接车宝派发更新
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@@ -4,6 +4,9 @@ import pandas as pd
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from back_ground_module import CommonModule
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from api import API
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from log_config import configure_task_logger, configure_error_task_logger
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from datetime import datetime, timedelta, timezone
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import pandas as pd
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import os
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# 获取已经配置好的常规日志记录器
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logger = configure_task_logger()
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@@ -24,6 +27,7 @@ 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.daily_revisit_list = None
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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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@@ -108,7 +112,8 @@ class JCBEfficientCarPickup:
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new_sign_abnormal_data = [self.row_to_dict(row, self.field_mapping) for index, row in
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df.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 = {'api_key': Config.EFFICIENT_CAR_PICKUP_APP_ID,
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'entry_id': Config.EFFICIENT_CAR_PICKUP_ENTRY_ID,
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"data_list": new_sign_abnormal_data}
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result = api_instance.entry_data_batch_create(data)
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@@ -137,6 +142,14 @@ class JCBEfficientCarPickup:
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result2 = api_instance.entry_data_update(data2)
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logger.info(f"明日派发人员信息已修改:{result2}")
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def load_all_data(self):
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# 获取接车宝日常回访单
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payload = {"api_key": "6717470a0b3975ef583c6df1",
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"entry_id": "67174710da507490d8ac12c1",
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}
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daily_revisit = api_instance.entry_data_list(payload)
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self.daily_revisit_list = daily_revisit.get("data") # api请求格式，将数据封装在data字典里
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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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@@ -145,6 +158,7 @@ class JCBEfficientCarPickup:
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if data_JCB is None:
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logger.error("获取接车宝数据失败，返回None")
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raise ValueError("获取接车宝数据失败，返回None")
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self.load_all_data()
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logger.info(f"数据加载完成")
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@@ -181,6 +195,97 @@ class JCBEfficientCarPickup:
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else:
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logger.info(f"新签异常待办回访无数据，跳过")
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# 异常待办
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current_local = datetime.now() + timedelta(days=-1) # tz-naive，代表本地时间
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current_date_str = current_local.strftime("%Y-%m-%d")
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# 计算30天前的本地日期（用于开户日判断）
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thirty_days_ago_local = (current_local - timedelta(days=30)).date()
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abnormal_data = []
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for index, row in data_JCB.iterrows():
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try:
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# 开户日是本地日期字符串，解析为 date 对象
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open_date = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
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except (ValueError, TypeError):
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continue # 跳过无效日期
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if (
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open_date < thirty_days_ago_local
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and row['近30天开单天数'] == 0
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and row['客户状态'] == "留存"
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):
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new_row = row.copy()
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new_row["日期"] = open_date.strftime("%Y-%m-%d")
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abnormal_data.append(new_row)
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abnormal_data = pd.DataFrame(abnormal_data) if abnormal_data else pd.DataFrame()
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if not abnormal_data.empty:
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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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# 清洗手机号（仅去除浮点型 .0）
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def clean_phone(x):
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if pd.isna(x) or x == "" or x == "None":
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return ""
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s = str(x)
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if s.endswith('.0') and s[:-2].isdigit():
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return s[:-2]
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return s
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abnormal_data['联系手机号'] = abnormal_data['联系手机号'].apply(clean_phone)
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# 构建云端已派发记录 DataFrame
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df_cloud = pd.DataFrame([
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{
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"数据id": item.get("_id", ""),
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"账号": item.get("_widget_1739258942667", ""),
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"提交时间": item.get("createTime", ""),
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"表单类型": item.get("_widget_1739951204545", "")
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}
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for item in self.daily_revisit_list
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])
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recent_accounts = set()
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if not df_cloud.empty and not abnormal_data.empty:
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# 将 createTime 转为 UTC 时间（强制统一时区）
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df_cloud["提交时间"] = pd.to_datetime(df_cloud["提交时间"], utc=True, errors="coerce")
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df_cloud = df_cloud.dropna(subset=["提交时间"])
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# 筛选“异常待办”
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df_abnormal_cloud = df_cloud[df_cloud["表单类型"] == "异常待办"]
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if not df_abnormal_cloud.empty:
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# 每个账号保留最新一条
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df_recent = df_abnormal_cloud.sort_values("提交时间").groupby("账号", as_index=False).tail(1)
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current_utc = datetime.now(timezone.utc)
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cutoff_utc = pd.Timestamp(current_utc) - pd.Timedelta(days=30)
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# 安全比较：两边都是 UTC
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recent_accounts = set(df_recent[df_recent["提交时间"] > cutoff_utc]["账号"])
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# 剔除已派发账号 + 过滤有效手机号
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if not abnormal_data.empty:
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abnormal_data = abnormal_data[
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(~abnormal_data["账号"].isin(recent_accounts)) &
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(abnormal_data["联系手机号"].notna()) &
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(abnormal_data["联系手机号"] != "") &
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(abnormal_data["联系手机号"] != "None")
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]
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# # 保存结果
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output_path = os.path.join(output_dir, "异常待办1.csv")
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abnormal_data.to_csv(output_path, index=False)
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# 发送或跳过
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if not abnormal_data.empty:
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abnormal_data = abnormal_data[:20]
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self.send_request(abnormal_data)
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logger.info(f"异常待办完成，共 {len(abnormal_data)} 条")
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else:
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logger.info("异常待办无数据，跳过")
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# 优质客户转商机
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# current_date = datetime.now()
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thirty_days_ago = current_date - timedelta(days=30)
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@@ -274,7 +274,7 @@ class CommonModule:
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else: # 如果没有数据，返回空 DataFrame
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data_NGV = pd.DataFrame()
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headers = [
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"门店编码", "类型", "占位", "价格"
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"门店编码", "类型", "订单商品名称", "价格"
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]
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data_NGV.columns = headers
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