diff --git a/src/screener/t_sunnyband.py b/src/screener/t_sunnyband.py index a21f3ff..becde63 100644 --- a/src/screener/t_sunnyband.py +++ b/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 diff --git a/src/utils/data_utils.py b/src/utils/data_utils.py index 53f9faf..dc505ff 100644 --- a/src/utils/data_utils.py +++ b/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