refactor: Consolidate initialize_scanner function and remove duplicate

src/utils/data_utils.py

@@ -5,6 +5,7 @@ from datetime import datetime, timedelta
 from db.db_connection import create_client
 from screener.user_input import get_interval_choice, get_date_range
 from trading.position_calculator import PositionCalculator
+from utils.scanner_utils import initialize_scanner
 
 from typing import Optional
 
@@ -203,42 +204,6 @@ def save_signals_to_csv(signals: list, scanner_name: str) -> None:
     df_signals.to_csv(output_file, index=False)
     print(f"\nSaved {len(signals)} signals to {output_file}")
 
-def initialize_scanner(min_price: float, max_price: float, min_volume: int, portfolio_size: float = None) -> tuple:
-    """
-    Initialize common scanner components
-    
-    Args:
-        min_price (float): Minimum stock price
-        max_price (float): Maximum stock price
-        min_volume (int): Minimum trading volume
-        portfolio_size (float, optional): Portfolio size for position sizing
-        
-    Returns:
-        tuple: (interval, start_date, end_date, qualified_stocks, calculator)
-    """
-    print(f"\nScanning for stocks ${min_price:.2f}-${max_price:.2f} with min volume {min_volume:,}")
-    
-    interval = get_interval_choice()
-    start_date, end_date = get_date_range()
-    
-    qualified_stocks = get_qualified_stocks(start_date, end_date, min_price, max_price, min_volume)
-    
-    if not qualified_stocks:
-        print("No stocks found matching criteria.")
-        return None, None, None, None, None
-
-    print(f"\nFound {len(qualified_stocks)} stocks matching criteria")
-    
-    # Initialize position calculator if portfolio size provided
-    calculator = None
-    if portfolio_size and portfolio_size > 0:
-        calculator = PositionCalculator(
-            account_size=portfolio_size,
-            risk_percentage=1.0,
-            stop_loss_percentage=7.0
-        )
-        
-    return interval, start_date, end_date, qualified_stocks, calculator
 
 def process_signal_data(ticker: str, signal_data: dict, current_volume: int, 
                        last_update: int, stock_type: str, calculator: PositionCalculator = None) -> dict: