import pandas as pd
import yfinance as yf
import matplotlib.pyplot as plt
import io
import gradio as gr

def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
    try:
        df = yf.download(ticker, start=start_date, end=end_date, progress=False)
        if df.empty:
            return None, "No data available for the specified ticker and date range."
    except Exception as e:
        return None, f"Error fetching data: {str(e)}"

    df = df[['Close']]
    df['SMA_50'] = df['Close'].rolling(window=50).mean()
    df['SMA_150'] = df['Close'].rolling(window=150).mean()

    df['Signal'] = 0
    df.loc[df['SMA_50'] > df['SMA_150'], 'Signal'] = 1
    df.loc[df['SMA_50'] < df['SMA_150'], 'Signal'] = -1
    df['Position'] = df['Signal'].diff()

    cash = initial_budget
    shares = 0
    portfolio_values = []

    for _, row in df.iterrows():
        if pd.isna(row['Close']):
            continue
        if row['Position'] == 1 and cash > 0:
            shares = cash / row['Close']
            cash = 0
        elif row['Position'] == -1 and shares > 0:
            cash = shares * row['Close']
            shares = 0
        portfolio_value = cash + (shares * row['Close'])
        portfolio_values.append(portfolio_value)

    df = df.iloc[149:]
    df['Portfolio Value'] = portfolio_values[149:]

    plt.figure(figsize=(14, 8))
    plt.plot(df['Portfolio Value'], label='Portfolio Value', color='purple')
    plt.xlabel('Date')
    plt.ylabel('Portfolio Value ($)')
    plt.title(f'Portfolio Value Over Time with SMA Strategy ({ticker})')
    plt.legend()
    plt.grid()
    plt.tight_layout()

    plot_file = io.BytesIO()
    plt.savefig(plot_file, format='png')
    plot_file.seek(0)
    plt.close()

    final_value = portfolio_values[-1]
    profit_loss = final_value - initial_budget
    percentage_return = (profit_loss / initial_budget) * 100

    results = f"""
    Ticker: {ticker}
    Trading Period: {start_date} to {end_date}
    Initial Investment: ${initial_budget}
    Final Portfolio Value: ${final_value:.2f}
    Profit/Loss: ${profit_loss:.2f}
    Percentage Return: {percentage_return:.2f}%
    """

    return plot_file, results

with gr.Blocks() as app:
    gr.Markdown("# SMA Crossover Strategy Simulator")
    with gr.Row():
        initial_budget = gr.Number(label="Initial Investment ($)", value=100)
        start_date = gr.Text(label="Start Date (YYYY-MM-DD)", value="1993-01-01")
        end_date = gr.Text(label="End Date (YYYY-MM-DD)", value="2023-12-31")
        ticker = gr.Dropdown(
            label="Stock Ticker Symbol",
            choices=["SPY", "TSLA", "GOOGL", "AAPL", "MSFT"],
            value="SPY",
        )
    run_button = gr.Button("Run Simulation")
    portfolio_graph = gr.Image(label="Portfolio Value Over Time")
    summary_text = gr.Textbox(label="Simulation Summary", lines=8)

    run_button.click(
        sma_crossover_strategy,
        inputs=[initial_budget, start_date, end_date, ticker],
        outputs=[portfolio_graph, summary_text],
    )

if __name__ == "__main__":
    app.launch(server_port=7861)