app.py

import gradio as gr
import yfinance as yf
from prophet import Prophet
import plotly.express as px
from datetime import datetime
import plotly.graph_objects as go


def download_data(ticker, start_date='2010-01-01'):
    """ 데이터를 다운로드하고 적절히 포맷팅하는 함수 """
    data = yf.download(ticker, start=start_date)
    if data.empty:
        raise ValueError(f"No data returned for {ticker}")
    data.reset_index(inplace=True)
    if 'Adj Close' in data.columns:
        data = data[['Date', 'Adj Close']]
        data.rename(columns={'Date': 'ds', 'Adj Close': 'y'}, inplace=True)
    else:
        raise ValueError("Expected 'Adj Close' in columns")
    return data

def predict_future_prices(ticker, periods=1825):  # 5년간의 데이터 예측
    data = yf.download(ticker, start="2010-01-01")['Adj Close'].reset_index()
    data.rename(columns={'Date': 'ds', 'Adj Close': 'y'}, inplace=True)
    
    model = Prophet(daily_seasonality=False, weekly_seasonality=False, yearly_seasonality=True)
    model.fit(data)
    
    future = model.make_future_dataframe(periods=periods, freq='D')
    forecast = model.predict(future)
    
    # Timestamp를 문자열로 변환
    forecast['ds'] = forecast['ds'].dt.strftime('%Y-%m-%d')
    
    fig = go.Figure(data=[go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='Forecast')])
    fig.update_layout(title=f'5-Year Future Price Forecast for {ticker}', xaxis_title='Date', yaxis_title='Predicted Price')

    return fig, forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].to_dict(orient='records')

# 이제 이 함수를 Gradio 인터페이스와 연결하여 사용자가 시각화를 볼 수 있게 합니다.


# Gradio 인터페이스 설정
with gr.Blocks() as app:
    with gr.Row():
        ticker_input = gr.Textbox(value="AAPL", label="Enter Stock Ticker")
        forecast_button = gr.Button("Generate 5-Year Forecast")
    
    forecast_chart = gr.Plot(label="Future Price Forecast")
    forecast_data = gr.Dataframe(label="Forecast Data Table")
    
    forecast_button.click(
        fn=predict_future_prices,
        inputs=ticker_input,
        outputs=[forecast_chart, forecast_data]
    )

app.launch()