161 lines
7.5 KiB
Python
161 lines
7.5 KiB
Python
from datetime import date, timedelta, datetime
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import holidays
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from config import Config
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import pandas as pd
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import pymysql # 使用 pymysql 替代 mysql.connector
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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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from api import API
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common_module = CommonModule()
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api_instance = API()
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global last_day_end_customer_service, is_customer_service_data_id, customer_service_data_id
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class JCBEfficientCarPickup:
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def __init__(self):
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# 使用 pymysql 连接数据库
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self.field_mapping = {}
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self.staff_id_list = None
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self.customer_service_list = None
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def load_all_data(self):
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# 获取接车宝客服表单
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payload = {"api_key": "6717470a0b3975ef583c6df1",
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"entry_id": "67b6f2462f9ac03b783d409a",
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}
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customer_service = api_instance.entry_data_list(payload)
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self.customer_service_list = customer_service.get("data") # api请求格式，将数据封装在data字典里
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def today_customer_service_list(self):
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# 获取今日接车宝派发客服顺序
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today_customer_service_list = []
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all_customer_service_list = []
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today_customer_service_start_list = []
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for row_items in self.customer_service_list:
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# print(row_items)
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customer_service_name_id = row_items.get("_widget_1740042824214", {}).get("username", {})
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customer_service_name = row_items.get("_widget_1740042824214", {}).get("name", {})
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customer_service_state = row_items.get("_widget_1740117343937", {})
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is_last_day_end = row_items.get("_widget_1740042824216", {})
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customer_service_data_id = row_items.get("_id", {})
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print(customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end)
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all_customer_service_list.append(
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[customer_service_name, customer_service_name_id, customer_service_state, is_last_day_end,
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customer_service_data_id])
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if is_last_day_end == "是": # 判断是否是下次开始位置
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last_day_end_customer_service = customer_service_name_id
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is_customer_service_data_id = row_items.get("_id", {})
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split_index = None
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for index, row in enumerate(all_customer_service_list):
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print(row[3])
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if row[3] == "是":
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split_index = index
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print(f"找到索引 {index}")
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break
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if split_index is not None:
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# 根据索引切割列表
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first_part = all_customer_service_list[split_index:] # 索引位置及之后的行
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second_part = all_customer_service_list[:split_index] # 索引位置之前的行
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# 调换两个子列表的位置并重新组合
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today_customer_service_start_list = first_part + second_part
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else:
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# 如果没有找到“是”，保持原列表不变
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today_customer_service_start_list = all_customer_service_list
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pass
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for index, row in enumerate(today_customer_service_start_list):
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if row[2] == "开":
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today_customer_service_list.append(row[1])
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return today_customer_service_list, customer_service_data_id, all_customer_service_list
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def main(self):
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self.load_all_data()
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print(self.customer_service_list)
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today_customer_service_list, customer_service_data_id, all_customer_service_list = self.today_customer_service_list()
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print(today_customer_service_list)
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data_JCB = common_module.get_jcb_details()
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# 保存为CSV文件
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output_dir = "output" # 设置输出目录
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# 创建输出目录（如果不存在）
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import os
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os.makedirs(output_dir, exist_ok=True)
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# data_JCB.to_csv(os.path.join(output_dir, 'JCB_all_data.csv'), index=False)
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self.fields()
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# 异常待办回访 近1个月开单为0客户
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# 当前日期
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current_date = datetime.now()
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current_date = current_date + timedelta(days=-1)
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current_date_str = current_date.strftime("%Y-%m-%d")
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# current_date = datetime.now()
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thirty_days_ago = current_date - timedelta(days=30)
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thirty_days_ago = thirty_days_ago.date()
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abnormal_data = []
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# df = pd.read_csv(os.path.join(output_dir, "JCB_异常待办.csv")) # 读取异常待办表
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# print(df)
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for index, row in data_JCB.iterrows():
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new_row = row.copy()
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new_row['开户日'] = datetime.strptime(new_row['开户日'], "%Y-%m-%d").date()
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if new_row['开户日'] < thirty_days_ago and row['近30天开单天数'] == 0 and row['客户状态'] == "留存":
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# print(row['账号'], row['开户日'], row['近30天开单天数'], row["客户状态"])
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row["日期"] = datetime.strptime(row['开户日'], "%Y-%m-%d").date()
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row['日期'] = row["日期"].strftime("%Y-%m-%d")
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abnormal_data.append(row)
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# 推送给客服
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abnormal_data = pd.DataFrame(abnormal_data)
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abnormal_data["表单类型"] = "异常待办"
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abnormal_data["派发日期"] = current_date_str
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abnormal_data.to_excel(os.path.join(output_dir, 'JCB_前一日异常待办.xlsx'), index=False)
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abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in
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abnormal_data.iterrows()]
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data = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID, 'entry_id': Config.EFFICIENT_CAR_PICKUP_ENTRY_ID,
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"data_list": abnormal_data}
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# result = api_instance.entry_data_batch_create(data)
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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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# print(field_mapping)
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for col_name, widget_id in field_mapping.items():
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# print(col_name, widget_id)
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if col_name in row:
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value = row[col_name]
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clean_value = None if pd.isna(value) else value
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result[widget_id] = {"value": clean_value}
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return result
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def fields(self):
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self.field_mapping = {"日期": "_widget_1739252804406", "产品名称": "_widget_1739252804397",
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"账号": "_widget_1739258942667", "联系手机号": "_widget_1739252804407",
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"使用时长": "_widget_1739252804409", "开户日": "_widget_1739252804396",
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"到期日": "_widget_1739252804408", "续约日": "_widget_1739252804410",
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"客户状态": "_widget_1739252804400", "近一周开单量": "_widget_1739252804413",
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"近一周是否活跃": "_widget_1739252804414",
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"G状态：近30天开单大于等于10天": "_widget_1739252804415",
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"当月开单天数": "_widget_1739252804416", "近30天开单天数": "_widget_1739252804417",
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"当月G天数": "_widget_1739252804418", "日分区": "_widget_1739252804419",
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"表单类型": "_widget_1739951204545", "派发日期": "_widget_1740036367181",
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"跟进人": "_widget_1740043340255",
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}
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if __name__ == "__main__":
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start = JCBEfficientCarPickup()
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start.main()
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# if result is not None:
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# print(result.head()) # 打印前几行数据
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