# 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

"""趋势回调：纯计算（期货整数手）。"""
from __future__ import annotations

import json
import math
from typing import Any, Optional, Tuple

from contract_specs import get_contract_spec


def validate_trend_bounds(direction: str, stop_loss: float, add_upper: float) -> Optional[str]:
    direction = (direction or "long").strip().lower()
    if direction == "long":
        if not (float(stop_loss) < float(add_upper)):
            return "做多：止损须低于补仓上沿"
    else:
        if not (float(stop_loss) > float(add_upper)):
            return "做空：止损须高于补仓下沿"
    return None


def build_grid_prices(direction: str, sl: float, upper: float, n_legs: int) -> list[float]:
    sl, upper = float(sl), float(upper)
    out: list[float] = []
    if n_legs <= 0:
        return out
    direction = (direction or "long").strip().lower()
    if direction == "long":
        if upper <= sl:
            return out
        span = upper - sl
        for i in range(1, n_legs + 1):
            out.append(sl + (i / float(n_legs + 1)) * span)
        out.sort(reverse=True)
    else:
        if sl <= upper:
            return out
        span = sl - upper
        for i in range(1, n_legs + 1):
            out.append(upper + (i / float(n_legs + 1)) * span)
        out.sort()
    return [round(p, 4) for p in out]


def compute_trend_plan_futures(
    *,
    direction: str,
    stop_loss: float,
    add_upper: float,
    take_profit: float,
    risk_percent: float,
    capital: float,
    live_price: float,
    ths_code: str,
    dca_legs: int = 5,
) -> Tuple[Optional[dict[str, Any]], Optional[str]]:
    err = validate_trend_bounds(direction, stop_loss, add_upper)
    if err:
        return None, err
    spec = get_contract_spec(ths_code)
    mult = spec["mult"]
    d = (direction or "long").strip().lower()
    if d == "short":
        worst_per_lot = (float(stop_loss) - float(add_upper)) * mult
    else:
        worst_per_lot = (float(add_upper) - float(stop_loss)) * mult
    if worst_per_lot <= 0:
        return None, "止损与补仓边界无法计算风险"
    budget = float(capital) * float(risk_percent) / 100.0
    total_lots = int(math.floor(budget / worst_per_lot))
    if total_lots < 3:
        return None, f"按 {risk_percent}% 风险，总手数至少需 3 手才能拆分首仓+补仓（当前 {total_lots} 手）"
    first_lots = total_lots // 2
    remainder = total_lots - first_lots
    legs = max(1, min(int(dca_legs), remainder))
    per_leg = remainder // legs
    leg_amounts = [per_leg] * (legs - 1) + [remainder - per_leg * (legs - 1)]
    if any(x < 1 for x in leg_amounts):
        legs = 1
        leg_amounts = [remainder]
    grid = build_grid_prices(d, stop_loss, add_upper, len(leg_amounts))
    margin_rate = spec["margin_rate"]
    plan_margin = float(live_price) * mult * total_lots * margin_rate
    return {
        "direction": d,
        "stop_loss": float(stop_loss),
        "add_upper": float(add_upper),
        "take_profit": float(take_profit),
        "risk_percent": float(risk_percent),
        "capital_snapshot": float(capital),
        "live_price_ref": float(live_price),
        "target_lots": total_lots,
        "first_lots": first_lots,
        "remainder_lots": remainder,
        "dca_legs": len(leg_amounts),
        "leg_amounts": leg_amounts,
        "leg_amounts_json": json.dumps(leg_amounts),
        "grid_prices_json": json.dumps(grid),
        "grid": grid,
        "plan_margin": round(plan_margin, 2),
        "mult": mult,
    }, None


def trend_dca_level_reached(direction: str, mark_price: float, level: float) -> bool:
    d = (direction or "long").strip().lower()
    pf, lv = float(mark_price), float(level)
    return pf <= lv if d == "long" else pf >= lv


def trend_strategy_periods() -> list[dict[str, str]]:
    """策略页可选 K 线周期。"""
    from kline_chart import MARKET_PERIODS

    skip = frozenset({"timeshare", "w"})
    return [p for p in MARKET_PERIODS if p["key"] not in skip]


def trend_period_label(key: str) -> str:
    k = (key or "").strip()
    for p in trend_strategy_periods():
        if p["key"] == k:
            return p["label"]
    return k or "15分"


def normalize_trend_period(key: str) -> str:
    valid = {p["key"] for p in trend_strategy_periods()}
    k = (key or "15m").strip()
    return k if k in valid else "15m"


def _avg_after_entries(entries: list[tuple[float, int]]) -> float:
    total = sum(q for _, q in entries)
    if total <= 0:
        return 0.0
    return sum(p * q for p, q in entries) / total


def enrich_trend_plan_preview(
    plan: dict,
    *,
    symbol: str,
    symbol_name: str = "",
    period: str = "15m",
) -> dict[str, Any]:
    """补全预览：周期、风险金额、分档表格（对齐币圈预览样式）。"""
    out = dict(plan)
    d = (out.get("direction") or "long").strip().lower()
    sl = float(out["stop_loss"])
    tp = float(out["take_profit"])
    mult = float(out.get("mult") or 1)
    entry0 = float(out["live_price_ref"])
    first_lots = int(out["first_lots"])
    leg_amounts = [int(x) for x in (out.get("leg_amounts") or [])]
    grid = [float(x) for x in (out.get("grid") or [])]
    capital = float(out.get("capital_snapshot") or 0)
    risk_pct = float(out.get("risk_percent") or 0)
    budget = capital * risk_pct / 100.0
    remainder = int(out.get("remainder_lots") or sum(leg_amounts))

    out["symbol"] = symbol
    out["symbol_name"] = symbol_name or symbol
    out["period"] = normalize_trend_period(period)
    out["period_label"] = trend_period_label(out["period"])
    out["stop_loss_budget"] = round(budget, 2)
    out["direction_label"] = "做多" if d == "long" else "做空"

    entries: list[tuple[float, int]] = [(entry0, first_lots)]
    rows: list[dict[str, Any]] = []

    def leg_metrics() -> tuple[float, float, float, Optional[float]]:
        total = sum(q for _, q in entries)
        avg = _avg_after_entries(entries)
        if d == "long":
            profit = (tp - avg) * total * mult
            loss = (avg - sl) * total * mult
        else:
            profit = (avg - tp) * total * mult
            loss = (sl - avg) * total * mult
        rr = profit / loss if loss > 0 else None
        return (
            round(avg, 4),
            round(profit, 2),
            round(loss, 2),
            round(rr, 2) if rr is not None else None,
        )

    avg, profit, loss, rr = leg_metrics()
    rows.append({
        "level": "首仓",
        "price": round(entry0, 4),
        "lots": first_lots,
        "avg_after": avg,
        "profit_at_tp": profit,
        "loss_at_sl": loss,
        "rr_ratio": rr,
    })
    out["first_rr_ratio"] = rr

    for i, lots in enumerate(leg_amounts):
        price = grid[i] if i < len(grid) else sl
        entries.append((float(price), int(lots)))
        avg, profit, loss, rr = leg_metrics()
        rows.append({
            "level": f"补仓{i + 1}",
            "price": round(float(price), 4),
            "lots": int(lots),
            "avg_after": avg,
            "profit_at_tp": profit,
            "loss_at_sl": loss,
            "rr_ratio": rr,
        })

    out["preview_rows"] = rows
    out["summary_line"] = (
        f"{out['symbol_name']} {out['symbol']} {out['direction_label']} {out['period_label']}"
        f" | 权益 {capital:.2f} 元"
        f" | 参考价 {entry0}"
        f" | 计划保证金 ≈ {out.get('plan_margin')} 元"
        f" | 总手 {out.get('target_lots')}（首仓 {first_lots} + 补仓 {remainder}）"
    )
    out["detail_line"] = (
        f"止损价 {sl} | 止损金额 {out['stop_loss_budget']} 元（权益 × 风险 {risk_pct}%）"
        f" | 补仓边界 {float(out['add_upper'])} | 止盈价 {tp}"
        f" | 首仓盈亏比 {out['first_rr_ratio'] if out['first_rr_ratio'] is not None else '—'}"
    )
    return out