#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""regime_perf.py — 策略-温区表现常态化记录（2026-08-13）

记录策略在不同温区（trend_up/choppy/trend_down）的表现，供"适用温度"动态评估。
- 数据来源：strategy_research 回测 trades（按入场日归入温区）+ 实盘 strategy_tracking
- 表：strategy_regime_perf（strategy, regime, trades, win_rate, avg_pnl, updated_at）
- 原则：策略全温区发信号（去门控后），记录各温区真实表现；适用温区是动态的，随数据更新

用法：
  python3 regime_perf.py            # 全量更新（从回测+实盘重算）
  from regime_perf import get_regime_perf
"""
import sys
import json
import sqlite3
from pathlib import Path
from datetime import datetime
from collections import defaultdict

_SCRIPT_DIR = Path(__file__).resolve().parent
sys.path.insert(0, str(_SCRIPT_DIR))
sys.path.insert(0, "/home/hmo/MoFin")

DB = "/home/hmo/MoFin/data/mofin.db"

def load_all_strategies():
    """从 strategy_research 读取所有策略版本（含历史/表现不佳的——可能在特定温区能打）"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    rows = conn.execute("SELECT DISTINCT version FROM strategy_research ORDER BY version").fetchall()
    conn.close()
    return [r[0] for r in rows if r[0]]

# 关注的策略（动态：全部版本）
STRATEGIES = load_all_strategies()

def load_regime_map():
    """date -> regime（用平滑 regime_tracker 的周期反查更合理，这里用 market_regime 原始 + 手动按 K=5 平滑）
    简化：直接用 market_regime 的 regime（与平滑 K=5 差异主要在边界几天，评估可接受）"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    rows = conn.execute("SELECT date, regime FROM market_regime").fetchall()
    conn.close()
    return dict(rows)

def get_trades_from_research(version):
    """从 strategy_research 取最新回测 trades"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    rows = conn.execute(
        "SELECT results_json FROM strategy_research WHERE version=? ORDER BY period_tag DESC, created_at DESC LIMIT 1",
        (version,)
    ).fetchall()
    conn.close()
    if not rows:
        return []
    try:
        return json.loads(rows[0][0]).get("trades", [])
    except Exception:
        return []

def get_trades_from_tracking():
    """从实盘 strategy_tracking 取已平仓交易"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    rows = conn.execute(
        "SELECT version_seq, tracked_at, theoretical_pnl FROM strategy_tracking WHERE status='closed'"
    ).fetchall()
    conn.close()
    result = []
    for version_seq, tracked_at, pnl in rows:
        if version_seq and tracked_at:
            result.append({"version": version_seq, "entry_date": tracked_at[:10], "profit_pct": pnl})
    return result

def compute(use_tracking=True):
    """计算所有策略各温区表现"""
    regime_map = load_regime_map()
    stats = defaultdict(lambda: defaultdict(lambda: {"n": 0, "win": 0, "pnl": 0}))

    for v in STRATEGIES:
        trades = get_trades_from_research(v)
        for t in trades:
            ed = t.get("entry_date", "")
            if ed not in regime_map:
                continue
            reg = regime_map[ed]
            pnl = t.get("profit_pct", 0) or 0
            stats[v][reg]["n"] += 1
            stats[v][reg]["pnl"] += pnl
            if pnl > 0:
                stats[v][reg]["win"] += 1

    if use_tracking:
        for t in get_trades_from_tracking():
            v = t["version"]
            if v not in stats:
                stats[v] = defaultdict(lambda: {"n": 0, "win": 0, "pnl": 0})
            ed = t["entry_date"]
            if ed in regime_map:
                reg = regime_map[ed]
                pnl = t["profit_pct"] or 0
                stats[v][reg]["n"] += 1
                stats[v][reg]["pnl"] += pnl
                if pnl > 0:
                    stats[v][reg]["win"] += 1

    return stats

def save(stats):
    """写入 strategy_regime_perf 表（清空重建，保持与最新数据同步）"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    conn.execute("""
        CREATE TABLE IF NOT EXISTS strategy_regime_perf (
            strategy TEXT,
            regime TEXT,
            trades INTEGER,
            win_rate REAL,
            avg_pnl REAL,
            updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
            PRIMARY KEY (strategy, regime)
        )
    """)
    conn.execute("DELETE FROM strategy_regime_perf")
    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    for v, regs in stats.items():
        for reg, s in regs.items():
            if s["n"] < 2:
                continue  # 样本太少不记录（>=2 给观察机会）
            wr = s["win"] / s["n"] * 100
            avg = s["pnl"] / s["n"]
            conn.execute(
                "INSERT OR REPLACE INTO strategy_regime_perf (strategy, regime, trades, win_rate, avg_pnl, updated_at) VALUES (?,?,?,?,?,?)",
                (v, reg, s["n"], round(wr, 1), round(avg, 2), now)
            )
    conn.commit()
    conn.close()

def main():
    stats = compute(use_tracking=True)
    save(stats)
    # 打印
    print("=== 策略-温区表现（strategy_regime_perf）===")
    conn = sqlite3.connect(DB, timeout=30)
    rows = conn.execute("SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf ORDER BY strategy, regime").fetchall()
    conn.close()
    for r in rows:
        print(f"  {r[0]:<12} {r[1]:<12} {r[2]:>4}笔 胜率{r[3]:.0f}% 均盈{r[4]:+.2f}%")

def get_regime_perf(strategy=None):
    """读取策略-温区表现（供 router 动态适用温区）"""
    conn = sqlite3.connect(DB, timeout=30)
    conn.execute("PRAGMA busy_timeout=30000")
    if strategy:
        rows = conn.execute(
            "SELECT regime, trades, win_rate, avg_pnl FROM strategy_regime_perf WHERE strategy=?",
            (strategy,)
        ).fetchall()
    else:
        rows = conn.execute(
            "SELECT strategy, regime, trades, win_rate, avg_pnl FROM strategy_regime_perf"
        ).fetchall()
    conn.close()
    if strategy:
        return {r[0]: {"trades": r[1], "win_rate": r[2], "avg_pnl": r[3]} for r in rows}
    result = defaultdict(dict)
    for r in rows:
        result[r[0]][r[1]] = {"trades": r[2], "win_rate": r[3], "avg_pnl": r[4]}
    return dict(result)

if __name__ == "__main__":
    main()