widget_1734590278266": {"value": row['region_name']}, # 大区 "_widget_1734590278285": {"value": row['branch_name']}, # 小区 "_widget_1734590278284": {"value": row['province_name']}, # 省 "_widget_1734590278283": {"value": row['city_name']}, # 市 "_widget_1734590278282": {"value": row['area_name']}, # 区 "_widget_1734590278278": {"value": row['saas_customer_type']}, # 门店分层 "_widget_1734590278277": {"value": row['group_grade']}, # 公司等级 "_widget_1734590278276": {"value": row['limit_user_type']}, # 限制账户类型 "_widget_1734590278275": {"value": row['active_user_type']}, # 有效账户类型 "_widget_1734590278274": {"value": row['saas_version']}, # ERP操作模式 "_widget_1734590278273": {"value": row['saas_use_year']}, # 使用时长 "_widget_1734590278272": {"value": row['org_stage']}, # 门店阶段 "_widget_1734590278271": {"value": row['manage_model']}, # 经营模式 "_widget_1734590278267": {"value": row['contacts']}, # 联系人 "_widget_1734590278287": {"value": row['contact_mobile']}, # 联系手机号 "_widget_1734590278286": {"value": row['saas_edition_fmt']}, # SaaS版本 "_widget_1734590278280": {"value": row['org_code']}, # 门店编码 "_widget_1735287791875": {"value": row['salesmen']}, # 销售负责人 "_widget_1735096489244": {"value": distribution_date}, # 派发时间 }) routine_follow_up_payload = { "api_key": "675b900991ad2491c69389ca", "entry_id": "675b9c63925cd404038a6b86", "is_start_workflow": "true", "data": payload_dict, } print(routine_follow_up_payload) res = api_instance.data_batch_create(routine_follow_up_payload) logger.info(f"创建结果：{res}") print(res) # data_NGV.to_csv("final_data_NGV.csv", index=False) common_module.send_task_status(task_start_time, "大客户回访") if __name__ == '__main__': start = KeyCustomerRevisit() start.main()