Update utils/forex_signals.py

utils/forex_signals.py

@@ -1,49 +1,45 @@
 import random
-from datetime import datetime, timedelta
-
-# Generate forex signals with new logic
-def generate_forex_signals(trading_capital, market_risk, user_timezone, leverage, stop_loss_percentage, take_profit_percentage):
-    # Example list of currency pairs (add 10 more pairs here)
-    currency_pairs = ["EUR/USD", "USD/JPY", "GBP/USD", "AUD/USD", "USD/CAD", "USD/CHF", 
-                      "NZD/USD", "EUR/GBP", "GBP/JPY", "EUR/JPY", "AUD/JPY", "EUR/AUD", 
-                      "GBP/CAD", "USD/ZAR", "EUR/CHF", "GBP/NZD"]
-
-    # Simulating generated signals
+from datetime import datetime
+
+# Function to generate Forex signals
+def generate_forex_signals(trading_capital, market_risk, user_timezone, additional_pairs=None):
+    """
+    Generates trading signals for the forex market.
+    :param trading_capital: The amount of capital the user has for trading.
+    :param market_risk: The risk level selected by the user (Low, Medium, High).
+    :param user_timezone: The user's timezone.
+    :param additional_pairs: List of additional currency pairs to consider (optional).
+    :return: Dictionary of forex signals with relevant details.
+    """
+    
+    # Default list of currency pairs
+    default_pairs = [
+        "EUR/USD", "GBP/USD", "USD/JPY", "AUD/USD", "USD/CHF", 
+        "USD/CAD", "NZD/USD", "EUR/GBP", "EUR/JPY", "GBP/JPY"
+    ]
+    
+    # Add additional pairs if provided
+    if additional_pairs:
+        all_pairs = default_pairs + additional_pairs
+    else:
+        all_pairs = default_pairs
+    
+    # Example of generating signals (simplified logic for demo purposes)
     signals = []
-    for pair in currency_pairs:
-        # Randomized data for demonstration purposes
-        entry_price = random.uniform(1.1, 1.5)  # Entry price
-        exit_price = random.uniform(1.1, 1.5)  # Exit price
-        signal_strength = random.uniform(0.7, 1.0)  # Signal strength (0 to 1)
-        trade_duration = timedelta(minutes=random.randint(15, 120))  # Trade duration in minutes
-
-        # Calculate ROI with leverage
-        roi = ((exit_price - entry_price) / entry_price) * leverage * 100
-
-        # Calculate stop loss and take profit
-        stop_loss = entry_price * (1 - (stop_loss_percentage / 100))
-        take_profit = entry_price * (1 + (take_profit_percentage / 100))
-
-        # Generate signal dictionary
+    for pair in all_pairs:
         signal = {
             "currency_pair": pair,
-            "entry_time": (datetime.now() + trade_duration).strftime("%Y-%m-%d %H:%M:%S"),
-            "exit_time": (datetime.now() + trade_duration).strftime("%Y-%m-%d %H:%M:%S"),
-            "roi": round(roi, 2),
-            "signal_strength": round(signal_strength * 100, 2),
-            "stop_loss": round(stop_loss, 5),
-            "take_profit": round(take_profit, 5)
+            "entry_time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+            "exit_time": (datetime.now().strftime("%Y-%m-%d %H:%M:%S")),  # Simplified; should be dynamic
+            "roi": random.uniform(5, 15),  # Random ROI for demonstration
+            "signal_strength": random.uniform(50, 100)  # Random signal strength for demo
         }
-
         signals.append(signal)
-
-    # Sort signals by ROI in descending order
-    signals = sorted(signals, key=lambda x: x["roi"], reverse=True)
-
-    # Best signal is the one with the highest ROI
-    best_signal = signals[0] if signals else None
+    
+    # Determine the best signal based on ROI (just a simplified example)
+    best_signal = max(signals, key=lambda x: x["roi"])
 
     return {
-        "all_signals": signals,
-        "best_signal": best_signal
+        "best_signal": best_signal,
+        "all_signals": signals
     }