Made improvements to overall functionality

main.py

@@ -7,28 +7,32 @@ Author: Mike Kiwalabye
 """
 
 import time
-from flask import Flask, render_template, request, redirect, globals
+from flask import Flask, render_template, request, redirect, json, Response
 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
+import threading
+import pandas as pd
 
 app = Flask(__name__)
 
 # Define input shape for the neural network
-input_shape = (10,)  # Adjust the input shape based on your features and data
+input_shape = (11,)  # 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
+mt5_initialized = False
+latest_trade_signals = []
+
 
 # Web Interface Routes
 
 @app.route('/')
 def index():
-    """Render the main page with login form."""
+    """Render the main page with the login form."""
     return render_template('index.html')
 
 @app.route('/login', methods=['POST'])
@@ -41,6 +45,7 @@ def login():
     Returns:
     - str: HTML response.
     """
+    global mt5_initialized
     if request.method == 'POST':
         credentials = {
             'username': request.form['username'],
@@ -50,7 +55,7 @@ def login():
         }
         if mt5_connector.connect_to_mt5(credentials):
             # Set MT5 initialization state to True
-            globals.mt5_initialized = True
+            mt5_initialized = True
             # Redirect to the main dashboard or another page
             return redirect('/dashboard')
         else:
@@ -73,45 +78,68 @@ def dashboard():
 def start_ml_bot():
     """
     Handle the request to start the ML bot.
-
     """
-
     # Start the ML bot
-    run_trading_bot_web_interface()
+    threading.Thread(target=run_trading_bot_web_interface).start()
+
+    # Return an empty response
+    return Response(status=200)
 
 
-# Main Trading Bot Logic
+@app.route("/stop_ml_bot", methods=['GET'])
+def stop_ml_bot():
+    mt5_connector.stop_mt5_ml_bot()
+    redirect('/dashboard')
+
+def map_signal_priority(signal_priority):
+    # Define a mapping for string values to integers
+    signal_mapping = {
+        'Both': 1,
+        'Pattern': 2,
+        'RSI': 3
+        # Add more mappings as needed
+    }
+
+    # Use the mapping, default to 0 if not found
+    return signal_mapping.get(signal_priority, 0)
+# Main Trading Bot Logic 
 
 def run_trading_bot_web_interface():
     """
     Run the trading bot using MetaTrader 5 credentials from the web interface.
     """
-
+    global latest_trade_signals
+    historical_data_df = pd.DataFrame()
+    
     while True:
         try:
             symbol = 'EURUSD'
             lot_size = 0.01
             stop_loss = 100
-            take_profit = 150
+            take_profit = 200
 
             # Get the latest historical data
-            latest_data = get_historical_data(symbol).iloc[-1:]
+            historical_data_df = get_historical_data(symbol, historical_data_df)
 
             # Calculate indicators and detect patterns for the latest data
-            df = calculate_indicators_and_detect_patterns(latest_data)
+            df = calculate_indicators_and_detect_patterns(historical_data_df)
 
             # 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)
+            df.to_csv('your_file.csv', sep='\t', index=False)
 
-            # Visualize data
-            # plot_trade_signals(df)
+            # Inside the run_trading_bot_web_interface function
+            latest_trade_signals = df.replace({pd.NA: 'null'}).to_json(orient='records')
+
+
+            # Execute trades
+            for i in range(len(df)):
+                
+                signal_priority = df['signal'].iloc[i]  # Replace with your actual value
+                mapped_priority = map_signal_priority(signal_priority)
+
+                if mapped_priority != 0:
+                    execute_trade(mapped_priority, df, symbol, lot_size, stop_loss, take_profit)
 
         except Exception as e:
             print(f"Error running trading bot: {str(e)}")
@@ -119,6 +147,11 @@ def run_trading_bot_web_interface():
         # Wait for the next iteration
         time.sleep(60)  # Adjust the time interval as needed
 
+@app.route('/get_latest_trade_signals', methods=['GET'])
+def get_latest_trade_signals():
+    global latest_trade_signals
+    return json.dumps(latest_trade_signals)
+
 # Start the Flask app
 if __name__ == '__main__':
     app.run(debug=True)