from datetime import datetime
from sqlalchemy import Column, Integer, String, Float, DateTime, Enum
import enum
from app.database import Base


class PeriodType(str, enum.Enum):
    DAILY = "DAILY"
    WEEKLY = "WEEKLY"
    MONTHLY = "MONTHLY"


class PerformanceLog(Base):
    __tablename__ = "performance_logs"

    id = Column(Integer, primary_key=True, index=True, autoincrement=True)
    period_type = Column(Enum(PeriodType), nullable=False)
    period_start = Column(DateTime, nullable=False)
    period_end = Column(DateTime, nullable=False)
    total_trades = Column(Integer, nullable=False, default=0)
    win_rate = Column(Float, nullable=True)
    total_pnl = Column(Float, nullable=True)
    max_drawdown = Column(Float, nullable=True)
    sharpe_ratio = Column(Float, nullable=True)
    profit_factor = Column(Float, nullable=True)
    expectancy = Column(Float, nullable=True)
    # Optional filters: per pair or per strategy
    pair = Column(String(20), nullable=True)
    strategy_name = Column(String(100), nullable=True)
    created_at = Column(DateTime, nullable=False, default=datetime.utcnow)

    def to_dict(self) -> dict:
        return {
            "id": self.id,
            "period_type": self.period_type,
            "period_start": self.period_start.isoformat() if self.period_start else None,
            "period_end": self.period_end.isoformat() if self.period_end else None,
            "total_trades": self.total_trades,
            "win_rate": self.win_rate,
            "total_pnl": self.total_pnl,
            "max_drawdown": self.max_drawdown,
            "sharpe_ratio": self.sharpe_ratio,
            "profit_factor": self.profit_factor,
            "expectancy": self.expectancy,
            "pair": self.pair,
            "strategy_name": self.strategy_name,
        }