"""
evolution/evolution_api.py — 进化模块 API 接口
供 dashboard 查询健康度、教训、迭代历史
"""
import sys, os, json, sqlite3

sys.path.insert(0, '/home/hmo/MoFin')
sys.path.insert(0, '/home/hmo/MoFin/deploy/profile-scripts')

DB = os.environ.get('MOFIN_DB', '/home/hmo/MoFin/data/mofin.db')


def get_evolution_dashboard():
    """进化模块 Dashboard 数据"""
    conn = sqlite3.connect(DB)
    conn.row_factory = sqlite3.Row
    
    # 最近健康度（近30天）
    health = []
    for r in conn.execute("""
        SELECT strategy_version, date, live_trades, live_wins, live_return_pct,
               backtest_wr, backtest_avg_ret, deviation, health_score
        FROM strategy_health ORDER BY date DESC LIMIT 30
    """).fetchall():
        health.append(dict(r))
    
    # 最近教训（近20条）
    lessons = []
    for r in conn.execute("""
        SELECT strategy_version, lesson_type, lesson_text, confidence, applied, created_at
        FROM strategy_lessons ORDER BY id DESC LIMIT 20
    """).fetchall():
        lessons.append(dict(r))
    
    # 迭代历史
    evolution = []
    for r in conn.execute("""
        SELECT parent_version, child_version, change_description, promoted, created_at
        FROM strategy_evolution ORDER BY id DESC LIMIT 20
    """).fetchall():
        evolution.append(dict(r))
    
    # 当前策略基线（2026-08-15: 数据驱动——跟随 strategy_weights.json 激活集合，
    # 原硬编码 ['v_weak','v_oversold'] 与温区路由脱节，激活策略换了一批但基线还显示旧的）
    def _active_versions():
        try:
            d = json.loads(open('/home/hmo/MoFin/data/strategy_weights.json', encoding='utf-8').read())
            vs = list(d.get('active') or [])
            vs += list(((d.get('markets') or {}).get('hk') or {}).get('active') or [])
            seen, out = set(), []
            for v in vs:
                if v and v not in seen:
                    seen.add(v)
                    out.append(v)
            return out or ['v_weak', 'v_oversold']
        except Exception:
            return ['v_weak', 'v_oversold']
    baseline = {}
    for v in _active_versions():
        r = conn.execute("""
            SELECT results_json FROM strategy_research 
            WHERE version=? AND period_tag='5y' ORDER BY id DESC LIMIT 1
        """, (v,)).fetchone()
        if r:
            res = json.loads(r[0])
            s = res.get('summary', {})
            pf = s.get('portfolio_full', {})
            baseline[v] = {
                'win_rate': s.get('win_rate', 0),
                'total_return': pf.get('total_return_pct', 0),
                'cagr': pf.get('cagr_pct', 0),
                'max_dd': pf.get('portfolio_max_dd_pct', 0),
            }
    
    # ── 2026-08-16 进化机制数据：读预计算快照（precompute_evolution.py 定期生成，避免实时重算）──
    hypotheses = []
    b_group = []
    qual_overview = []
    try:
        _ec = json.loads(open('/home/hmo/MoFin/data/evolution_center.json', encoding='utf-8').read())
        hypotheses = _ec.get('hypotheses', [])
        b_group = _ec.get('b_group', [])
        qual_overview = _ec.get('qual_overview', [])
    except Exception:
        pass

    conn.close()
    
    return {
        'health': health,
        'lessons': lessons,
        'evolution': evolution,
        'baseline': baseline,
        'hypotheses': hypotheses,
        'b_group': b_group,
        'qual_overview': qual_overview,
    }


def get_combo_dashboard():
    """组合方案 Dashboard 数据 (2026-08-02 新增)
    返回: 当前组合方案(v_next4+v_mr按regime分工) + 组合回测版本(v_combo) + 市场阶段
    """
    conn = sqlite3.connect(DB)
    conn.row_factory = sqlite3.Row

    # 1. 当前市场阶段 (market_regime)
    regime = None
    r = conn.execute("SELECT * FROM market_regime ORDER BY date DESC LIMIT 1").fetchone()
    if r:
        regime = dict(r)

    # 2. 组合回测版本 (v_combo 家族)
    combos = []
    rows = conn.execute(
        "SELECT id, version, market, period_tag, created_at, results_json"
        " FROM strategy_research WHERE version LIKE '%combo%' OR version LIKE 'v_combo%'"
        " ORDER BY id DESC"
    ).fetchall()
    for r in rows:
        d = dict(r)
        res = json.loads(d.pop("results_json") or "{}")
        s = res.get("summary", {})
        pf = s.get("portfolio_full", {})
        p5 = s.get("portfolio", {})
        d["summary_stats"] = {
            "total_trades": s.get("total_trades"),
            "win_rate": s.get("win_rate"),
            "avg_profit_pct": s.get("avg_profit_pct"),
            "avg_hold_days": s.get("avg_hold_days"),
            "sharpe_ratio": s.get("sharpe_ratio"),
            "profit_factor": s.get("profit_factor"),
            "universality": s.get("universality", {}),
            "portfolio": p5,
            "portfolio_full": pf,
        }
        combos.append(d)

    # 3. 组合成员策略的独立指标
    # 2026-08-11 更新：组合成员 = v_weak（实盘）+ p_oversold（新策略），替代旧的 v_next4+v_mr
    # v_next4 移除（池内卫星仓，全市场失效；现有池子票不是它选的）
    members = {}
    for v in ["v_weak", "p_oversold"]:
        sel_v = "v_weak" if v == "v_mr" else None
        # 2026-08-12: p_oversold 实盘名 → 回测数据存 v_oversold（研究名），两个都查
        candidates = ["v_oversold", "p_oversold"] if v == "p_oversold" else (["v_weak", "v_mr_sel", v] if sel_v else [v])
        r = None
        used_sel = False
        for cv in candidates:
            r = conn.execute(
                "SELECT results_json FROM strategy_research"
                " WHERE version=? AND period_tag='10y' ORDER BY id DESC LIMIT 1",
                (cv,),
            ).fetchone()
            if r:
                used_sel = (cv == "v_weak")
                break
        if r:
            res = json.loads(r[0])
            s = res.get("summary", {})
            pf = s.get("portfolio_full", {})
            p5 = s.get("portfolio", {})
            members[v] = {
                "role": "弱市超跌确认（实盘）" if v == "v_weak" else "预测超跌反弹（新策略）",
                "version": ("v_weak" if used_sel else "v_mr") if v == "v_mr" else v,
                "is_sel": used_sel,
                "trades": s.get("total_trades"),
                "win_rate": s.get("win_rate"),
                "avg_profit_pct": s.get("avg_profit_pct"),
                "avg_hold_days": s.get("avg_hold_days"),
                "cagr_pct": p5.get("cagr_pct"),
                "return_pct": p5.get("total_return_pct"),
                "max_dd_pct": p5.get("portfolio_max_dd_pct"),
                "slots": p5.get("slots") or 6,
                "universality": s.get("universality", {}),
                # 组合模拟实际执行笔数(扣费后) + 年均(手工可行性参考)
                "positions_taken_5slot": p5.get("positions_taken"),
                "positions_taken_full": pf.get("positions_taken"),
            }
    # 2026-08-11：p_oversold 无回测数据时给兜底卡片（新策略待回测）
    if "p_oversold" not in members:
        members["p_oversold"] = {
            "role": "预测超跌反弹（新策略）",
            "version": "p_oversold",
            "is_sel": False,
            "trades": None, "win_rate": None, "avg_profit_pct": None,
            "avg_hold_days": None, "cagr_pct": None, "return_pct": None,
            "max_dd_pct": None, "slots": 10,
            "universality": {},
            "positions_taken_5slot": None, "positions_taken_full": None,
            "note": "新策略，待回测/实盘验证",
        }

    conn.close()

    # 2026-08-13 温区自适应：并入 strategy_weights.json（当前温区+温度+各策略权重/激活）
    # + strategy_alerts.json（三振出局状态）
    import json as _json
    from pathlib import Path as _Path
    _d = _Path("/home/hmo/MoFin/data")
    weights_data = None
    alerts_data = None
    try:
        _w = _d / "strategy_weights.json"
        if _w.exists():
            weights_data = _json.loads(_w.read_text(encoding="utf-8"))
    except Exception:
        pass
    try:
        _a = _d / "strategy_alerts.json"
        if _a.exists():
            alerts_data = _json.loads(_a.read_text(encoding="utf-8"))
    except Exception:
        pass

    return {
        "regime": regime,
        "regime_weights": weights_data,   # 当前温区/温度/各策略权重/激活
        "strategy_alerts": alerts_data,   # 三振出局状态
        "combos": combos,
        "members": members,
        "routing": [
            {"regime": "trend_up", "active": "p_oversold", "action": "预测超跌反弹", "desc": "趋势市/反弹期, p_oversold 预测超跌反弹"},
            {"regime": "choppy", "active": "v_weak", "action": "弱市超跌确认", "desc": "震荡/下跌市, v_weak 均值回复主战场"},
            {"regime": "trend_down", "active": "v_weak", "action": "深超跌管理", "desc": "下跌市, v_weak 管理超跌持仓"},
        ],
    }


def get_health_trend(version='v_weak', days=30):
    """健康度趋势"""
    conn = sqlite3.connect(DB)
    conn.row_factory = sqlite3.Row
    rows = conn.execute("""
        SELECT date, health_score, deviation, live_trades
        FROM strategy_health WHERE strategy_version=? ORDER BY date DESC LIMIT ?
    """, (version, days)).fetchall()
    conn.close()
    return [dict(r) for r in rows]


def record_evolution(parent, child, description, backtest_result=None, promoted=0):
    """记录一次策略迭代"""
    conn = sqlite3.connect(DB)
    conn.execute("""
        INSERT INTO strategy_evolution (parent_version, child_version, change_description, backtest_result, promoted)
        VALUES (?, ?, ?, ?, ?)
    """, (parent, child, description, json.dumps(backtest_result) if backtest_result else None, promoted))
    conn.commit()
    conn.close()


if __name__ == '__main__':
    d = get_evolution_dashboard()
    print(f"健康度: {len(d['health'])}条, 教训: {len(d['lessons'])}条, 迭代: {len(d['evolution'])}条")
    print(f"基线: {list(d['baseline'].keys())}")