"""Leaderboard stats: compare all users on overtime precision and directive compliance."""
from models import list_users
from stats import compute_all_stats, _compliance_over, _day_compliant
from calcul import minutes_to_hhmm


def compute_classement() -> list[dict]:
    """Return ranked list of users with their key metrics."""
    results = []

    for user_id in list_users():
        s = compute_all_stats(user_id)
        if not s["weekly_balances"] and s["n_jours"] == 0:
            continue  # skip empty accounts

        balances = [b["delta_min"] for b in s["weekly_balances"]]

        # Precision: % of weeks where |solde| ≤ 30 min (≈ at zero)
        if balances:
            pct_zero = round(100 * sum(1 for b in balances if abs(b) <= 30) / len(balances))
            mean_abs = round(sum(abs(b) for b in balances) / len(balances))
        else:
            pct_zero = None
            mean_abs = None

        conf_pct = s["comp_globale"]["pct"]

        # Combined score (SSO era: will weight per role/contract)
        score = round(
            (pct_zero or 0) * 0.6 + (conf_pct or 0) * 0.4
        )

        results.append({
            "user_id": user_id,
            "display_name": user_id.replace("_", " ").replace("-", " ").title(),
            "n_semaines": len(balances),
            "n_jours": s["n_jours"],
            "pct_zero": pct_zero,           # % weeks ≈ 0 HS — higher = better
            "mean_abs_min": mean_abs,        # mean abs(solde) in minutes — lower = better
            "mean_abs_str": minutes_to_hhmm(mean_abs) if mean_abs is not None else "—",
            "conf_pct": conf_pct,           # directive compliance % — higher = better
            "score": score,                  # combined 0-100 — higher = better
            "avg_delta": s["avg_delta"],
            "avg_delta_min": s["avg_delta_min"],
        })

    results.sort(key=lambda r: -r["score"])
    return results