非标业绩提报、合伙人结算登记字段时间分区修改

back_ground_module/partner_settlement_to_BI.py

@@ -139,13 +139,15 @@ 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","订单支付时间-核实","结算月份"]
+        # 3. 日期字段转为北京时间（主表）
+        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')
-            .dt.tz_localize(None)
-            .dt.strftime('%Y-%m-%d %H:%M:%S')
-        )
+        for col in time_columns:
+            if col in df.columns:
+                # 假设原始时间是 UTC（即使字符串无时区）
+                dt_utc = pd.to_datetime(df[col], errors='coerce', utc=True)
+                dt_beijing = dt_utc.dt.tz_convert('Asia/Shanghai')
+                df[col] = dt_beijing.dt.tz_localize(None).dt.strftime('%Y-%m-%d %H:%M:%S')
 
         # 4.处理订单登记表列表字段，将其拆分成多行
         if "订单登记表" in df.columns:
@@ -168,12 +170,11 @@ class PartnerSettlementToBI:
 
             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')
+                    dt_utc = pd.to_datetime(df_exploded[col], errors='coerce', utc=True)
+                    dt_beijing = dt_utc.dt.tz_convert('Asia/Shanghai')
+                    df_exploded[col] = dt_beijing.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"])