# Copyright (c) 2025-2026 马建军. All rights reserved.
# 专有软件 — 未经授权禁止复制、传播、转售。
# 严禁用于：带单/代客理财、向他人推荐期货品种或买卖建议、融资配资等业务。
# 详见 LICENSE.zh-CN.txt 与 docs/软件购买与使用协议.md

"""交易记录：字段补全、资金曲线数据。"""
from __future__ import annotations

from typing import Any


TRADE_LOG_EXTRA_COLUMNS = (
    "ALTER TABLE trade_logs ADD COLUMN margin_pct REAL",
    "ALTER TABLE trade_logs ADD COLUMN equity_after REAL",
    "ALTER TABLE trade_logs ADD COLUMN source TEXT DEFAULT 'local'",
    "ALTER TABLE trade_logs ADD COLUMN ctp_trade_key TEXT",
)


def ensure_trade_log_columns(conn) -> None:
    for sql in TRADE_LOG_EXTRA_COLUMNS:
        try:
            conn.execute(sql)
        except Exception:
            pass


def calc_equity_after(capital: float, pnl_net: float) -> float | None:
    cap = float(capital or 0)
    if cap <= 0:
        return None
    return round(cap + float(pnl_net or 0), 2)


def _norm_symbol(symbol: str) -> str:
    return (symbol or "").split(".")[0].strip().lower()


def _norm_close_minute(ts: str) -> str:
    """统一 close_time 到分钟粒度，兼容 ISO `T` 与空格分隔。"""
    return (ts or "").strip().replace("T", " ")[:16]


def purge_duplicate_local_trade_logs(conn) -> int:
    """删除已被 CTP 柜台记录覆盖的本地重复成交。"""
    removed = 0
    ctp_rows = [
        dict(r)
        for r in conn.execute("SELECT * FROM trade_logs WHERE source='ctp'").fetchall()
    ]
    local_rows = [
        dict(r)
        for r in conn.execute(
            """SELECT * FROM trade_logs
               WHERE COALESCE(source, 'local') != 'ctp'
                 AND (ctp_trade_key IS NULL OR ctp_trade_key = '')"""
        ).fetchall()
    ]
    for ctp in ctp_rows:
        ct16 = _norm_close_minute(ctp.get("close_time") or "")
        sym_n = _norm_symbol(ctp.get("symbol") or "")
        lots = float(ctp.get("lots") or 0)
        direction = (ctp.get("direction") or "long").strip().lower()
        for loc in local_rows:
            if loc.get("id") == ctp.get("id"):
                continue
            if _norm_symbol(loc.get("symbol") or "") != sym_n:
                continue
            if (loc.get("direction") or "long").strip().lower() != direction:
                continue
            if _norm_close_minute(loc.get("close_time") or "") != ct16:
                continue
            if abs(float(loc.get("lots") or 0) - lots) > 0.01:
                continue
            conn.execute("DELETE FROM trade_logs WHERE id=?", (loc["id"],))
            removed += 1
    return removed


def _attach_symbol_meta(t: dict[str, Any]) -> None:
    try:
        from symbols import position_symbol_meta

        sym = (t.get("symbol") or "").strip()
        meta = position_symbol_meta(sym)
        if not t.get("symbol_name"):
            t["symbol_name"] = meta.get("name") or sym
        t["symbol_exchange"] = meta.get("exchange") or ""
        t["symbol_is_main"] = bool(meta.get("is_main"))
    except Exception:
        t.setdefault("symbol_exchange", "")
        t.setdefault("symbol_is_main", False)


def enrich_trades_for_records(
    trades: list[dict[str, Any]],
    *,
    initial_capital: float = 0.0,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
    """表格仍按 id 降序；资金曲线按平仓时间升序用最新资金绘制。"""
    rows = [dict(t) for t in trades]
    chrono = sorted(
        rows,
        key=lambda t: ((t.get("close_time") or ""), int(t.get("id") or 0)),
    )
    running = float(initial_capital or 0)
    curve: list[dict[str, Any]] = []

    for t in chrono:
        _attach_symbol_meta(t)
        pnl_net = float(t.get("pnl_net") or 0)
        eq = t.get("equity_after")
        if eq is None:
            if running > 0:
                eq = round(running + pnl_net, 2)
            else:
                eq = None
            t["equity_after"] = eq
        if eq is not None:
            running = float(eq)

        if t.get("margin_pct") is None:
            margin = float(t.get("margin") or 0)
            cap_before = float(eq or 0) - pnl_net if eq is not None else 0.0
            if margin > 0 and cap_before > 0:
                t["margin_pct"] = round(margin / cap_before * 100, 2)

        if eq is not None:
            curve.append({
                "time": (t.get("close_time") or "")[:19],
                "value": float(eq),
                "id": int(t.get("id") or 0),
            })

    return rows, curve