from datetime import timedelta, datetime from config import Config import pandas as pd from back_ground_module import CommonModule from api import API from log_config import configure_task_logger, configure_error_task_logger # 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() # 保存为CSV文件 output_dir = "output" # 设置输出目录 # 创建输出目录（如果不存在） import os os.makedirs(output_dir, exist_ok=True) common_module = CommonModule() api_instance = API() class JCBEfficientCarPickup: """接车宝日常回访""" def __init__(self): # 使用 pymysql 连接数据库 self.field_mapping = {} self.staff_id_list = None self.customer_service_list = None def load_cus_data(self): # 获取接车宝客服表单 payload = {"api_key": "6717470a0b3975ef583c6df1", "entry_id": "67b6f2462f9ac03b783d409a", } customer_service = api_instance.entry_data_list(payload) customer_service_list = customer_service.get("data") # api请求格式，将数据封装在data字典里 return customer_service_list def today_customer_service_list(self): # 获取今日接车宝派发客服顺序 global is_customer_service_data_id today_customer_service_list = [] all_customer_service_list = [] today_customer_service_start_list = [] for row_items in self.load_cus_data(): # print(row_items) customer_service_name_id = row_items.get("_widget_1740042824214", {}).get("username", {}) customer_service_name = row_items.get("_widget_1740042824214", {}).get("name", {}) customer_service_state = row_items.get("_widget_1740117343937", {}) is_last_day_end = row_items.get("_widget_1740042824216", {}) customer_service_data_id = row_items.get("_id", {}) print(customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end) all_customer_service_list.append( [customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end, customer_service_data_id]) if is_last_day_end == "是": # 判断是否是下次开始位置 last_day_end_customer_service = customer_service_name_id is_customer_service_data_id = row_items.get("_id", {}) split_index = None for index, row in enumerate(all_customer_service_list): print(row[3]) if row[3] == "是": split_index = index print(f"找到索引 {index}") break if split_index is not None: # 根据索引切割列表 first_part = all_customer_service_list[split_index:] # 索引位置及之后的行 second_part = all_customer_service_list[:split_index] # 索引位置之前的行 # 调换两个子列表的位置并重新组合 today_customer_service_start_list = first_part + second_part else: # 如果没有找到"是"，保持原列表不变 today_customer_service_start_list = all_customer_service_list pass for index, row in enumerate(today_customer_service_start_list): if row[2] == "开": today_customer_service_list.append(row[1]) return today_customer_service_list, is_customer_service_data_id, all_customer_service_list def send_request(self, df): if df is None or df.empty: # 检查DataFrame是否为None或空 logger.info("当前派发数据为空或None，跳过此派发") return today_customer_service_list, is_customer_service_data_id, all_customer_service_list = self.today_customer_service_list() # 初始化派发索引 next_dispatcher_index = 0 # 显式循环分配跟进人 follow_up_persons = [] for _ in range(len(df)): follow_up_person = today_customer_service_list[next_dispatcher_index] follow_up_persons.append(follow_up_person) next_dispatcher_index = (next_dispatcher_index + 1) % len(today_customer_service_list) # 添加跟进人到 DataFrame df["跟进人"] = follow_up_persons # 获取下一个派发人 next_dispatcher = today_customer_service_list[next_dispatcher_index] new_sign_abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in df.iterrows()] data = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID, 'entry_id': Config.EFFICIENT_CAR_PICKUP_ENTRY_ID, "data_list": new_sign_abnormal_data} result = api_instance.entry_data_batch_create(data) logger.info(f"数据发送成功:{result}") data1 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID, "entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID, "data_id": is_customer_service_data_id, "data": {"_widget_1740042824216": {"value": ""}, } } # 原来的是"_widget_1740042824216": {"value": "是"},修改昨日截至人员 next_customer_service_data_id = None for index, row in enumerate(all_customer_service_list): print(row[3]) if row[1] == next_dispatcher: next_customer_service_data_id = row[4] break data2 = {"api_key": Config.EFFICIENT_CAR_PICKUP_APP_ID, "entry_id": Config.EFFICIENT_CAR_PICKUP_CUSTOMER_SERVICE_ID, "data_id": next_customer_service_data_id, "data": {"_widget_1740042824216": {"value": "是"}, }} api_instance.entry_data_update(data1) result2 = api_instance.entry_data_update(data2) logger.info(f"明日派发人员信息已修改:{result2}") def main(self): task_start_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") try: logger.info(f"接车宝日常回访开始执行") data_JCB = common_module.get_jcb_details() if data_JCB is None: logger.error("获取接车宝数据失败，返回None") raise ValueError("获取接车宝数据失败，返回None") logger.info(f"数据加载完成") # data_JCB.to_csv(os.path.join(output_dir, 'JCB_all_data.csv'), index=False) self.fields() # 新签异常待办回访。 # 当前日期 current_date = datetime.now() current_date = current_date + timedelta(days=0) current_date_str = current_date.strftime("%Y-%m-%d") seven_days_ago = current_date - timedelta(days=7) seven_days_ago = seven_days_ago.date() # print(three_days_ago) new_sign_abnormal = [] for index, row in data_JCB.iterrows(): new_row = row.copy() # 先转成字符串，再解析回 date 对象 new_row['开户日'] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date() if new_row['开户日'] == seven_days_ago and row['当月开单天数'] == 0: # print(row['账号'], row['开户日'], row['当月开单天数']) row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date() row['日期'] = row["日期"].strftime("%Y-%m-%d") new_sign_abnormal.append(row) new_sign_abnormal = pd.DataFrame(new_sign_abnormal) if new_sign_abnormal else None if new_sign_abnormal is not None and not new_sign_abnormal.empty: new_sign_abnormal["表单类型"] = "新签异常待办" new_sign_abnormal["派发日期"] = current_date_str self.send_request(new_sign_abnormal) # 发送请求 logger.info(f"新签异常待办回访完成") else: logger.info(f"新签异常待办回访无数据，跳过") # 优质客户转商机 # current_date = datetime.now() thirty_days_ago = current_date - timedelta(days=30) sixty_days_ago = current_date - timedelta(days=60) thirty_days_ago = thirty_days_ago.date() sixty_days_ago = sixty_days_ago.date() customer_to_opportunity = [] for index, row in data_JCB.iterrows(): new_row = row.copy() # 先转成字符串，再解析回 date 对象 new_row['到期日'] = datetime.strptime(str(row['到期日']), "%Y-%m-%d").date() if new_row['到期日'] == thirty_days_ago and row['近一周开单量'] >= 3 and row[ 'G状态：近30天开单大于等于10天'] == 1: print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数']) row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date() row['日期'] = row["日期"].strftime("%Y-%m-%d") customer_to_opportunity.append(row) # 推送给客服 pass if new_row['到期日'] == sixty_days_ago and row['近一周开单量'] >= 3 and row[ 'G状态：近30天开单大于等于10天'] == 1: print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数']) row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date() row['日期'] = row["日期"].strftime("%Y-%m-%d") customer_to_opportunity.append(row) # 推送给客服 pass customer_to_opportunity = pd.DataFrame(customer_to_opportunity) if customer_to_opportunity else None if customer_to_opportunity is not None and not customer_to_opportunity.empty: customer_to_opportunity["表单类型"] = "续约优质客户转商机" customer_to_opportunity["派发日期"] = current_date_str self.send_request(customer_to_opportunity) logger.info(f"优质客户转商机完成") else: logger.info(f"优质客户转商机无数据，跳过") # 过期7天客服回访 # current_date = datetime.now() seven_days_ago = current_date - timedelta(days=7) seven_days_ago = seven_days_ago.date() outdated_30 = [] for index, row in data_JCB.iterrows(): new_row = row.copy() new_row['到期日'] = datetime.strptime(str(row['到期日']), "%Y-%m-%d").date() # seven_days_ago = seven_days_ago.date() # print(row['到期日'], seven_days_ago) if new_row['到期日'] == seven_days_ago and row['客户状态'] == "过期": print(row['账号'], row['到期日'], row['当月开单天数'], row['当月G天数']) row["日期"] = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date() row['日期'] = row["日期"].strftime("%Y-%m-%d") outdated_30.append(row) # 推送给客服 pass outdated_30 = pd.DataFrame(outdated_30) if outdated_30 else None if outdated_30 is not None and not outdated_30.empty: outdated_30["表单类型"] = "过期7天回访" outdated_30["派发日期"] = current_date_str self.send_request(outdated_30) logger.info(f"过期7天客服回访完成") else: logger.info(f"过期7天客服回访无数据，跳过") common_module.send_task_status(task_start_time, "接车宝日常派发") logger.info(f"接车宝日常派发执行完成") except Exception as e: common_module.send_task_error(task_start_time, "接车宝日常派发", str(e)) error_task_logger.error(f"接车宝日常派发执行出错：{e}") @staticmethod def row_to_dict(row, field_mapping): """将一行数据转换为指定格式的字典""" result = {} # print(field_mapping) for col_name, widget_id in field_mapping.items(): # print(col_name, widget_id) if col_name in row: value = row[col_name] clean_value = None if pd.isna(value) else value result[widget_id] = {"value": clean_value} return result def fields(self): self.field_mapping = {"日期": "_widget_1739252804406", "产品名称": "_widget_1739252804397", "账号": "_widget_1739258942667", "联系手机号": "_widget_1739252804407", "使用时长": "_widget_1739252804409", "开户日": "_widget_1739252804396", "到期日": "_widget_1739252804408", "续约日": "_widget_1739252804410", "客户状态": "_widget_1739252804400", "近一周开单量": "_widget_1739252804413", "近一周是否活跃": "_widget_1739252804414", "G状态：近30天开单大于等于10天": "_widget_1739252804415", "当月开单天数": "_widget_1739252804416", "近30天开单天数": "_widget_1739252804417", "当月G天数": "_widget_1739252804418", "日分区": "_widget_1739252804419", "表单类型": "_widget_1739951204545", "派发日期": "_widget_1740036367181", "跟进人": "_widget_1740043340255", } if __name__ == "__main__": start = JCBEfficientCarPickup() start.main()