import matplotlib.pyplot as plt
import matplotlib.dates as mdates

def plot_data_with_indicators_and_signals(data):
    """
    Plots historical price data, SMAs, Bollinger Bands, and buy/sell signals.

    Args:
        data (pd.DataFrame): The DataFrame containing the historical prices, SMAs, Bollinger Bands,
                             and signals. It expects 'close', 'SMA_21', 'SMA_50', 'BB_Upper',
                             'BB_Lower', 'Buy_Signal', and 'Sell_Signal' columns.
    """
    # Create a new figure and set the size
    plt.figure(figsize=(14, 7))

    # Plot closing price
    plt.plot(data['date'], data['close'], label='Close Price', alpha=0.5)

    # Plot SMAs
    plt.plot(data['date'], data['SMA_21'], label='21-Period SMA', alpha=0.75)
    plt.plot(data['date'], data['SMA_50'], label='50-Period SMA', alpha=0.75)

    # Plot Bollinger Bands
    plt.plot(data['date'], data['BB_Upper'], label='Upper Bollinger Band', linestyle='--', alpha=0.5)
    plt.plot(data['date'], data['BB_Lower'], label='Lower Bollinger Band', linestyle='--', alpha=0.5)

    # Highlight buy signals
    buy_signals = data[data['Buy_Signal']]
    plt.scatter(buy_signals['date'], buy_signals['close'], label='Buy Signal', marker='^', color='green', alpha=1)

    # Highlight sell signals
    sell_signals = data[data['Sell_Signal']]
    plt.scatter(sell_signals['date'], sell_signals['close'], label='Sell Signal', marker='v', color='red', alpha=1)

    # Formatting the plot
    plt.title('Cryptocurrency Analysis with Buy/Sell Signals')
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.legend()
    plt.grid(True)
    plt.xticks(rotation=45)
    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
    plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=5))

    # Show plot
    plt.tight_layout()
    plt.show()