"""各实例当日平仓记录查询（供 hub_bridge /api/hub/trades/today 与中控 AI 聚合）。"""
from __future__ import annotations

from datetime import datetime, timedelta
from typing import Any, Callable, Optional

TRADE_COMPLETED_RESULTS = (
    "止盈",
    "止损",
    "保本止盈",
    "移动止盈",
    "手动平仓",
    "强制清仓",
    "外部平仓",
)


def trading_day_from_dt(dt: datetime, reset_hour: int = 8) -> str:
    """与实例 get_trading_day 一致：小时 < reset_hour 归属上一日历日。"""
    if dt.hour < reset_hour:
        dt = dt - timedelta(days=1)
    return dt.strftime("%Y-%m-%d")


def current_trading_day(*, now: datetime | None = None, reset_hour: int = 8) -> str:
    return trading_day_from_dt(now or datetime.now(), reset_hour)


def parse_dt_for_trading_day(raw: Any) -> datetime | None:
    if raw is None:
        return None
    s = str(raw).strip().replace("Z", "").replace("T", " ")
    if not s:
        return None
    for fmt, ln in (("%Y-%m-%d %H:%M:%S", 19), ("%Y-%m-%d %H:%M", 16), ("%Y-%m-%d", 10)):
        try:
            return datetime.strptime(s[:ln], fmt)
        except ValueError:
            continue
    return None


def trading_day_window_bounds(trading_day: str, reset_hour: int = 8) -> tuple[str, str]:
    """交易日 [reset_hour, 次日 reset_hour) 对应的北京时间字符串区间（闭区间）。"""
    day = datetime.strptime((trading_day or "").strip()[:10], "%Y-%m-%d")
    start = day.replace(hour=reset_hour, minute=0, second=0, microsecond=0)
    end = start + timedelta(days=1) - timedelta(seconds=1)
    return start.strftime("%Y-%m-%d %H:%M:%S"), end.strftime("%Y-%m-%d %H:%M:%S")


def _row_dict(row, row_to_dict: Optional[Callable] = None) -> dict:
    if row is None:
        return {}
    if row_to_dict:
        try:
            return dict(row_to_dict(row))
        except Exception:
            pass
    try:
        keys = row.keys() if hasattr(row, "keys") else ()
        if keys:
            return {k: row[k] for k in keys}
    except Exception:
        pass
    try:
        return dict(row)
    except Exception:
        return {}


def _effective_field(d: dict, reviewed_key: str, base_key: str, default: Any = None) -> Any:
    rv = d.get(reviewed_key)
    if rv is not None and str(rv).strip() != "":
        return rv
    bv = d.get(base_key)
    if bv is not None and str(bv).strip() != "":
        return bv
    return default


def _effective_pnl(d: dict) -> float:
    reviewed = d.get("reviewed_pnl_amount")
    if reviewed is not None and str(reviewed).strip() != "":
        try:
            return float(reviewed)
        except (TypeError, ValueError):
            pass
    ex = d.get("exchange_realized_pnl")
    if ex is not None and str(ex).strip() != "":
        try:
            return float(ex)
        except (TypeError, ValueError):
            pass
    try:
        return float(d.get("pnl_amount") or 0)
    except (TypeError, ValueError):
        return 0.0


def _trade_close_dt(d: dict) -> datetime | None:
    raw = _effective_field(d, "reviewed_closed_at", "closed_at")
    if raw is None or str(raw).strip() == "":
        raw = d.get("created_at") or d.get("opened_at")
    return parse_dt_for_trading_day(raw)


def _normalize_trade_row(
    d: dict,
    *,
    trading_day: str,
    reset_hour: int,
) -> dict[str, Any] | None:
    effective_result = str(_effective_field(d, "reviewed_result", "result") or "").strip()
    if effective_result not in TRADE_COMPLETED_RESULTS:
        return None
    close_dt = _trade_close_dt(d)
    if not close_dt:
        return None
    if trading_day_from_dt(close_dt, reset_hour) != trading_day:
        return None
    pnl = _effective_pnl(d)
    closed_at = _effective_field(d, "reviewed_closed_at", "closed_at")
    opened_at = _effective_field(d, "reviewed_opened_at", "opened_at")
    return {
        "symbol": d.get("symbol"),
        "direction": d.get("direction"),
        "result": effective_result,
        "pnl_amount": round(pnl, 4),
        "closed_at": closed_at,
        "opened_at": opened_at,
        "monitor_type": d.get("monitor_type"),
        "actual_rr": d.get("actual_rr"),
        "planned_rr": d.get("planned_rr"),
        "trade_style": d.get("trade_style"),
        "entry_reason": d.get("entry_reason"),
        "reviewed": bool(d.get("reviewed_at") or d.get("reviewed_result")),
    }


def fetch_trades_for_trading_day(
    conn,
    trading_day: str,
    *,
    row_to_dict_fn: Optional[Callable] = None,
    reset_hour: int = 8,
    limit: int = 200,
) -> list[dict[str, Any]]:
    """返回指定交易日的已平仓记录（与 /records 交易记录一致，复盘字段优先）。"""
    day = (trading_day or "").strip()[:10]
    if not day:
        return []
    lim = max(1, min(int(limit or 200), 500))
    start_bj, end_bj = trading_day_window_bounds(day, reset_hour)
    ts_expr = "REPLACE(COALESCE(reviewed_closed_at, closed_at, created_at, opened_at), 'T', ' ')"
    rows = conn.execute(
        f"""
        SELECT symbol, direction, result, reviewed_result, pnl_amount, reviewed_pnl_amount,
               exchange_realized_pnl, closed_at, reviewed_closed_at, opened_at, reviewed_opened_at,
               created_at, monitor_type, actual_rr, planned_rr, trade_style, entry_reason,
               reviewed_at
        FROM trade_records
        WHERE {ts_expr} >= ? AND {ts_expr} <= ?
        ORDER BY {ts_expr} ASC
        LIMIT ?
        """,
        (start_bj, end_bj, lim * 3),
    ).fetchall()
    out: list[dict[str, Any]] = []
    for row in rows:
        d = _row_dict(row, row_to_dict_fn)
        norm = _normalize_trade_row(d, trading_day=day, reset_hour=reset_hour)
        if norm:
            out.append(norm)
        if len(out) >= lim:
            break
    return out


def _normalize_archive_trade_row(
    d: dict,
    *,
    exchange_key: str = "",
    reset_hour: int = 8,
) -> dict[str, Any] | None:
    """全历史档案用：已平仓记录（不按交易日截断）。"""
    effective_result = str(_effective_field(d, "reviewed_result", "result") or "").strip()
    if effective_result not in TRADE_COMPLETED_RESULTS:
        return None
    close_dt = _trade_close_dt(d)
    if not close_dt:
        return None
    pnl = _effective_pnl(d)
    closed_at = _effective_field(d, "reviewed_closed_at", "closed_at")
    opened_at = _effective_field(d, "reviewed_opened_at", "opened_at")
    opened_ms = d.get("opened_at_ms")
    closed_ms = d.get("closed_at_ms")
    if opened_ms in (None, ""):
        odt = parse_dt_for_trading_day(opened_at)
        opened_ms = int(odt.timestamp() * 1000) if odt else None
    if closed_ms in (None, ""):
        cdt = close_dt
        closed_ms = int(cdt.timestamp() * 1000) if cdt else None
    try:
        trade_id = int(d.get("id"))
    except (TypeError, ValueError):
        return None
    return {
        "id": trade_id,
        "exchange_key": (exchange_key or "").strip().lower(),
        "symbol": (d.get("symbol") or "").strip().upper(),
        "direction": d.get("direction"),
        "result": effective_result,
        "pnl_amount": round(pnl, 4),
        "closed_at": closed_at,
        "opened_at": opened_at,
        "opened_at_ms": int(opened_ms) if opened_ms else None,
        "closed_at_ms": int(closed_ms) if closed_ms else None,
        "monitor_type": d.get("monitor_type"),
        "actual_rr": d.get("actual_rr"),
        "planned_rr": d.get("planned_rr"),
        "trade_style": d.get("trade_style"),
        "entry_reason": d.get("entry_reason"),
        "trigger_price": d.get("trigger_price"),
        "stop_loss": _effective_field(d, "reviewed_stop_loss", "stop_loss"),
        "take_profit": _effective_field(d, "reviewed_take_profit", "take_profit"),
        "reviewed": bool(d.get("reviewed_at") or d.get("reviewed_result")),
        "trading_day": trading_day_from_dt(close_dt, reset_hour),
    }


_SNAPSHOT_STATUS_TO_RESULT = {
    "stopped_sl": "止损",
    "stopped_tp": "止盈",
    "stopped_manual": "手动平仓",
    "stopped_external": "外部平仓",
}


def _table_columns(conn, table: str) -> set[str]:
    try:
        rows = conn.execute(f"PRAGMA table_info({table})").fetchall()
    except Exception:
        return set()
    out: set[str] = set()
    for r in rows:
        try:
            out.add(str(r[1]))
        except (IndexError, TypeError):
            try:
                out.add(str(r["name"]))
            except Exception:
                continue
    return out


def _archive_ts_expr(cols: set[str]) -> str:
    parts = [c for c in ("reviewed_closed_at", "closed_at", "created_at", "opened_at") if c in cols]
    if not parts:
        return "''"
    return f"REPLACE(COALESCE({', '.join(parts)}), 'T', ' ')"


def _archive_trade_select_sql(cols: set[str]) -> str:
    wanted = [
        "id",
        "symbol",
        "direction",
        "result",
        "reviewed_result",
        "pnl_amount",
        "reviewed_pnl_amount",
        "exchange_realized_pnl",
        "closed_at",
        "reviewed_closed_at",
        "opened_at",
        "reviewed_opened_at",
        "opened_at_ms",
        "closed_at_ms",
        "created_at",
        "monitor_type",
        "actual_rr",
        "planned_rr",
        "trade_style",
        "entry_reason",
        "trigger_price",
        "stop_loss",
        "take_profit",
        "reviewed_stop_loss",
        "reviewed_take_profit",
        "reviewed_at",
        "trend_plan_id",
    ]
    select_cols = [c for c in wanted if c in cols]
    if "id" not in select_cols:
        select_cols = ["id"] + select_cols
    return ", ".join(select_cols)


def _existing_trend_plan_ids(conn) -> set[int]:
    cols = _table_columns(conn, "trade_records")
    if "trend_plan_id" not in cols:
        return set()
    rows = conn.execute(
        "SELECT DISTINCT trend_plan_id FROM trade_records WHERE trend_plan_id IS NOT NULL"
    ).fetchall()
    out: set[int] = set()
    for row in rows:
        d = _row_dict(row)
        try:
            out.add(int(d.get("trend_plan_id")))
        except (TypeError, ValueError):
            continue
    return out


def _normalize_snapshot_archive_row(
    snap: dict,
    *,
    reset_hour: int = 8,
) -> dict[str, Any] | None:
    result = str(snap.get("result_label") or "").strip()
    if not result:
        result = _SNAPSHOT_STATUS_TO_RESULT.get(
            str(snap.get("status_at_close") or "").strip(), ""
        )
    if result not in TRADE_COMPLETED_RESULTS:
        return None
    closed_at = snap.get("closed_at")
    close_dt = parse_dt_for_trading_day(closed_at)
    if not close_dt:
        return None
    opened_at = snap.get("opened_at")
    opened_ms = _parse_ms_from_row(snap.get("opened_at"))
    closed_ms = _parse_ms_from_row(closed_at)
    try:
        snap_id = int(snap.get("id"))
    except (TypeError, ValueError):
        return None
    try:
        pnl = float(snap.get("pnl_amount") or 0)
    except (TypeError, ValueError):
        pnl = 0.0
    st = str(snap.get("strategy_type") or "").strip()
    monitor_type = "trend_pullback" if st == "trend_pullback" else ("roll" if st == "roll" else st)
    return {
        "id": -snap_id,
        "symbol": (snap.get("symbol") or "").strip().upper(),
        "direction": snap.get("direction"),
        "result": result,
        "pnl_amount": round(pnl, 4),
        "closed_at": closed_at,
        "opened_at": opened_at,
        "opened_at_ms": opened_ms,
        "closed_at_ms": closed_ms,
        "monitor_type": monitor_type,
        "entry_reason": "trend_pullback" if st == "trend_pullback" else monitor_type,
        "from_snapshot": True,
        "snapshot_id": snap_id,
        "trend_plan_id": snap.get("source_id"),
        "trading_day": trading_day_from_dt(close_dt, reset_hour),
    }


def _parse_ms_from_row(raw: Any) -> int | None:
    if raw in (None, ""):
        return None
    try:
        if isinstance(raw, (int, float)):
            v = int(raw)
            return v if v > 1_000_000_000_000 else v * 1000
    except (TypeError, ValueError):
        pass
    dt = parse_dt_for_trading_day(raw)
    return int(dt.timestamp() * 1000) if dt else None


def _fetch_strategy_snapshots_for_archive(
    conn,
    *,
    days: int = 365,
    reset_hour: int = 8,
    limit: int = 2000,
    skip_plan_ids: set[int] | None = None,
) -> list[dict[str, Any]]:
    cols = _table_columns(conn, "strategy_trade_snapshots")
    if not cols:
        return []
    lim = max(1, min(int(limit or 2000), 5000))
    day_span = max(1, min(int(days or 365), 3650))
    cutoff = datetime.now() - timedelta(days=day_span)
    cutoff_s = cutoff.strftime("%Y-%m-%d %H:%M:%S")
    ts_expr = "REPLACE(COALESCE(closed_at, opened_at, created_at), 'T', ' ')"
    rows = conn.execute(
        f"""
        SELECT * FROM strategy_trade_snapshots
        WHERE {ts_expr} >= ?
        ORDER BY {ts_expr} DESC
        LIMIT ?
        """,
        (cutoff_s, lim * 2),
    ).fetchall()
    skip = skip_plan_ids or set()
    out: list[dict[str, Any]] = []
    for row in rows:
        d = _row_dict(row)
        try:
            source_id = int(d.get("source_id") or 0)
        except (TypeError, ValueError):
            source_id = 0
        if source_id > 0 and source_id in skip:
            continue
        norm = _normalize_snapshot_archive_row(d, reset_hour=reset_hour)
        if norm:
            out.append(norm)
        if len(out) >= lim:
            break
    return out


def fetch_trades_for_archive(
    conn,
    *,
    days: int = 365,
    row_to_dict_fn: Optional[Callable] = None,
    reset_hour: int = 8,
    limit: int = 2000,
    include_strategy_snapshots: bool = True,
) -> list[dict[str, Any]]:
    """返回近 N 天已平仓记录（trade_records + 未落库的 strategy 快照）。"""
    lim = max(1, min(int(limit or 2000), 5000))
    day_span = max(1, min(int(days or 365), 3650))
    cutoff = datetime.now() - timedelta(days=day_span)
    cutoff_s = cutoff.strftime("%Y-%m-%d %H:%M:%S")
    cols = _table_columns(conn, "trade_records")
    if not cols:
        records: list[dict[str, Any]] = []
    else:
        ts_expr = _archive_ts_expr(cols)
        sql = f"""
            SELECT {_archive_trade_select_sql(cols)}
            FROM trade_records
            WHERE {ts_expr} >= ?
            ORDER BY {ts_expr} DESC
            LIMIT ?
        """
        rows = conn.execute(sql, (cutoff_s, lim * 2)).fetchall()
        records = []
        for row in rows:
            d = _row_dict(row, row_to_dict_fn)
            norm = _normalize_archive_trade_row(d, reset_hour=reset_hour)
            if norm:
                records.append(norm)
            if len(records) >= lim:
                break

    if not include_strategy_snapshots:
        return records

    skip_ids = _existing_trend_plan_ids(conn)
    for rec in records:
        try:
            pid = int(rec.get("trend_plan_id") or 0)
        except (TypeError, ValueError):
            pid = 0
        if pid > 0:
            skip_ids.add(pid)

    snaps = _fetch_strategy_snapshots_for_archive(
        conn,
        days=days,
        reset_hour=reset_hour,
        limit=max(0, lim - len(records)),
        skip_plan_ids=skip_ids,
    )
    merged = records + snaps
    merged.sort(
        key=lambda x: int(x.get("closed_at_ms") or 0),
        reverse=True,
    )
    return merged[:lim]


def summarize_trades(trades: list[dict]) -> dict[str, Any]:
    """单笔列表 → 笔数 / 盈亏 / 胜败统计。"""
    total_pnl = 0.0
    win = loss = flat = 0
    for t in trades or []:
        try:
            pnl = float(t.get("pnl_amount") or 0)
        except (TypeError, ValueError):
            pnl = 0.0
        total_pnl += pnl
        if pnl > 1e-9:
            win += 1
        elif pnl < -1e-9:
            loss += 1
        else:
            flat += 1
    return {
        "closed_count": len(trades or []),
        "win_count": win,
        "loss_count": loss,
        "flat_count": flat,
        "total_pnl_u": round(total_pnl, 4),
    }