from __future__ import annotations

import numpy as np
import pandas as pd  # type: ignore[import-untyped]


def sharpe_ratio(returns: pd.Series, periods_per_year: int = 8760, rf: float = 0.0) -> float:
    """Sharpe annualizzato. periods_per_year=8760 per dati orari."""
    excess = returns - rf / periods_per_year
    std = excess.std(ddof=1)
    if std == 0 or np.isnan(std):
        return 0.0
    return float(np.sqrt(periods_per_year) * excess.mean() / std)


def max_drawdown(equity: pd.Series) -> float:
    """Max drawdown percentuale (positivo)."""
    peak = equity.cummax()
    dd = (peak - equity) / peak.replace(0, np.nan)
    dd = dd.fillna(0.0)
    return float(dd.max())


def total_return(equity: pd.Series) -> float:
    if equity.iloc[0] == 0:
        return float(equity.iloc[-1])
    return float(equity.iloc[-1] / equity.iloc[0] - 1.0)