Remove deprecated modules and files related to the backtesting framework, including backtest.py, cli.py, config.py, data.py, intrabar.py, logging_utils.py, market_costs.py, metrics.py, trade.py, and supertrend indicators. Introduce a new structure for the backtesting engine with improved organization and functionality, including a CLI handler, data manager, and reporting capabilities. Update dependencies in pyproject.toml to support the new architecture.

strategies/base.py

@@ -0,0 +1,80 @@
+"""
+Base strategy class for all trading strategies.
+
+Strategies should inherit from BaseStrategy and implement the run() method.
+"""
+from abc import ABC, abstractmethod
+
+import pandas as pd
+
+from engine.market import MarketType
+
+
+class BaseStrategy(ABC):
+    """
+    Abstract base class for trading strategies.
+    
+    Class Attributes:
+        default_market_type: Default market type for this strategy
+        default_leverage: Default leverage (only applies to perpetuals)
+        default_sl_stop: Default stop-loss percentage
+        default_tp_stop: Default take-profit percentage
+        default_sl_trail: Whether stop-loss is trailing by default
+    """
+    # Market configuration defaults
+    default_market_type: MarketType = MarketType.SPOT
+    default_leverage: int = 1
+    
+    # Risk management defaults (can be overridden per strategy)
+    default_sl_stop: float | None = None
+    default_tp_stop: float | None = None
+    default_sl_trail: bool = False
+    
+    def __init__(self, **kwargs):
+        self.params = kwargs
+
+    @abstractmethod
+    def run(
+        self, 
+        close: pd.Series, 
+        **kwargs
+    ) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame]:
+        """
+        Run the strategy logic.
+        
+        Args:
+            close: Price series (can be multiple columns for grid search)
+            **kwargs: Additional data (high, low, open, volume) and parameters
+            
+        Returns:
+            Tuple of 4 DataFrames/Series:
+                - long_entries: Boolean signals to open long positions
+                - long_exits: Boolean signals to close long positions
+                - short_entries: Boolean signals to open short positions
+                - short_exits: Boolean signals to close short positions
+                
+        Note:
+            For spot markets, short signals will be ignored.
+            For backward compatibility, strategies can return 2-tuple (entries, exits)
+            which will be interpreted as long-only signals.
+        """
+        pass
+
+    def get_indicator(self, ind_cls, *args, **kwargs):
+        """Helper to run a vectorbt indicator."""
+        return ind_cls.run(*args, **kwargs)
+    
+    @staticmethod
+    def create_empty_signals(reference: pd.Series | pd.DataFrame) -> pd.DataFrame:
+        """
+        Create an empty (all False) signal DataFrame matching the reference shape.
+        
+        Args:
+            reference: Series or DataFrame to match shape/index
+            
+        Returns:
+            DataFrame of False values with same shape as reference
+        """
+        if isinstance(reference, pd.DataFrame):
+            return pd.DataFrame(False, index=reference.index, columns=reference.columns)
+        return pd.Series(False, index=reference.index)