fetch data bug fix for both index and DVA/DCA calculation

app.py

@@ -62,54 +62,41 @@ def run_sync():
 @app.route('/api/backtest', methods=['POST'])
 def api_backtest():
     data = request.get_json() or {}
-    
-    # 1. Extract and Sanitize Symbol
     symbol = data.get('symbol', '').strip().upper()
-    print(f"DEBUG: Processing {symbol} with payload: {data}")
-
+    engine = DataEngine(symbol=symbol)
+    
     if not symbol:
         return jsonify({"error": "Symbol is required"}), 400
 
     try:
-        # 2. Extract and Cast Inputs (Ensuring types match engine requirements)
-        # Note: JS uses 'startDate' (camelCase), Python often uses 'start_date'
-        initial = float(data.get('initial_inv', 0))
-        monthly = float(data.get('monthly_target', 0))
-        start_date = data.get('startDate') or data.get('start_date', '2024-01-01')
-        frequency = data.get('frequency', 'Monthly')
-        
-        # Robust Boolean Check
-        allow_sell = data.get('allow_sell') is True
-        allow_frac = data.get('allow_fractional') is True
-
-        # 3. Initialize Engines
+        # 1. Initialize the Engine 
+        # (The Engine's __init__ should handle looking up the URL in instruments.csv)
         data_eng = DataEngine(symbol=symbol)
         
-        # Verify file exists after DataEngine logic
-        if not os.path.exists(data_eng.file_path):
-            return jsonify({"error": f"Data for {symbol} could not be retrieved."}), 404
-            
-        strat_eng = StrategyEngine(data_eng)
+        # 2. Trigger Smart Fetch 
+        # (Inside engine.py, this checks the 24h clock and updates if needed)
+        data_eng.fetch_data() 
         
-        # 4. Calculation - Calling the correctly named method 'run_simulation'
-        # Ensure arguments match the signature in your engine.py
+        # 3. Verify data exists before proceeding
+        if not os.path.exists(data_eng.file_path):
+            return jsonify({"error": f"No data found for {symbol}"}), 404
+            
+        # 4. Run Strategy
+        strat_eng = StrategyEngine(data_eng)
         history = strat_eng.run_simulation(
-            start_date=start_date,
-            monthly_goal=monthly,
-            initial_inv=initial,
-            frequency=frequency,
-            allow_sell=allow_sell,
-            allow_fractional=allow_frac
+            start_date=data.get('startDate', '2024-01-01'),
+            monthly_goal=float(data.get('monthly_target', 0)),
+            initial_inv=float(data.get('initial_inv', 0)),
+            frequency=data.get('frequency', 'Monthly'),
+            allow_sell=data.get('allow_sell') is True,
+            allow_fractional=data.get('allow_fractional') is True
         )
 
         return jsonify(history)
 
     except Exception as e:
-        import traceback
-        print("CRITICAL ERROR in /api/backtest:")
-        print(traceback.format_exc()) 
-        # Returning the actual error message helps debugging the '500' faster
-        return jsonify({"error": str(e)}), 500
+        app.logger.error(f"Backtest Error: {str(e)}")
+        return jsonify({"error": "Internal server error"}), 500
 
 @app.route('/backtest') # This is the URL you will actually visit
 def backtest_ui():