new strategies

strategies/base_strategy.py

@@ -6,13 +6,16 @@ import logging
 from datetime import datetime, timezone
 import sqlite3
 
+from logging_utils import setup_logging
+
 class BaseStrategy(ABC):
     """
     An abstract base class that defines the blueprint for all trading strategies.
-    It provides common functionality like loading data and saving status.
+    It provides common functionality like loading data, saving status, and state management.
     """
     
-    def __init__(self, strategy_name: str, params: dict, log_level: str):
+    def __init__(self, strategy_name: str, params: dict):
+        # Note: log_level is not needed here as logging is set up by the process
         self.strategy_name = strategy_name
         self.params = params
         self.coin = params.get("coin", "N/A")
@@ -20,21 +23,17 @@ class BaseStrategy(ABC):
         self.db_path = os.path.join("_data", "market_data.db")
         self.status_file_path = os.path.join("_data", f"strategy_status_{self.strategy_name}.json")
         
-        # --- ADDED: State variables required for status reporting ---
         self.current_signal = "INIT"
         self.last_signal_change_utc = None
         self.signal_price = None
 
-        # This will be set up by the child class after it's initialized
-        # setup_logging(log_level, f"Strategy-{self.strategy_name}")
-        # logging.info(f"Initializing with parameters: {self.params}")
+        logging.info(f"Initializing with parameters: {self.params}")
 
     def load_data(self) -> pd.DataFrame:
         """Loads historical data for the configured coin and timeframe."""
         table_name = f"{self.coin}_{self.timeframe}"
         
-        # Dynamically determine the number of candles needed based on all possible period parameters
-        periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' in k]
+        periods = [v for k, v in self.params.items() if 'period' in k or '_ma' in k or 'slow' in k or 'fast' in k]
         limit = max(periods) + 50 if periods else 500
 
         try:
@@ -51,10 +50,30 @@ class BaseStrategy(ABC):
 
     @abstractmethod
     def calculate_signals(self, df: pd.DataFrame) -> pd.DataFrame:
-        """
-        The core logic of the strategy. Must be implemented by child classes.
-        """
+        """The core logic of the strategy. Must be implemented by child classes."""
         pass
+        
+    def calculate_signals_and_state(self, df: pd.DataFrame):
+        """
+        A wrapper that calls the strategy's signal calculation and then
+        determines the last signal change from the historical data.
+        """
+        df_with_signals = self.calculate_signals(df)
+        df_with_signals.dropna(inplace=True)
+        if df_with_signals.empty: return
+
+        df_with_signals['position_change'] = df_with_signals['signal'].diff()
+        
+        last_signal = df_with_signals['signal'].iloc[-1]
+        if last_signal == 1: self.current_signal = "BUY"
+        elif last_signal == -1: self.current_signal = "SELL"
+        else: self.current_signal = "HOLD"
+        
+        last_change_series = df_with_signals[df_with_signals['position_change'] != 0]
+        if not last_change_series.empty:
+            last_change_row = last_change_series.iloc[-1]
+            self.last_signal_change_utc = last_change_row.name.tz_localize('UTC').isoformat()
+            self.signal_price = last_change_row['close']
 
     def _save_status(self):
         """Saves the current strategy state to its JSON file."""