Update app.py

app.py

@@ -5,9 +5,10 @@ import pandas as pd
 from datetime import datetime
 import plotly.graph_objects as go
 import plotly.express as px
+import json
+import numpy as np
 
 def download_data(ticker, start_date='2010-01-01'):
-    """ 주식 데이터를 다운로드하고 포맷을 조정하는 함수 """
     data = yf.download(ticker, start=start_date)
     if data.empty:
         raise ValueError(f"No data returned for {ticker}")
@@ -15,38 +16,30 @@ def download_data(ticker, start_date='2010-01-01'):
     if 'Adj Close' in data.columns:
         data = data[['Date', 'Adj Close']].copy()
         data.rename(columns={'Date': 'ds', 'Adj Close': 'y'}, inplace=True)
-        data['ds'] = pd.to_datetime(data['ds'])  # Ensure 'ds' is datetime type
+        data['ds'] = pd.to_datetime(data['ds'])
     else:
         raise ValueError("Expected 'Adj Close' in columns")
     return data
 
+def json_serial(obj):
+    """JSON serializer for objects not serializable by default json code"""
+    if isinstance(obj, (datetime, np.datetime64)):
+        return obj.isoformat()
+    raise TypeError("Type not serializable")
+
 def predict_future_prices(ticker, periods=1825):
     data = download_data(ticker)
-    
-    # Prophet 모델 생성 및 학습
     model = Prophet(daily_seasonality=False, weekly_seasonality=True, yearly_seasonality=True)
     model.fit(data)
-    
-    # 미래 데이터 프레임 생성 및 예측
     future = model.make_future_dataframe(periods=periods, freq='D')
     forecast = model.predict(future)
-    
-    # 예측 결과 그래프 생성
+    forecast['ds'] = forecast['ds'].apply(pd.to_datetime)
     fig_main = go.Figure()
     fig_main.add_trace(go.Scatter(x=data['ds'], y=data['y'], mode='lines', name='Actual (Black)', line=dict(color='black')))
     fig_main.add_trace(go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='Forecast (Blue)'))
-    
-    # 연간 및 주간 계절성 그래프 생성
-    # 임시로 matplotlib 플롯 반환을 비활성화하고 결과만 반환
-    fig_seasonal = model.plot_components(forecast)
-    forecast['ds'] = pd.to_datetime(forecast['ds'])  # Revert to datetime type to avoid AttributeError
-    
-    fig_yearly = px.line(x=pd.to_datetime(forecast['ds']), y=forecast['yearly'], labels={'x': 'Date', 'y': 'Yearly Trend'})
-    fig_weekly = px.line(x=pd.to_datetime(forecast['ds']), y=forecast['weekly'], labels={'x': 'Date', 'y': 'Weekly Trend'})
-
-    return fig_main, forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']], fig_yearly, fig_weekly
+    fig_main.update_layout(title="Forecast vs Actual Stock Prices")
+    return json.dumps({"figure": fig_main.to_json(), "forecast": forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].to_dict('records')}, default=json_serial)
 
-# Gradio 인터페이스 설정 및 실행
 with gr.Blocks() as app:
     with gr.Row():
         ticker_input = gr.Textbox(value="AAPL", label="Enter Stock Ticker for Forecast")
@@ -55,13 +48,11 @@ with gr.Blocks() as app:
         
     forecast_chart = gr.Plot(label="Forecast Chart")
     forecast_data = gr.Dataframe(label="Forecast Data")
-    yearly_chart = gr.Plot(label="Yearly (Monthly) Trend Chart")
-    weekly_chart = gr.Plot(label="Weekly Trend Chart")
     
     forecast_button.click(
         fn=predict_future_prices,
         inputs=[ticker_input, periods_input],
-        outputs=[forecast_chart, forecast_data, yearly_chart, weekly_chart]
+        outputs=[forecast_chart, forecast_data]
     )
 
 app.launch()