from datetime import datetime
from typing import Optional

from sqlalchemy import Float, Integer, String, DateTime, JSON
from sqlalchemy.orm import Mapped, mapped_column

from app.core.database import Base


class BacktestResult(Base):
    __tablename__ = "backtest_results"

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    instrument: Mapped[str] = mapped_column(String(20))
    granularity: Mapped[str] = mapped_column(String(10))
    start_date: Mapped[datetime] = mapped_column(DateTime)
    end_date: Mapped[datetime] = mapped_column(DateTime)
    initial_balance: Mapped[float] = mapped_column(Float, default=10000.0)
    final_balance: Mapped[float] = mapped_column(Float)
    total_pnl: Mapped[float] = mapped_column(Float)
    total_trades: Mapped[int] = mapped_column(Integer)
    winning_trades: Mapped[int] = mapped_column(Integer)
    losing_trades: Mapped[int] = mapped_column(Integer)
    win_rate: Mapped[float] = mapped_column(Float)
    max_drawdown: Mapped[float] = mapped_column(Float)
    sharpe_ratio: Mapped[Optional[float]] = mapped_column(Float, nullable=True)
    expectancy: Mapped[float] = mapped_column(Float)
    # Courbe d'équité [{time, balance}] stockée en JSON
    equity_curve: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True)
    # Paramètres de la stratégie utilisés
    strategy_params: Mapped[Optional[dict]] = mapped_column(JSON, nullable=True)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)