Update app.py

app.py

@@ -1005,25 +1005,25 @@ def advanced_xgboost_predict(predict_days=5):
         dji_return = 0
         sox_return = 0
         
-        # 嘗試獲取美股前一日報酬率
-        try:
-            dji_data = get_stock_data('^DJI', '5d')
-            if not dji_data.empty and len(dji_data) >= 2:
-                dji_return = (dji_data['Close'].iloc[-1] / dji_data['Close'].iloc[-2] - 1)
-        except:
-            pass
+            # 嘗試獲取美股前一日報酬率
+            try:
+                dji_data = get_stock_data('^DJI', '5d')
+                if not dji_data.empty and len(dji_data) >= 2:
+                    dji_return = (dji_data['Close'].iloc[-1] / dji_data['Close'].iloc[-2] - 1)
+            except:
+                pass
+                
+            try:
+                sox_data = get_stock_data('^SOX', '5d') 
+                if not sox_data.empty and len(sox_data) >= 2:
+                    sox_return = (sox_data['Close'].iloc[-1] / sox_data['Close'].iloc[-2] - 1)
+            except:
+                pass
             
-        try:
-            sox_data = get_stock_data('^SOX', '5d') 
-            if not sox_data.empty and len(sox_data) >= 2:
-                sox_return = (sox_data['Close'].iloc[-1] / sox_data['Close'].iloc[-2] - 1)
-        except:
-            pass
-        
-        # 檢查並處理 NaN 值，建立特徵狀態記錄
-        feature_status = {}
-        features_list = []
-        feature_names = []
+            # 檢查並處理 NaN 值，建立特徵狀態記錄
+            feature_status = {}
+            features_list = []
+            feature_names = []
         
         # 處理本地計算的技術指標特徵
         for feature in model_feature_columns: