import MetaTrader5 as mt5
import pandas as pd
from datetime import datetime
import time
import logging

# Configure logging
logging.basicConfig(filename='trading_bot.log', level=logging.INFO, format='%(asctime)s - %(levelname)s: %(message)s')

# Connect to the MetaTrader 5 terminal
if not mt5.initialize():
    logging.error("Failed to initialize MetaTrader 5")
    quit()

# Define parameters
symbol = "EURUSD"
timeframe = mt5.TIMEFRAME_M30
fast_ma_period = 50
slow_ma_period = 200
risk_per_trade = 0.02  # Risk 2% of account balance per trade

# Main trading function
def main():
    while True:
        try:
            # Retrieve market data
            rates = mt5.copy_rates_from_pos(symbol, timeframe, 0, 1)
            if rates is not None and len(rates) > 0:
                current_price = rates[0][mt5.TIME_CLOSE]

                # Check for buy signal
                if is_buy_signal():
                    # Calculate order volume based on risk per trade
                    account_info = mt5.account_info()
                    if account_info is not None:
                        balance = account_info.balance
                        volume = calculate_volume(balance)

                        # Place buy order
                        order = mt5.order_send(symbol=symbol, action=mt5.ORDER_BUY, volume=volume, type=mt5.ORDER_MARKET, deviation=20)
                        logging.info("Buy order placed at price: %s", current_price)
                        print("Buy order placed at price:", current_price)
                        time.sleep(5)  # Wait for 5 seconds before checking for order status

                        # Check order status
                        check_order_status(order)

        except Exception as e:
            logging.error("An error occurred: %s", str(e))
            print("An error occurred:", str(e))

        time.sleep(60)  # Wait for 1 minute before checking again

# Function to calculate order volume based on risk per trade
def calculate_volume(balance):
    risk_amount = balance * risk_per_trade
    volume = risk_amount / (current_price * 100000)  # 1 lot = 100,000 units
    return volume

# Function to check for buy signal based on moving average crossover strategy
def is_buy_signal():
    # Retrieve historical prices for calculating moving averages
    rates = mt5.copy_rates_from_pos(symbol, timeframe, 0, fast_ma_period + 1)
    if rates is not None and len(rates) > 0:
        df = pd.DataFrame(rates)
        df['MA_fast'] = df['close'].rolling(window=fast_ma_period).mean()
        df['MA_slow'] = df['close'].rolling(window=slow_ma_period).mean()

        # Check for crossover
        if df['MA_fast'].iloc[-1] > df['MA_slow'].iloc[-1] and df['MA_fast'].iloc[-2] <= df['MA_slow'].iloc[-2]:
            return True

    return False

# Function to check and handle order status
def check_order_status(order):
    order_info = mt5.order_get(order)
    if order_info is not None:
        if order_info.status == mt5.ORDER_STATUS_FILLED:
            logging.info("Order filled: %s", order_info)
            print("Order filled:", order_info)
            # Implement logic for setting stop-loss and take-profit levels
            # Example: mt5.order_send(symbol=symbol, action=mt5.ORDER_SELL, volume=order_info.volume, type=mt5.ORDER_MARKET, deviation=20)
        else:
            logging.warning("Order status: %s", order_info.status)
            print("Order status:", order_info.status)
    else:
        logging.warning("Order not found")
        print("Order not found")

# Run the main trading function
if __name__ == "__main__":
    main()