#!/usr/bin/env python3
"""
股票模拟盘业绩汇报 — 自动收集/分析/汇总/建议
============================================
2026-08-02 牧尘批评："项目运行一个月了，你从没有把数据收集、分析、汇总，给我建议。
每次都是我问你进度，你才开始看情况"——本脚本修复这个缺口：
不再等人问，定期自动把模拟盘业绩算清楚推给牧尘。

数据源：
1. paper 账户（~/.hermes/stock_backtest/paper_trades_*.json）— 早期单股模拟
2. 多行业账户（multi_account/account_*.json）— 当前主力模拟盘
3. 实时行情（腾讯 qt.gtimg.cn）— 持仓浮盈计算
4. 回测汇总（ma20_summary.json）— 策略历史有效性

用法:
  python3 stock_performance.py              # 完整报告（默认）
  python3 stock_performance.py --weekly     # 周报模式（周五收盘后）
  python3 stock_performance.py --monthly    # 月报模式（月末）
  python3 stock_performance.py --json       # JSON 输出

输出: 报告文本 + 推飞书（--push）
"""
import json, os, subprocess, sys
from datetime import datetime, date
from pathlib import Path

HOME = Path.home()
BACKTEST = HOME / ".hermes" / "stock_backtest"
SCRIPTS = HOME / ".hermes" / "scripts"

# 腾讯行情接口（curl subprocess 模式，铁律：urllib 在此目录挂起）
def get_url(url, timeout=8, enc="utf-8"):
    env = dict(os.environ)
    for k in ["http_proxy", "https_proxy", "HTTP_PROXY", "HTTPS_PROXY"]:
        env.pop(k, None)
    r = subprocess.run(["curl", "-s", "--max-time", str(timeout), "--compressed", url],
                       capture_output=True, timeout=timeout+2, env=env)
    return r.stdout.decode(enc, errors="ignore")

def get_quote(code):
    """腾讯实时行情 → {price, name}；code 如 000001 → sz000001"""
    mc = ("sh" if code.startswith(("6", "5")) else "sz") + code
    raw = get_url(f"https://qt.gtimg.cn/q={mc}", enc="gbk")
    if "~" not in raw:
        return None
    parts = raw.split("~")
    return {"price": float(parts[3]), "name": parts[1], "code": code}

def load_json(path):
    if Path(path).exists():
        try:
            return json.load(open(path))
        except Exception:
            return None
    return None

def calc_position_pnl(code, shares, avg_cost):
    """按实时价算浮盈"""
    q = get_quote(code)
    if not q:
        return None, None, None
    market_value = shares * q["price"]
    pnl = market_value - shares * avg_cost
    pnl_pct = pnl / (shares * avg_cost) * 100
    return q["price"], pnl, pnl_pct

def collect_paper_accounts():
    """早期 paper 账户"""
    result = []
    for f in sorted(BACKTEST.glob("paper_trades_*.json")):
        d = load_json(f)
        if not d:
            continue
        for pos in d.get("positions", []):
            code = f.stem.replace("paper_trades_", "")
            result.append({
                "type": "paper",
                "stock": d.get("stock", code),
                "code": code,
                "shares": pos["shares"],
                "avg_cost": pos["avg_cost"],
                "start": d.get("start_date", ""),
            })
    return result

def collect_multi_accounts():
    """多行业账户 + 做空账户 + 全球账户"""
    result = []
    # 多行业账户
    adir = BACKTEST / "multi_account"
    if adir.exists():
        for f in sorted(adir.glob("account_*.json")):
            a = load_json(f)
            if not a:
                continue
            for pos in a.get("positions", []):
                result.append({
                    "type": "multi",
                    "stock": a.get("stock", ""),
                    "code": a.get("code", ""),
                    "industry": a.get("industry", ""),
                    "shares": pos.get("shares", 0),
                    "avg_cost": pos.get("avg_cost", 0),
                    "start": a.get("created", ""),
                })
    # 做空账户（空头持仓：盈亏 = (开仓价 - 现价) * 股数）
    sdir = BACKTEST / "short_account"
    if sdir.exists():
        for f in sorted(sdir.glob("short_*.json")):
            a = load_json(f)
            if not a:
                continue
            for pos in a.get("short_positions", []):
                result.append({
                    "type": "short",
                    "stock": a.get("stock", ""),
                    "code": a.get("code", ""),
                    "industry": a.get("industry", ""),
                    "shares": pos.get("shares", 0),
                    "avg_cost": pos.get("open_price", 0),
                    "start": pos.get("open_date", ""),
                })
    # 全球账户
    gdir = BACKTEST / "global_account"
    if gdir.exists():
        for f in sorted(gdir.glob("global_*.json")):
            a = load_json(f)
            if not a:
                continue
            for pos in a.get("positions", []):
                result.append({
                    "type": "global",
                    "stock": a.get("stock", ""),
                    "code": a.get("code", ""),
                    "market": a.get("market", ""),
                    "shares": pos.get("shares", 0),
                    "avg_cost": pos.get("avg_cost", 0),
                    "start": a.get("created", ""),
                })
    return result

def build_report():
    today = date.today().isoformat()
    lines = []
    lines.append(f"📊 模拟盘业绩报告 {today}")
    lines.append("=" * 42)

    # 1. 当前持仓 + 浮盈
    positions = collect_paper_accounts() + collect_multi_accounts()
    lines.append("📈 当前持仓")
    total_pnl = 0
    total_cost = 0
    if positions:
        for p in positions:
            price, pnl, pnl_pct = calc_position_pnl(p["code"], p["shares"], p["avg_cost"])
            if price is None:
                lines.append(f"  {p['stock']}({p['code']}) 行情获取失败")
                continue
            # 做空盈亏 = (开仓价 - 现价) * 股数，与做多方向相反
            if p["type"] == "short":
                pnl = (p["avg_cost"] - price) * p["shares"]
                pnl_pct = pnl / (p["avg_cost"] * p["shares"]) * 100
            if p["type"] == "paper":
                tag = "paper"
            elif p["type"] == "short":
                tag = f"做空[{p.get('industry','')}]"
            elif p["type"] == "global":
                tag = f"{p.get('market','')}[{p['stock']}]"
            else:
                tag = f"多账户[{p.get('industry','')}]"
            arrow = "🟢" if pnl >= 0 else "🔴"
            lines.append(f"  {arrow} {p['stock']} {p['shares']}股 @{p['avg_cost']:.2f} → {price:.2f} "
                        f"({pnl:+,.0f}元 / {pnl_pct:+.2f}%) [{tag}]")
            total_pnl += pnl
            total_cost += p["shares"] * p["avg_cost"]
        if total_cost > 0:
            lines.append(f"  合计持仓成本 {total_cost:,.0f}元 | 浮盈 {total_pnl:+,.0f}元 ({total_pnl/total_cost*100:+.2f}%)")
    else:
        lines.append("  空仓（无持仓）")

    # 2. 多账户总资产（2026-08-28 修复：总资产 = 现金 + 持仓成本，之前只算现金导致持仓账户资产被低估）
    adir = BACKTEST / "multi_account"
    total_cap = 0
    acct_count = 0
    if adir.exists():
        for f in sorted(adir.glob("account_*.json")):
            a = load_json(f)
            if a:
                total_cap += a.get("current_capital", 0)
                for p in a.get("positions", []):
                    total_cap += p.get("shares", 0) * p.get("avg_cost", 0)
                acct_count += 1
        lines.append(f"\n💰 多账户资产: {acct_count} 个账户 | 总资产 {total_cap:,.0f}元")
        # 有平仓交易的账户显示胜率
        win_t = sum(load_json(f).get("stats", {}).get("winning_trades", 0)
                    for f in adir.glob("account_*.json") if load_json(f))
        lose_t = sum(load_json(f).get("stats", {}).get("losing_trades", 0)
                     for f in adir.glob("account_*.json") if load_json(f))
        if win_t + lose_t > 0:
            lines.append(f"  已平仓交易: 胜{win_t} 负{lose_t} 胜率 {win_t/(win_t+lose_t)*100:.0f}%")

    # 2b. 做空 + 全球账户资产（2026-08-28 同步修复持仓市值计入）
    for dname, label in [("short_account", "做空"), ("global_account", "全球")]:
        d = BACKTEST / dname
        if d.exists():
            cap = 0
            for f in d.glob("*.json"):
                a = load_json(f)
                if a:
                    cap += a.get("current_capital", 0)
                    for p in a.get("positions", []):
                        cap += p.get("shares", 0) * p.get("avg_cost", 0)
            cnt = len(list(d.glob("*.json")))
            lines.append(f"💰 {label}账户资产: {cnt} 个账户 | 总资产 {cap:,.0f}元")

    # 3. 策略回测有效性（ma20_summary）
    ms = load_json(BACKTEST / "ma20_summary.json")
    if ms:
        lines.append("\n📚 策略回测参考 (2024-06~2026 区间)")
        for s in ms.get("stocks", [])[:5]:
            lines.append(f"  {s['name']}: α {s['alpha']:+.1f}% 胜率{s['win_rate']:.0f}% 交易{s['total_trades']}笔")
        lines.append(f"  有效板块: {', '.join(ms.get('effective', []))} | 低效: {', '.join(ms.get('ineffective', []))}")

    # 4. 建议
    lines.append("\n💡 建议")
    if total_pnl > 0 and total_cost > 0:
        lines.append(f"  ✅ 当前持仓浮盈 {total_pnl:+,.0f}元 — 持有策略有效，继续按 MA20 纪律（死叉卖出）")
    else:
        lines.append("  ⚠️ 当前空仓 — 等待强势行业金叉信号自动开仓")
    if positions:
        for p in positions:
            lines.append(f"  • {p['stock']}: 关注 MA20 死叉信号（{p['code']}）")

    return "\n".join(lines)

if __name__ == "__main__":
    args = sys.argv[1:]
    mode = "monthly" if "--monthly" in args else ("weekly" if "--weekly" in args else "daily")
    report = build_report()
    print(report)
    if "--push" in args:
        # 通过 send_message 推飞书（由外层 wrapper 处理）
        pass