"""ORM 模型。

Candle 表设计与 TimescaleDB hypertable 完全兼容：将来在目标 PG 库执行
  SELECT create_hypertable('candles', 'ts');
即可升级为时序表 + Continuous Aggregates 多周期预聚合，无需改表结构。
"""
from datetime import datetime

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

from .db import Base


def _utcnow() -> datetime:
    # naive UTC，避免 SQLite 存储时区带来的麻烦
    from datetime import timezone
    return datetime.now(timezone.utc).replace(tzinfo=None)


class Candle(Base):
    __tablename__ = "candles"

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    symbol: Mapped[str] = mapped_column(String(16), index=True)
    timeframe: Mapped[str] = mapped_column(String(4), default="1d", index=True)
    ts: Mapped[datetime] = mapped_column(DateTime, index=True)  # bar 开始时间
    open: Mapped[float] = mapped_column(Float)
    high: Mapped[float] = mapped_column(Float)
    low: Mapped[float] = mapped_column(Float)
    close: Mapped[float] = mapped_column(Float)
    volume: Mapped[float] = mapped_column(Float)

    __table_args__ = (
        UniqueConstraint("symbol", "timeframe", "ts", name="uq_candle_sym_tf_ts"),
    )


class BacktestRun(Base):
    """回测运行注册表（可复现/可审计/可回归对比的基础）。

    完整版应记录 策略版本 + 参数快照 + 数据快照（复权/数据源/库版本）+ 环境指纹 + 结果指纹。
    MVP 先落关键字段，结构就位。
    """
    __tablename__ = "backtest_runs"

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    created_at: Mapped[datetime] = mapped_column(DateTime, default=_utcnow)
    symbol: Mapped[str] = mapped_column(String(16))
    strategy: Mapped[str] = mapped_column(String(64))
    timeframe: Mapped[str] = mapped_column(String(4), default="1d")
    params_json: Mapped[str] = mapped_column(String, default="{}")
    initial_cash: Mapped[float] = mapped_column(Float, default=100000.0)
    total_return: Mapped[float] = mapped_column(Float, default=0.0)
    max_drawdown: Mapped[float] = mapped_column(Float, default=0.0)
    sharpe: Mapped[float] = mapped_column(Float, default=0.0)
    num_trades: Mapped[int] = mapped_column(Integer, default=0)