非标业绩提报、合伙人结算登记字段修改

续约回访 宜搭同步简道云辅助脚本 简道云同步宜搭辅助脚本

back_ground_module/partner_settlement_to_BI.py

@@ -53,6 +53,17 @@ class PartnerSettlementToBI:
             "特殊情况备注": "_widget_1712805391035",
             "合伙人介绍证明（微信聊天截图等）": "_widget_1712815331256",
             "合伙人类型": "_widget_1753957844818",
+            "小程序签约状态": "_widget_1756087218860",
+            "订单登记表.订单支付时间": "_widget_1712803222905._widget_1762918516630",
+            "小程序签约状态-核实": "_widget_1756084913318",
+            "签约状态-手机号匹配": "_widget_1756195470603",
+            "签约状态-姓名匹配": "_widget_1756195470602",
+            "是否重名": "_widget_1756195470601",
+            "结算月份": "_widget_1756704906867",
+            "订单支付时间-核实": "_widget_1756804675274",
+            "结算状态": "_widget_1756804412410",
+            "提成动作": "_widget_1758529175921",
+            "是否同步": "_widget_1762855878035",
             "提交时间": "createTime",
             "更新时间": "updateTime"
         }
@@ -68,6 +79,7 @@ class PartnerSettlementToBI:
                 "_widget_1753952737266": "佣金",
                 "_widget_1753952737267": "理论佣金",
                 "_widget_1712807001396": "佣金比例",
+                "_widget_1762918516630": "订单支付时间",
             },
             # 可以在这里添加其他列表字段的配置
             # "另一个列表字段": {
@@ -127,7 +139,7 @@ class PartnerSettlementToBI:
             df[col] = df[col].map(lambda x: x.get("name", "") if isinstance(x, dict) else "")
 
         # 3.日期字段转为北京时间
-        time_columns = ["提交时间", "更新时间"]
+        time_columns = ["提交时间", "更新时间","订单支付时间-核实","结算月份"]
 
         df[time_columns] = df[time_columns].apply(
             lambda col: pd.to_datetime(col, errors='coerce')
@@ -154,6 +166,15 @@ class PartnerSettlementToBI:
                     lambda x: x.get(field) if isinstance(x, dict) else None
                 )
 
+            time_columns_nested = ["订单支付时间"]  # 来自订单登记表等嵌套结构
+
+            # 时间字段标准化：处理订单支付时间
+            for col in time_columns_nested:
+                if col in df_exploded.columns:
+                    df_exploded[col] = pd.to_datetime(df_exploded[col], errors='coerce') \
+                        .dt.tz_localize(None) \
+                        .dt.strftime('%Y-%m-%d %H:%M:%S')
+
             # 删除原始的订单登记表列
             df_exploded = df_exploded.drop(columns=["订单登记表"])