"""中控统计汇总:KPI 对比 + 余额曲线."""
from __future__ import annotations

from typing import Any

from lib.bridge_client_lib import pull_all_enabled, pull_all_stats
from lib.cash_sample_lib import query_cash_series, record_cash_samples_from_overview


def _safe_float(v: Any) -> float | None:
    if v is None or v == "":
        return None
    try:
        return float(v)
    except (TypeError, ValueError):
        return None


def _safe_int(v: Any) -> int:
    try:
        return int(float(v))
    except (TypeError, ValueError):
        return 0


def normalize_window(raw: Any) -> str:
    w = str(raw or "7d").strip().lower()
    if w in ("1d", "day", "今日"):
        return "today"
    if w in ("7", "week"):
        return "7d"
    if w in ("30", "month"):
        return "30d"
    if w in ("0", "全部", "total"):
        return "all"
    return w if w in ("today", "7d", "30d", "all") else "7d"


def build_stats_summary(window: str = "7d") -> dict[str, Any]:
    w = normalize_window(window)
    # 实时状态(余额/权利金/浮盈)来自快照;窗口 KPI 来自各机 stats
    snaps = pull_all_enabled()
    try:
        record_cash_samples_from_overview(snaps)
    except Exception:
        pass
    stats_rows = pull_all_stats(w)
    stats_by_id = {r.get("id"): r for r in stats_rows}

    machines: list[dict[str, Any]] = []
    sum_cash = 0.0
    sum_premium = 0.0
    sum_unreal = 0.0
    sum_net = 0.0
    sum_profit = 0.0
    sum_loss = 0.0
    sum_closed = 0
    sum_wins = 0
    sum_losses = 0
    online_n = 0
    cash_known = False
    premium_known = False
    unreal_known = False

    for snap in snaps:
        iid = snap.get("id")
        st = stats_by_id.get(iid) or {}
        stats = st.get("stats") if isinstance(st.get("stats"), dict) else {}
        body = snap.get("snapshot") if isinstance(snap.get("snapshot"), dict) else {}
        premium = body.get("premium") if isinstance(body.get("premium"), dict) else {}
        pnl = body.get("pnl") if isinstance(body.get("pnl"), dict) else {}
        brief = body.get("positions_brief") if isinstance(body.get("positions_brief"), list) else []
        cash = _safe_float(premium.get("cash_usdt"))
        paid = _safe_float(premium.get("paid_usdt"))
        ratio = _safe_float(premium.get("ratio_pct"))
        unreal = _safe_float(pnl.get("unrealized_usdt"))
        net = _safe_float(stats.get("net_realized_pnl"))
        profit = _safe_float(stats.get("total_profit"))
        loss = _safe_float(stats.get("total_loss"))
        closed = _safe_int(stats.get("total_closed"))
        wins = _safe_int(stats.get("win_count"))
        losses = _safe_int(stats.get("loss_count"))
        win_rate = _safe_float(stats.get("win_rate"))
        avg_hold = _safe_float(stats.get("avg_hold_sec"))
        online = bool(snap.get("online"))
        if online:
            online_n += 1
        if cash is not None:
            sum_cash += cash
            cash_known = True
        if paid is not None:
            sum_premium += paid
            premium_known = True
        if unreal is not None:
            sum_unreal += unreal
            unreal_known = True
        if online and stats.get("ok"):
            if net is not None:
                sum_net += net
            if profit is not None:
                sum_profit += profit
            if loss is not None:
                sum_loss += loss
            sum_closed += closed
            sum_wins += wins
            sum_losses += losses
        machines.append(
            {
                "id": iid,
                "name": snap.get("name"),
                "online": online,
                "error": snap.get("error") or st.get("error") or "",
                "mode": ((body.get("instance") or {}) if isinstance(body.get("instance"), dict) else {}).get(
                    "mode"
                ),
                "cash_usdt": cash,
                "premium_usdt": paid,
                "ratio_pct": ratio,
                "unrealized_usdt": unreal,
                "pos_count": len(brief),
                "total_closed": closed if online and stats.get("ok") else None,
                "win_count": wins if online and stats.get("ok") else None,
                "loss_count": losses if online and stats.get("ok") else None,
                "win_rate": win_rate if online and stats.get("ok") else None,
                "net_realized_pnl": net if online and stats.get("ok") else None,
                "total_profit": profit if online and stats.get("ok") else None,
                "total_loss": loss if online and stats.get("ok") else None,
                "avg_hold_sec": avg_hold if online and stats.get("ok") else None,
                "stats_ok": bool(online and stats.get("ok")),
            }
        )

    agg_win_rate = round(sum_wins / sum_closed * 100, 2) if sum_closed else 0.0
    return {
        "ok": True,
        "window": w,
        "totals": {
            "online": online_n,
            "machines": len(machines),
            "cash_usdt": round(sum_cash, 4) if cash_known else None,
            "premium_usdt": round(sum_premium, 4) if premium_known else None,
            "unrealized_usdt": round(sum_unreal, 4) if unreal_known else None,
            "net_realized_pnl": round(sum_net, 4),
            "total_profit": round(sum_profit, 4),
            "total_loss": round(sum_loss, 4),
            "total_closed": sum_closed,
            "win_count": sum_wins,
            "loss_count": sum_losses,
            "win_rate": agg_win_rate,
        },
        "machines": machines,
    }


def build_stats_curve(range_key: str = "7d") -> dict[str, Any]:
    # 顺手采一笔,让打开页面时也有点
    try:
        snaps = pull_all_enabled()
        record_cash_samples_from_overview(snaps)
    except Exception:
        pass
    data = query_cash_series(range_key=range_key)
    data["ok"] = True
    return data