100 lines
3.5 KiB
Python
100 lines
3.5 KiB
Python
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"""
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SQLAlchemy database models and session management for backtest run persistence.
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"""
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import json
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from datetime import datetime, timezone
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from pathlib import Path
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from sqlalchemy import JSON, Column, DateTime, Float, Integer, String, Text, create_engine
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from sqlalchemy.orm import DeclarativeBase, Session, sessionmaker
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# Database file location
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DB_PATH = Path(__file__).parent.parent.parent / "data" / "backtest_runs.db"
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DATABASE_URL = f"sqlite:///{DB_PATH}"
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engine = create_engine(DATABASE_URL, connect_args={"check_same_thread": False})
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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class Base(DeclarativeBase):
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"""Base class for SQLAlchemy models."""
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pass
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class BacktestRun(Base):
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"""
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Persisted backtest run record.
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Stores all information needed to display and compare runs.
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"""
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__tablename__ = "backtest_runs"
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id = Column(Integer, primary_key=True, autoincrement=True)
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run_id = Column(String(36), unique=True, nullable=False, index=True)
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# Configuration
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strategy = Column(String(50), nullable=False, index=True)
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symbol = Column(String(20), nullable=False, index=True)
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exchange = Column(String(20), nullable=False, default="okx")
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market_type = Column(String(20), nullable=False)
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timeframe = Column(String(10), nullable=False)
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leverage = Column(Integer, nullable=False, default=1)
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params = Column(JSON, nullable=False, default=dict)
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# Date range
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start_date = Column(String(20), nullable=True)
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end_date = Column(String(20), nullable=True)
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# Metrics (denormalized for quick listing)
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total_return = Column(Float, nullable=False)
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benchmark_return = Column(Float, nullable=False, default=0.0)
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alpha = Column(Float, nullable=False, default=0.0)
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sharpe_ratio = Column(Float, nullable=False)
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max_drawdown = Column(Float, nullable=False)
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win_rate = Column(Float, nullable=False)
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total_trades = Column(Integer, nullable=False)
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profit_factor = Column(Float, nullable=True)
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total_fees = Column(Float, nullable=False, default=0.0)
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total_funding = Column(Float, nullable=False, default=0.0)
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liquidation_count = Column(Integer, nullable=False, default=0)
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liquidation_loss = Column(Float, nullable=False, default=0.0)
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adjusted_return = Column(Float, nullable=True)
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# Full data (JSON serialized)
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equity_curve = Column(Text, nullable=False) # JSON array
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trades = Column(Text, nullable=False) # JSON array
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# Metadata
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created_at = Column(DateTime, nullable=False, default=lambda: datetime.now(timezone.utc))
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def set_equity_curve(self, data: list[dict]):
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"""Serialize equity curve to JSON string."""
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self.equity_curve = json.dumps(data)
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def get_equity_curve(self) -> list[dict]:
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"""Deserialize equity curve from JSON string."""
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return json.loads(self.equity_curve) if self.equity_curve else []
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def set_trades(self, data: list[dict]):
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"""Serialize trades to JSON string."""
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self.trades = json.dumps(data)
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def get_trades(self) -> list[dict]:
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"""Deserialize trades from JSON string."""
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return json.loads(self.trades) if self.trades else []
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def init_db():
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"""Create database tables if they don't exist."""
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DB_PATH.parent.mkdir(parents=True, exist_ok=True)
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Base.metadata.create_all(bind=engine)
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def get_db() -> Session:
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"""Get database session (dependency injection)."""
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close()
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