get_stock_prices

app.py

@@ -83,10 +83,6 @@ def period_to_start_end(period_str: str):
 
 # --- 取得股票價格與技術指標 ---
 def get_stock_prices(ticker: str, period: str = "3mo") -> Union[Dict, str]:
-    """
-    使用 start 與 end 取得歷史股價資料（避免連線到 fc.yahoo.com），
-    並計算 RSI、Stochastic、MACD 與 VWAP 指標。
-    """
     try:
         start_date, end_date = period_to_start_end(period)
         data = yf.download(
@@ -95,40 +91,59 @@ def get_stock_prices(ticker: str, period: str = "3mo") -> Union[Dict, str]:
             end=end_date,
             interval='1d'
         )
-        df = data.copy()
-        # 若有 multi-index，調整欄位名稱
-        if df.columns.nlevels > 1:
-            df.columns = [col[0] for col in df.columns]
+
+        if data.empty:
+            return f"無法取得 {ticker} 的歷史資料"
+
+        # reset_index() 之後，立刻把欄位名稱都轉成字串
         data.reset_index(inplace=True)
-        data['Date'] = data['Date'].astype(str)
+        data.columns = [str(col) for col in data.columns]
+
+        # 如果你另外有 df = data.copy() 想做技術指標，也要確保欄位一致
+        df = data.copy()
+
+        # 計算技術指標
+        from ta.momentum import RSIIndicator, StochasticOscillator
+        from ta.trend import MACD
+        from ta.volume import volume_weighted_average_price
 
         indicators = {}
 
-        # RSI
-        rsi_series = RSIIndicator(df['Close'], window=14).rsi().iloc[-12:]
-        indicators["RSI"] = {date.strftime('%Y-%m-%d'): int(value) for date, value in rsi_series.dropna().to_dict().items()}
+        n = min(12, len(df))
+        rsi_series = RSIIndicator(df['Close'], window=14).rsi().iloc[-n:]
+        indicators["RSI"] = {
+            str(date.date()): int(value) for date, value in rsi_series.dropna().items()
+        }
 
-        # Stochastic Oscillator
-        sto_series = StochasticOscillator(df['High'], df['Low'], df['Close'], window=14).stoch().iloc[-12:]
-        indicators["Stochastic_Oscillator"] = {date.strftime('%Y-%m-%d'): int(value) for date, value in sto_series.dropna().to_dict().items()}
+        sto_series = StochasticOscillator(df['High'], df['Low'], df['Close'], window=14).stoch().iloc[-n:]
+        indicators["Stochastic_Oscillator"] = {
+            str(date.date()): int(value) for date, value in sto_series.dropna().items()
+        }
 
-        # MACD 與訊號線
         macd = MACD(df['Close'])
-        macd_series = macd.macd().iloc[-12:]
-        indicators["MACD"] = {date.strftime('%Y-%m-%d'): int(value) for date, value in macd_series.to_dict().items()}
-        macd_signal_series = macd.macd_signal().iloc[-12:]
-        indicators["MACD_Signal"] = {date.strftime('%Y-%m-%d'): int(value) for date, value in macd_signal_series.to_dict().items()}
+        macd_series = macd.macd().iloc[-n:]
+        indicators["MACD"] = {
+            str(date.date()): int(value) for date, value in macd_series.items()
+        }
+        macd_signal_series = macd.macd_signal().iloc[-n:]
+        indicators["MACD_Signal"] = {
+            str(date.date()): int(value) for date, value in macd_signal_series.items()
+        }
 
-        # VWAP
         vwap_series = volume_weighted_average_price(
             high=df['High'],
             low=df['Low'],
             close=df['Close'],
             volume=df['Volume']
-        ).iloc[-12:]
-        indicators["vwap"] = {date.strftime('%Y-%m-%d'): int(value) for date, value in vwap_series.to_dict().items()}
+        ).iloc[-n:]
+        indicators["vwap"] = {
+            str(date.date()): int(value) for date, value in vwap_series.items()
+        }
 
-        return {'stock_price': data.to_dict(orient='records'), 'indicators': indicators}
+        return {
+            'stock_price': data.to_dict(orient='records'),
+            'indicators': indicators
+        }
     except Exception as e:
         return f"Error fetching price data: {str(e)}"