Refactored form factor

main.py

@@ -0,0 +1,124 @@
+"""
+Main script for running the trading bot with a web interface.
+
+This script initializes the MetaTrader 5 connection, runs the trading bot, and integrates with a web interface for user credentials.
+
+Author: Mike Kiwalabye
+"""
+
+import time
+from flask import Flask, render_template, request, redirect, globals
+from src.connectors import mt5_connector
+from src.models import neural_network_model
+from src.strategies.trading_strategy import get_historical_data, calculate_indicators_and_detect_patterns, generate_trade_signals, execute_trade
+from src.utils.visualization import plot_trade_signals
+
+app = Flask(__name__)
+
+# Define input shape for the neural network
+input_shape = (10,)  # Adjust the input shape based on your features and data
+
+# Create the neural network model
+neural_network_model = neural_network_model.create_neural_network_model(input_shape)
+
+# Global state to track whether MT5 is initialized
+globals.mt5_initialized = False
+
+# Web Interface Routes
+
+@app.route('/')
+def index():
+    """Render the main page with login form."""
+    return render_template('index.html')
+
+@app.route('/login', methods=['POST'])
+def login():
+    """
+    Handle the login form submission.
+
+    If the credentials are valid, start the trading bot with the provided credentials.
+
+    Returns:
+    - str: HTML response.
+    """
+    if request.method == 'POST':
+        credentials = {
+            'username': request.form['username'],
+            'password': request.form['password'],
+            'server': request.form['server'],
+            'path': request.form['path']
+        }
+        if mt5_connector.connect_to_mt5(credentials):
+            # Set MT5 initialization state to True
+            globals.mt5_initialized = True
+            # Redirect to the main dashboard or another page
+            return redirect('/dashboard')
+        else:
+            return render_template('index.html', error='Invalid credentials. Please try again.')
+
+@app.route('/dashboard')
+def dashboard():
+    # Replace these with the actual MetaTrader data retrieval logic
+    mt5_data = mt5_connector.get_account_info()  # Replace with the actual method to get account info
+    user_data = {'username': mt5_data.name, 'account_balance': mt5_data.balance, 'currency': mt5_data.currency}
+    username = user_data.get('username', 'N/A')
+    account_balance = user_data.get('account_balance', 'N/A')
+    account_currency = user_data.get('currency', 'N/A')
+
+    return render_template('dashboard.html', username=username, account_balance=account_balance, account_currency=account_currency)
+
+# Flask app routes
+
+@app.route('/start_ml_bot', methods=['POST'])
+def start_ml_bot():
+    """
+    Handle the request to start the ML bot.
+
+    """
+
+    # Start the ML bot
+    run_trading_bot_web_interface()
+
+
+# Main Trading Bot Logic
+
+def run_trading_bot_web_interface():
+    """
+    Run the trading bot using MetaTrader 5 credentials from the web interface.
+    """
+
+    while True:
+        try:
+            symbol = 'EURUSD'
+            lot_size = 0.01
+            stop_loss = 100
+            take_profit = 150
+
+            # Get the latest historical data
+            latest_data = get_historical_data(symbol).iloc[-1:]
+
+            # Calculate indicators and detect patterns for the latest data
+            df = calculate_indicators_and_detect_patterns(latest_data)
+
+            # Generate trade signals for the latest data
+            df = generate_trade_signals(df)
+            print(df)
+            # Execute trades
+            for i in range(len(latest_data)):
+                signal = df['signal'].iloc[i]
+                if signal != 'None':
+                    print(df['signal'].array)
+                    execute_trade(signal, df, symbol, lot_size, stop_loss, take_profit)
+
+            # Visualize data
+            # plot_trade_signals(df)
+
+        except Exception as e:
+            print(f"Error running trading bot: {str(e)}")
+
+        # Wait for the next iteration
+        time.sleep(60)  # Adjust the time interval as needed
+
+# Start the Flask app
+if __name__ == '__main__':
+    app.run(debug=True)