Update app.py

app.py

@@ -136,6 +136,7 @@ def advanced_xgboost_predict(data, predict_days):
         # 1. 獲取外部市場數據
         start_date = data.index.min() - pd.Timedelta(days=5) # 提前幾天以確保數據填充
         end_date = data.index.max()
+    
         
         external_symbols = {'DJI': '^DJI', 'NAS': '^IXIC', 'SOX': '^SOX', 'S&P_500': '^GSPC', 'TSM_ADR': 'TSM'}
         
@@ -155,8 +156,8 @@ def advanced_xgboost_predict(data, predict_days):
         input_df['NEWS'] = news_score if news_score is not None else 0
         
         # 【修改】: 獲取最新月份的單一數值
-        input_df['business_climate'] = get_business_climate_data1()
-        input_df['PMI'] = get_pmi_data1()
+        input_df['business_climate'] = 15
+        input_df['PMI'] = 46.7
         
         # 5. 數據清洗與格式化
         # 向前填充所有缺失值 (例如假日)
@@ -299,27 +300,27 @@ def calculate_volume_profile(df, num_bins=50):
         print(f"Volume profile 計算錯誤: {e}")
         return None, None, None
 
-def get_business_climate_data1(get_latest_value=False):
-    try:
-        if not os.path.exists('business_climate.csv'): return None
-        df = pd.read_csv('business_climate.csv', index_col='Date', parse_dates=True)
-        if get_latest_value:
-            return df['Index'].iloc[-1]
-        return df
-    except Exception as e:
-        print(f"無法獲取景氣燈號資料: {str(e)}")
-        return None if get_latest_value else pd.DataFrame()
-
-def get_pmi_data1(get_latest_value=False):
-    try:
-        if not os.path.exists('taiwan_pmi.csv'): return None
-        df = pd.read_csv('taiwan_pmi.csv', index_col='Date', parse_dates=True)
-        if get_latest_value:
-            return df['Index'].iloc[-1]
-        return df
-    except Exception as e:
-        print(f"無法獲取 PMI 資料: {str(e)}")
-        return None if get_latest_value else pd.DataFrame()
+# def get_business_climate_data1(get_latest_value=False):
+#     try:
+#         if not os.path.exists('business_climate.csv'): return None
+#         df = pd.read_csv('business_climate.csv', index_col='Date', parse_dates=True)
+#         if get_latest_value:
+#             return df['Index'].iloc[-1]
+#         return df
+#     except Exception as e:
+#         print(f"無法獲取景氣燈號資料: {str(e)}")
+#         return None if get_latest_value else pd.DataFrame()
+
+# def get_pmi_data1(get_latest_value=False):
+#     try:
+#         if not os.path.exists('taiwan_pmi.csv'): return None
+#         df = pd.read_csv('taiwan_pmi.csv', index_col='Date', parse_dates=True)
+#         if get_latest_value:
+#             return df['Index'].iloc[-1]
+#         return df
+#     except Exception as e:
+#         print(f"無法獲取 PMI 資料: {str(e)}")
+#         return None if get_latest_value else pd.DataFrame()
 
 
 def generate_gemini_analysis(stock_name, stock_symbol, period, data):