refactor: Move process_signal_data from data_utils to scanner_utils and update imports

src/screener/t_sunnyband.py

@@ -3,9 +3,9 @@ from datetime import datetime, timedelta
 from db.db_connection import create_client
 from utils.data_utils import (
     get_stock_data, validate_signal_date, print_signal, 
-    save_signals_to_csv, get_qualified_stocks,
-    initialize_scanner, process_signal_data
+    save_signals_to_csv, get_qualified_stocks
 )
+from utils.scanner_utils import initialize_scanner, process_signal_data
 from indicators.sunny_bands import SunnyBands
 from trading.position_calculator import PositionCalculator
 from screener.user_input import get_interval_choice, get_date_range

src/utils/data_utils.py

@@ -100,42 +100,3 @@ def save_signals_to_csv(signals: list, scanner_name: str) -> None:
     print(f"\nSaved {len(signals)} signals to {output_file}")
 
 
-def process_signal_data(ticker: str, signal_data: dict, current_volume: int, 
-                       last_update: int, stock_type: str, calculator: PositionCalculator = None) -> dict:
-    """
-    Process and format signal data consistently
-    
-    Args:
-        ticker (str): Stock ticker
-        signal_data (dict): Raw signal data
-        current_volume (int): Current trading volume
-        last_update (int): Last update timestamp
-        stock_type (str): Stock type/label
-        calculator (PositionCalculator, optional): Position calculator instance
-        
-    Returns:
-        dict: Processed signal data
-    """
-    entry_data = {
-        'ticker': ticker,
-        'entry_price': signal_data['price'],
-        'target_price': signal_data.get('ema', signal_data.get('upper_band')),  # Handle both ATR and Sunny
-        'volume': current_volume,
-        'signal_date': signal_data.get('date', datetime.now()),
-        'stock_type': stock_type,
-        'last_update': datetime.fromtimestamp(last_update/1000000000)
-    }
-    
-    if calculator:
-        position = calculator.calculate_position_size(entry_data['entry_price'])
-        potential_profit = (entry_data['target_price'] - entry_data['entry_price']) * position['shares']
-        entry_data.update({
-            'shares': position['shares'],
-            'position_size': position['position_value'],
-            'stop_loss': position['stop_loss'],
-            'risk_amount': position['potential_loss'],
-            'profit_amount': potential_profit,
-            'risk_reward_ratio': abs(potential_profit / position['potential_loss']) if position['potential_loss'] != 0 else 0
-        })
-    
-    return entry_data