import pandas as pd
from indicators.sma import calculate_21_50_sma
from indicators.bollinger_bands import calculate_bollinger_bands

def check_buy_signal(data):
    """
    Analyzes stock data to identify buy signals based on the criteria:
    - On the 1 day time frame, the 21-period SMA is above the 50-period SMA.
    - The 21-period SMA has been above the 50-period SMA for more than 1 day.
    - On the 1-hour time frame, the 21-period SMA has just crossed above the 50-period SMA from below.
    
    Parameters:
    - data (pd.DataFrame): The stock data with 'SMA_21', 'SMA_50' columns.
    
    Returns:
    - pd.Series: A boolean series indicating buy signals.
    """
    # Assuming 'data' has 'SMA_21' and 'SMA_50' calculated for both 1 day and 1 hour time frames
    buy_signal = (data['SMA_21'] > data['SMA_50']) & (data['SMA_21'].shift(1) > data['SMA_50'].shift(1))
    return buy_signal

def check_sell_signal(data):
    """
    Analyzes stock data to identify sell signals based on the criteria:
    - The price has crossed above the upper band of the 1.7SD Bollinger Band on the 21-period SMA.
    
    Parameters:
    - data (pd.DataFrame): The stock data with 'Close', 'BB_Upper' columns.
    
    Returns:
    - pd.Series: A boolean series indicating sell signals.
    """
    # Assuming 'data' has 'Close' and 'BB_Upper' calculated
    sell_signal = data['Close'] > data['BB_Upper']
    return sell_signal

def generate_signals(stock_data):
    """
    Main function to generate buy and sell signals for a given stock.
    
    Parameters:
    - stock_data (pd.DataFrame): The stock data.
    
    Returns:
    - pd.DataFrame: The stock data with additional columns 'Buy_Signal' and 'Sell_Signal'.
    """
    # First, ensure the necessary SMA and Bollinger Bands are calculated
    stock_data = calculate_21_50_sma(stock_data)
    stock_data = calculate_bollinger_bands(stock_data)
    
    # Generate buy and sell signals
    stock_data['Buy_Signal'] = check_buy_signal(stock_data)
    stock_data['Sell_Signal'] = check_sell_signal(stock_data)
    
    return stock_data

if __name__ == "__main__":
    # Example usage
    # This part is meant for testing. You'll need to replace it with actual stock data fetching.
    dates = pd.date_range(start='2023-01-01', periods=100, freq='D')
    close_prices = pd.Series((100 + pd.np.random.randn(100).cumsum()), index=dates)
    sample_data = pd.DataFrame({'Close': close_prices})
    
    signals_data = generate_signals(sample_data)
    print(signals_data[['Buy_Signal', 'Sell_Signal']].tail())