修复因无新增客户导致NGV数据新增异常

back_ground_module/data_monitor.py

@@ -10,6 +10,8 @@ from decimal import Decimal
 import time
 import numpy as np
 import json
+import os
+os.chdir(Path(__file__).parent)
 
 
 def replace_decimals(obj):

back_ground_module/update_NGV_data.py

@@ -54,8 +54,8 @@ class UpdateNGVData:
             timestamp = time.time()
 
 
-            # data_NGV_j.to_csv(os.path.join(output_dir, f"{timestamp}up_NGV_j.csv"))
+            data_NGV_j.to_csv(os.path.join(output_dir, f"up_NGV_j.csv"))
-            # data_NGV_j1.to_csv(os.path.join(output_dir, f"{timestamp}up_NGV_j1.csv"))
+            data_NGV_j1.to_csv(os.path.join(output_dir, f"up_NGV_j1.csv"))
 
             # 找出在 data_NGV_j 中存在但在 data_NGV_j1 中不存在的 data_id
             unique_data_ids = data_NGV_j[~data_NGV_j['org_code'].isin(data_NGV_j1['org_code'])]
@@ -111,9 +111,11 @@ class UpdateNGVData:
             logger.info(f"人员转换完成")
 
             # 数字保留3位小数
-            filtered_df['g_month_percentage'] = (pd.to_numeric(data_NGV_j['g_month_percentage'], errors='coerce')
+            filtered_df['g_month_percentage'] = (
-                                                .round(3)
+                pd.to_numeric(filtered_df['g_month_percentage'], errors='coerce')
-                                                .apply(lambda x: f"{x:.3f}" if pd.notna(x) else ''))
+                .round(3)
+                .apply(lambda x: f"{x:.3f}" if pd.notna(x) else '')
+            )
 
             # filtered_df.to_csv(r"D:\Idea Project\SaaS_V1.3\back_ground_module\output\NGV.csv")
 
@@ -138,17 +140,18 @@ class UpdateNGVData:
             # print(result_str[:500])
 
             # 保存到Excel文件
-            # output_path = r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细1.xlsx'
+            # output_path = r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细1.xlsx'
             # filtered_df.to_excel(output_path, index=False)
-            # data_NGV_j1.to_excel( r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细j1.xlsx', index=False)
+            # data_NGV_j1.to_excel( r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细j1.xlsx', index=False)
-            # data_NGV_j.to_excel( r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细j.xlsx', index=False)
+            # data_NGV_j.to_excel( r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细j.xlsx', index=False)
-            # new_df.to_excel(r'D:\Idea Project\F6+宜搭+其它(1)\new\文件输出\ngv明细ndf.xlsx', index=False)
+            # new_df.to_excel(r'D:\Idea Project\SaaS_V1.7\back_ground_module\output\ngv明细ndf.xlsx', index=False)
 
             common_module.send_task_status(task_start_time, "NGV新增数据")
             logger.info(f"任务完成。")
         except Exception as e:
             error_task_logger.error(f"任务执行时发生异常: {e}")
             common_module.send_task_error(task_start_time, "NGV新增数据", str(e))
+            # pass
 
     @staticmethod
     def row_to_dict(row, field_mapping):

back_ground_module/update_molecule_reporting_adjustment_to_bi.py

@@ -88,10 +88,6 @@ class MoleculeReportingAdjustment:
                         if id_in_map == field_id:
                             transformed_data[display_name] = value
                             break
-
-
-
-
                 # BI上已经实现
                 # if transformed_data.get("是否上传衡石") == "否" or transformed_data.get("是否上传衡石") is None:
                 #     continue

test/宜搭获取续约待办数据.py

@@ -0,0 +1,189 @@
+import os
+from datetime import datetime, timezone, timedelta
+import pandas as pd
+from tqdm import tqdm
+import json
+from yd_api import YDAPI
+from api import API
+import time
+
+output_dir = "output"
+os.makedirs(output_dir, exist_ok=True)
+
+api_instance = API()
+yd_api_instance = YDAPI()
+
+def generate_monthly_ranges(start: str, end: str):
+    """
+    生成按自然月划分的时间段列表（左闭右开）
+    例如: [('2025-11-01T00:00:00Z', '2025-12-01T00:00:00Z'), ...]
+    """
+    start_dt = datetime.fromisoformat(start.replace("Z", "+00:00"))
+    end_dt = datetime.fromisoformat(end.replace("Z", "+00:00"))
+
+    ranges = []
+    current = start_dt
+
+    while current < end_dt:
+        # 下一个月的第一天
+        if current.month == 12:
+            next_month = current.replace(year=current.year + 1, month=1, day=1)
+        else:
+            next_month = current.replace(month=current.month + 1, day=1)
+        # 不超过 end_dt
+        segment_end = min(next_month, end_dt)
+        ranges.append((
+            current.strftime("%Y-%m-%dT00:00:00Z"),
+            segment_end.strftime("%Y-%m-%dT00:00:00Z")
+        ))
+        current = next_month
+
+    return ranges
+
+class GetYDData:
+
+    def __init__(self):
+        self.FORMID = "FORM-PE866MD1MJMU0WGLYRFLYEN5YN9L1I55Z7ZUK22"
+        self.appType = "APP_UYZ0KG6L0CCNV80GZ66O"
+        self.systemToken = "XA966F81JAJOFCVVVKO64E9MIIZV1EWE5SFMKJ2"
+
+        # 第一段：2025-01-01 到 2025-11-01
+        first_segment = ("2025-01-01T00:00:00Z", "2025-11-01T00:00:00Z")
+
+        # 第二段：2025-11-01 到当前时间（按月拆分）
+        now_utc_str = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+        monthly_segments = generate_monthly_ranges("2025-11-01T00:00:00Z", now_utc_str)
+
+        # 合并所有时间段
+        self.time_ranges = [first_segment] + monthly_segments
+
+        print("📅 计划拉取以下时间段：")
+        for i, (s, e) in enumerate(self.time_ranges, 1):
+            print(f"  {i}. {s} → {e}")
+
+    def build_value_to_label_map(self, form_structure):
+        value_to_label_map = {}
+        fields = form_structure.get("result", [])
+        for field in fields:
+            field_id = field.get("fieldId")
+            component = field.get("componentName")
+            props = field.get("props", {})
+            data_source = props.get("dataSource", [])
+
+            if component in ["SelectField", "RadioField"] and data_source:
+                option_map = {}
+                for opt in data_source:
+                    val = opt.get("value")
+                    if val is None:
+                        continue
+                    text_obj = opt.get("text", {})
+                    if isinstance(text_obj, dict):
+                        zh_text = text_obj.get("zh_CN")
+                        if zh_text is None and "value" in text_obj:
+                            raw = text_obj["value"]
+                            if isinstance(raw, str) and raw.startswith('"') and raw.endswith('"'):
+                                zh_text = raw[1:-1]
+                            else:
+                                zh_text = str(val)
+                        elif zh_text is None:
+                            zh_text = str(val)
+                    else:
+                        zh_text = str(text_obj)
+                    option_map[str(val)] = zh_text
+                if option_map:
+                    value_to_label_map[field_id] = option_map
+        return value_to_label_map
+
+    def convert_record_values(self, record, value_map):
+        converted = {}
+        for key, val in record.items():
+            if key in value_map and val is not None:
+                str_val = str(val)
+                converted[key] = value_map[key].get(str_val, val)
+            else:
+                converted[key] = val
+        return converted
+
+    def fetch_records_in_range(self, token, start_time, end_time):
+        """拉取指定时间范围内的所有记录"""
+        try:
+            first_page = yd_api_instance.read_processes_instances(
+                token=token,
+                formUuid=self.FORMID,
+                page=1,
+                n=100,
+                appType=self.appType,
+                systemToken=self.systemToken,
+                instanceStatus="RUNNING",
+                modifiedFromTimeGMT=start_time,
+                modifiedToTimeGMT=end_time,
+            )
+        except Exception as e:
+            print(f"❌ 首页请求失败 ({start_time} ～ {end_time}): {e}")
+            return []
+
+        total_count = first_page.get("totalCount", 0)
+        total_pages = (total_count // 100) + (1 if total_count % 100 else 0)
+        print(f"📊 [{start_time[:10]} ～ {end_time[:10]}] 总记录数: {total_count}, 共 {total_pages} 页")
+
+        all_records = []
+        if total_count > 0:
+            all_records.extend(first_page.get("data", []))
+            for page in tqdm(range(2, total_pages + 1), desc=f"{start_time[:7]}"):
+                try:
+                    resp = yd_api_instance.read_processes_instances(
+                        token=token,
+                        formUuid=self.FORMID,
+                        page=page,
+                        n=100,
+                        appType=self.appType,
+                        systemToken=self.systemToken,
+                        instanceStatus="RUNNING",
+                        modifiedFromTimeGMT=start_time,
+                        modifiedToTimeGMT=end_time,
+                    )
+                    page_data = resp.get("data", [])
+                    all_records.extend(page_data)
+                    time.sleep(0.15)  # 稍微增加间隔，更安全
+                except Exception as e:
+                    print(f"⚠️ 第 {page} 页失败 ({start_time[:10]}): {e}")
+                    continue
+        return all_records
+
+    def main(self):
+        # Step 1: 获取表单结构
+        token = yd_api_instance.generateToken()
+        form_struct = yd_api_instance.get_form_structures(
+            token=token,
+            formUuid=self.FORMID
+        )
+        value_map = self.build_value_to_label_map(form_struct)
+        print("\n✅ 表单选项映射构建完成")
+
+        # Step 2: 按时间段拉取
+        all_records = []
+        for start_time, end_time in self.time_ranges:
+            print(f"\n⏳ 拉取: {start_time} → {end_time}")
+            records = self.fetch_records_in_range(token, start_time, end_time)
+            all_records.extend(records)
+
+        print(f"\n📥 总共获取 {len(all_records)} 条流程实例")
+
+        # Step 3: 转换 formData
+        converted_records = []
+        for inst in all_records:
+            form_data = inst.get("formData", {})
+            converted = self.convert_record_values(form_data, value_map)
+            converted_records.append(converted)
+
+        # Step 4: 保存
+        if converted_records:
+            df = pd.DataFrame(converted_records)
+            output_path = os.path.join(output_dir, "converted_yd_data.csv")
+            df.to_csv(output_path, index=False, encoding="utf_8_sig")
+            print(f"\n✅ 成功保存 {len(converted_records)} 条记录至: {output_path}")
+        else:
+            print("\n❌ 无有效数据")
+
+if __name__ == "__main__":
+    GetYDData().main()

test/异常回访待办问题排查.ipynb

@@ -0,0 +1,158 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2026-01-07T02:17:11.661841100Z",
+     "start_time": "2026-01-07T02:17:11.600589500Z"
+    }
+   },
+   "source": [
+    "from back_ground_module import CommonModule\n",
+    "from api import API\n",
+    "from log_config import configure_task_logger, configure_error_task_logger\n",
+    "from datetime import datetime, timedelta, timezone\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "\n",
+    "# 获取已经配置好的常规日志记录器\n",
+    "logger = configure_task_logger()\n",
+    "# 获取已经配置好的错误任务日志记录器\n",
+    "error_task_logger = configure_error_task_logger()\n",
+    "# 保存为CSV文件\n",
+    "output_dir = \"output\"  # 设置输出目录\n",
+    "# 创建输出目录（如果不存在）\n",
+    "import os\n",
+    "\n",
+    "os.makedirs(output_dir, exist_ok=True)\n",
+    "common_module = CommonModule()\n",
+    "api_instance = API()\n",
+    "\n",
+    "data_JCB = common_module.get_jcb_details()\n",
+    "current_local = datetime.now() + timedelta(days=-1) # tz-naive，代表本地时间\n",
+    "current_date_str = current_local.strftime(\"%Y-%m-%d\")\n",
+    "# 计算30天前的本地日期（用于开户日判断）\n",
+    "thirty_days_ago_local = (current_local - timedelta(days=30)).date()\n",
+    "payload = {\"api_key\": \"6717470a0b3975ef583c6df1\",\n",
+    "                   \"entry_id\": \"67174710da507490d8ac12c1\",\n",
+    "                   }\n",
+    "daily_revisit = api_instance.entry_data_list(payload)\n",
+    "daily_revisit_list = daily_revisit.get(\"data\")  # api请求格式，将数据封装在data字典里\n",
+    "abnormal_data = []\n",
+    "for index, row in data_JCB.iterrows():\n",
+    "    try:\n",
+    "        # 开户日是本地日期字符串，解析为 date 对象\n",
+    "        open_date = datetime.strptime(str(row['开户日']), \"%Y-%m-%d\").date()\n",
+    "    except (ValueError, TypeError):\n",
+    "        continue  # 跳过无效日期\n",
+    "\n",
+    "    if (\n",
+    "            open_date < thirty_days_ago_local\n",
+    "            and row['近30天开单天数'] == 0\n",
+    "            and row['客户状态'] == \"留存\"\n",
+    "    ):\n",
+    "        new_row = row.copy()\n",
+    "        new_row[\"日期\"] = open_date.strftime(\"%Y-%m-%d\")\n",
+    "        abnormal_data.append(new_row)\n",
+    "\n",
+    "abnormal_data = pd.DataFrame(abnormal_data) if abnormal_data else pd.DataFrame()\n",
+    "\n",
+    "if not abnormal_data.empty:\n",
+    "    abnormal_data[\"表单类型\"] = \"异常待办\"\n",
+    "    abnormal_data[\"派发日期\"] = current_date_str\n",
+    "\n",
+    "    # 清洗手机号（仅去除浮点型 .0）\n",
+    "    def clean_phone(x):\n",
+    "        if pd.isna(x) or x == \"\" or x == \"None\":\n",
+    "            return \"\"\n",
+    "        s = str(x)\n",
+    "        if s.endswith('.0') and s[:-2].isdigit():\n",
+    "            return s[:-2]\n",
+    "        return s\n",
+    "\n",
+    "    abnormal_data['联系手机号'] = abnormal_data['联系手机号'].apply(clean_phone)\n",
+    "\n",
+    "# 构建云端已派发记录 DataFrame\n",
+    "df_cloud = pd.DataFrame([\n",
+    "    {\n",
+    "        \"数据id\": item.get(\"_id\", \"\"),\n",
+    "        \"账号\": item.get(\"_widget_1739258942667\", \"\"),\n",
+    "        \"提交时间\": item.get(\"createTime\", \"\"),\n",
+    "        \"表单类型\": item.get(\"_widget_1739951204545\", \"\")\n",
+    "    }\n",
+    "    for item in daily_revisit_list\n",
+    "])\n",
+    "\n",
+    "recent_accounts = set()\n",
+    "if not df_cloud.empty and not abnormal_data.empty:\n",
+    "    # 将 createTime 转为 UTC 时间（强制统一时区）\n",
+    "    df_cloud[\"提交时间\"] = pd.to_datetime(df_cloud[\"提交时间\"], utc=True, errors=\"coerce\")\n",
+    "    df_cloud = df_cloud.dropna(subset=[\"提交时间\"])\n",
+    "\n",
+    "    # 筛选“异常待办”\n",
+    "    df_abnormal_cloud = df_cloud[df_cloud[\"表单类型\"] == \"异常待办\"]\n",
+    "\n",
+    "    if not df_abnormal_cloud.empty:\n",
+    "        # 每个账号保留最新一条\n",
+    "        df_recent = df_abnormal_cloud.sort_values(\"提交时间\").groupby(\"账号\", as_index=False).tail(1)\n",
+    "\n",
+    "        current_utc = datetime.now(timezone.utc)\n",
+    "        cutoff_utc = pd.Timestamp(current_utc) - pd.Timedelta(days=30)\n",
+    "\n",
+    "        # 安全比较：两边都是 UTC\n",
+    "        recent_accounts = set(df_recent[df_recent[\"提交时间\"] > cutoff_utc][\"账号\"])\n",
+    "\n",
+    "# 剔除已派发账号 + 过滤有效手机号\n",
+    "if not abnormal_data.empty:\n",
+    "    abnormal_data = abnormal_data[\n",
+    "        (~abnormal_data[\"账号\"].isin(recent_accounts)) &\n",
+    "        (abnormal_data[\"联系手机号\"].notna()) &\n",
+    "        (abnormal_data[\"联系手机号\"] != \"\") &\n",
+    "        (abnormal_data[\"联系手机号\"] != \"None\")\n",
+    "        ]\n",
+    "\n",
+    "# # 保存结果\n",
+    "output_path = os.path.join(output_dir, \"异常待办1.csv\")\n",
+    "abnormal_data.to_csv(output_path, index=False)"
+   ],
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'back_ground_module'",
+     "output_type": "error",
+     "traceback": [
+      "\u001B[31m---------------------------------------------------------------------------\u001B[39m",
+      "\u001B[31mModuleNotFoundError\u001B[39m                       Traceback (most recent call last)",
+      "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[3]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mback_ground_module\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m CommonModule\n\u001B[32m      2\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mapi\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m API\n\u001B[32m      3\u001B[39m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34;01mlog_config\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m configure_task_logger, configure_error_task_logger\n",
+      "\u001B[31mModuleNotFoundError\u001B[39m: No module named 'back_ground_module'"
+     ]
+    }
+   ],
+   "execution_count": 3
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

test/异常回访待办问题排查.py

@@ -0,0 +1,112 @@
+from back_ground_module import CommonModule
+from api import API
+from log_config import configure_task_logger, configure_error_task_logger
+from datetime import datetime, timedelta, timezone
+import pandas as pd
+import os
+
+# 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()
+
+data_JCB = common_module.get_jcb_details()
+output_path = os.path.join(output_dir, "借车包明细.csv")
+data_JCB.to_csv(output_path, index=False)
+
+current_local = datetime.now() + timedelta(days=-1) # tz-naive，代表本地时间
+current_date_str = current_local.strftime("%Y-%m-%d")
+# 计算30天前的本地日期（用于开户日判断）
+thirty_days_ago_local = (current_local - timedelta(days=30)).date()
+payload = {"api_key": "6717470a0b3975ef583c6df1",
+                   "entry_id": "67174710da507490d8ac12c1",
+                   }
+daily_revisit = api_instance.entry_data_list(payload)
+daily_revisit_list = daily_revisit.get("data")  # api请求格式，将数据封装在data字典里
+abnormal_data = []
+for index, row in data_JCB.iterrows():
+    try:
+        # 开户日是本地日期字符串，解析为 date 对象
+        open_date = datetime.strptime(str(row['开户日']), "%Y-%m-%d").date()
+    except (ValueError, TypeError):
+        continue  # 跳过无效日期
+
+    if (
+            open_date < thirty_days_ago_local
+            and row['近30天开单天数'] == 0
+            and row['客户状态'] == "留存"
+    ):
+        new_row = row.copy()
+        new_row["日期"] = open_date.strftime("%Y-%m-%d")
+        abnormal_data.append(new_row)
+
+abnormal_data = pd.DataFrame(abnormal_data) if abnormal_data else pd.DataFrame()
+output_path = os.path.join(output_dir, "异常待办.csv")
+abnormal_data.to_csv(output_path, index=False)
+
+if not abnormal_data.empty:
+    abnormal_data["表单类型"] = "异常待办"
+    abnormal_data["派发日期"] = current_date_str
+
+    # 清洗手机号（仅去除浮点型 .0）
+    def clean_phone(x):
+        if pd.isna(x) or x == "" or x == "None":
+            return ""
+        s = str(x)
+        if s.endswith('.0') and s[:-2].isdigit():
+            return s[:-2]
+        return s
+
+    abnormal_data['联系手机号'] = abnormal_data['联系手机号'].apply(clean_phone)
+
+# 构建云端已派发记录 DataFrame
+df_cloud = pd.DataFrame([
+    {
+        "数据id": item.get("_id", ""),
+        "账号": item.get("_widget_1739258942667", ""),
+        "提交时间": item.get("createTime", ""),
+        "表单类型": item.get("_widget_1739951204545", "")
+    }
+    for item in daily_revisit_list
+])
+output_path = os.path.join(output_dir, "异常待办云端.csv")
+df_cloud.to_csv(output_path, index=False)
+recent_accounts = set()
+if not df_cloud.empty and not abnormal_data.empty:
+    # 将 createTime 转为 UTC 时间（强制统一时区）
+    df_cloud["提交时间"] = pd.to_datetime(df_cloud["提交时间"], utc=True, errors="coerce")
+    df_cloud = df_cloud.dropna(subset=["提交时间"])
+
+    # 筛选“异常待办”
+    df_abnormal_cloud = df_cloud[df_cloud["表单类型"] == "异常待办"]
+
+    if not df_abnormal_cloud.empty:
+        # 每个账号保留最新一条
+        df_recent = df_abnormal_cloud.sort_values("提交时间").groupby("账号", as_index=False).tail(1)
+
+        current_utc = datetime.now(timezone.utc)
+        cutoff_utc = pd.Timestamp(current_utc) - pd.Timedelta(days=30)
+
+        # 安全比较：两边都是 UTC
+        recent_accounts = set(df_recent[df_recent["提交时间"] > cutoff_utc]["账号"])
+
+# 剔除已派发账号 + 过滤有效手机号
+if not abnormal_data.empty:
+    abnormal_data = abnormal_data[
+        (~abnormal_data["账号"].isin(recent_accounts)) &
+        (abnormal_data["联系手机号"].notna()) &
+        (abnormal_data["联系手机号"] != "") &
+        (abnormal_data["联系手机号"] != "None")
+        ]
+
+# # 保存结果
+output_path = os.path.join(output_dir, "异常待办1.csv")
+abnormal_data.to_csv(output_path, index=False)

test/续约待办宜搭同步简道云.py

@@ -1,33 +0,0 @@
-from datetime import datetime
-import os
-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
-
-logger = configure_task_logger()
-error_task_logger = configure_error_task_logger()
-output_dir = "output"  # 设置输出目录
-os.makedirs(output_dir, exist_ok=True)
-common_module = CommonModule()
-api_instance = API()
-
-
-class YdToJDYRenewalToDo:
-    def __init__(self):
-        pass
-
-    def load_all_data(self):
-        """
-        从各类来源加载数据上加载数据
-        :return:
-        """
-
-    def main(self):
-        pass
-
-
-if __name__ == '__main__':
-    yd_to_jd_renewal_to_do = YdToJDYRenewalToDo()
-    yd_to_jd_renewal_to_do.main()

tools/BI.ipynb

@@ -421,8 +421,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2026-01-06T08:21:20.943512600Z",
+     "end_time": "2026-01-06T08:49:37.955377100Z",
-     "start_time": "2026-01-06T08:21:19.361422Z"
+     "start_time": "2026-01-06T08:49:37.747330400Z"
     }
    },
    "cell_type": "code",
@@ -454,7 +454,7 @@
     "\n",
     "        # 使用DELETE删除ID大于等于127821的数据\n",
     "        # cursor.execute(f\"DELETE FROM {table_name} WHERE id >= {min_id_to_delete}\")\n",
-    "        cursor.execute(f\"DELETE FROM GP_monthly_renewal_rate_new WHERE 月分区（仅用于存储每月最后一天截至数据） = '202512';\")\n",
+    "        cursor.execute(f\"DELETE FROM GP_annual_renewal_rate_new WHERE 月分区（仅用于存储每月最后一天截至数据） = '202512';\")\n",
     "\n",
     "        connection.commit()\n",
     "\n",
@@ -478,7 +478,7 @@
      ]
     }
    ],
-   "execution_count": 2
+   "execution_count": 7
   },
   {
    "metadata": {},

yd_api.py

@@ -155,7 +155,7 @@ class YDAPI:
                                  systemToken="XA966F81JAJOFCVVVKO64E9MIIZV1EWE5SFMKJ2", instanceStatus="RUNNING",
                                  max_retries=10, delay=2, createFromTimeGMT=None, createToTimeGMT=None,
                                  modifiedFromTimeGMT=None,
-                                 modifiedToTimeGMT=None, searchFieldJson={}):
+                                 modifiedToTimeGMT=None, searchFieldJson={},useAlias=False):
         """
         函数功能：读取流程表单的所有数据，并加入重试机制。
 
@@ -196,7 +196,8 @@ class YDAPI:
             "modifiedToTimeGMT": modifiedToTimeGMT,
             "searchFieldJson": json.dumps(
                 searchFieldJson
-            )
+            ),
+            "useAlias": useAlias,
         }
         # print(formData)
 
@@ -460,39 +461,40 @@ class YDAPI:
     def get_form_structures(self, token, formUuid, appType="APP_UYZ0KG6L0CCNV80GZ66O",
                             systemToken="XA966F81JAJOFCVVVKO64E9MIIZV1EWE5SFMKJ2", max_retries=20):
         """
-        函数功能：获取表单结构 # 宜搭废弃
+        获取表单结构（宜搭）
-
+        注意：该接口必须使用 GET 方法，参数通过 query string 传递
-        Args:
-            token (str): 登录验证token，用于API调用的身份验证。
-            formUuid (str): 表单的UUID，标识要获取结构的表单。
-            appType
-
-        Returns:
-            响应值: 如果请求成功，则返回服务器的JSON响应；如果请求失败或无响应，则返回一个表示获取成功信息的字符串。
         """
 
-        api = f'https://api.dingtalk.com/v1.0/yida/forms/formFields'
+        api_base = 'https://api.dingtalk.com/v1.0/yida/forms/formFields'
-        headers = {
+
-            "Content-Type": "application/json",
+        # 构造查询参数
-            "x-acs-dingtalk-access-token": token
+        params = {
-        }
-        retries = 0
-        data_get = {}
-        payload = {
-            "formUuid": formUuid,
             "appType": appType,
             "systemToken": systemToken,
+            "formUuid": formUuid,
             "userId": "2268275546837446",
         }
+
+        headers = {
+            "x-acs-dingtalk-access-token": token
+        }
+
+        retries = 0
         while retries < max_retries:
-            res = requests.post(api, headers=headers, json=payload)
+            try:
-            if res.status_code == 200:
+                # 使用 GET，并传入 params（自动编码为 query string）
-                data_get = res.json()
+                res = requests.get(api_base, headers=headers, params=params, timeout=10)
-                break
+                if res.status_code == 200:
-            else:
+                    return res.json()
-                retries += 1
+                else:
-                time.sleep(0.1)
+                    print(f"请求失败，状态码: {res.status_code}, 响应: {res.text}")
-        return data_get
+            except Exception as e:
+                print(f"请求异常: {e}")
+
+            retries += 1
+            time.sleep(0.1)
+
+        return {}  # 或抛出异常
 
 
 class NpEncoder(json.JSONEncoder):