143 lines
4.8 KiB
Python
143 lines
4.8 KiB
Python
"""
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evolution/health_monitor.py — 策略健康度监控
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对比实盘交易 vs 回测预期，计算健康分，偏差过大时报警
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"""
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import sys, os, json, sqlite3
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from datetime import datetime, timedelta
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sys.path.insert(0, '/home/hmo/MoFin')
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sys.path.insert(0, '/home/hmo/MoFin/deploy/profile-scripts')
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DB = os.environ.get('MOFIN_DB', '/home/hmo/MoFin/data/mofin.db')
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CURRENT_STRATEGY = 'v_next4'
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def get_backtest_baseline(conn, version):
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"""从 strategy_research 取回测基线"""
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r = conn.execute("""
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SELECT results_json FROM strategy_research
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WHERE version=? AND period_tag='5y' ORDER BY id DESC LIMIT 1
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""", (version,)).fetchone()
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if not r:
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return None
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res = json.loads(r[0])
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s = res.get('summary', {})
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return {
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'win_rate': s.get('win_rate', 0),
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'avg_profit_pct': s.get('avg_profit_pct', 0),
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'total_trades': s.get('total_trades', 0),
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}
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def get_live_trades(conn, days=7):
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"""取近N天实盘交易（holding_strategies 全部，计算盈亏）"""
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since = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
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try:
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rows = conn.execute("""
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SELECT code, name, price as current_price, avg_price as entry_price,
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timing_signal as signal, updated_at,
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CASE WHEN avg_price > 0 THEN round((price - avg_price) / avg_price * 100, 2) ELSE 0 END as profit_pct
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FROM holding_strategies
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WHERE updated_at >= ? AND avg_price > 0
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ORDER BY updated_at DESC
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""", (since,)).fetchall()
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return rows
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except sqlite3.OperationalError as e:
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print(f"查询失败: {e}", flush=True)
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return []
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def calc_health_score(live_wr, live_ret, backtest_wr, backtest_ret):
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"""计算健康分 (0-100)
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健康分 = 100 - 偏差惩罚
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偏差 = |实盘胜率-回测胜率| + |实盘收益-回测收益|/2
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"""
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if backtest_wr == 0:
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return 50 # 无基线，中性分
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wr_dev = abs(live_wr - backtest_wr)
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ret_dev = abs(live_ret - backtest_ret) / 2
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deviation = wr_dev + ret_dev
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# 偏差越大，健康分越低
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health = max(0, 100 - deviation * 2)
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return round(health, 1)
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def run_health_check(strategy_version=None):
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"""执行健康度检查"""
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version = strategy_version or CURRENT_STRATEGY
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conn = sqlite3.connect(DB)
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conn.row_factory = sqlite3.Row
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# 回测基线
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baseline = get_backtest_baseline(conn, version)
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if not baseline:
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print(f"无 {version} 回测基线", flush=True)
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conn.close()
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return None
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# 实盘交易（近7天）
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live = get_live_trades(conn, days=7)
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today = datetime.now().strftime('%Y-%m-%d')
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if not live:
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# 无实盘数据，记录中性健康分
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health = 50
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deviation = 0
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live_wr = live_ret = 0
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print(f"{version}: 近7天无实盘交易，健康分=50(中性)", flush=True)
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else:
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wins = sum(1 for t in live if (t.get('profit_pct') or 0) > 0)
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total = len(live)
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live_wr = round(100 * wins / total, 1) if total else 0
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live_ret = round(sum(t.get('profit_pct') or 0 for t in live) / total, 2) if total else 0
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health = calc_health_score(live_wr, live_ret, baseline['win_rate'], baseline['avg_profit_pct'])
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deviation = abs(live_wr - baseline['win_rate'])
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# 写入 strategy_health 表
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conn.execute("""
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INSERT OR REPLACE INTO strategy_health
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(strategy_version, date, live_trades, live_wins, live_return_pct,
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backtest_wr, backtest_avg_ret, deviation, health_score)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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""", (version, today, len(live), sum(1 for t in live if (t.get('profit_pct') or 0) > 0),
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live_ret, baseline['win_rate'], baseline['avg_profit_pct'], deviation, health))
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conn.commit()
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# 报警判断
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alert = None
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if health < 40:
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alert = f"🔴 策略健康度严重下降: {health}分 (偏差{deviation}pp)"
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elif health < 60:
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alert = f"🟡 策略健康度偏低: {health}分 (偏差{deviation}pp)"
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result = {
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'version': version,
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'date': today,
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'live_trades': len(live),
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'live_wr': live_wr,
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'live_ret': live_ret,
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'backtest_wr': baseline['win_rate'],
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'backtest_ret': baseline['avg_profit_pct'],
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'deviation': deviation,
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'health_score': health,
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'alert': alert,
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}
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print(f"{version} 健康度: {health}分 (实盘{live_wr}%/{live_ret}% vs 回测{baseline['win_rate']}%/{baseline['avg_profit_pct']}%)", flush=True)
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if alert:
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print(f" {alert}", flush=True)
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conn.close()
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return result
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if __name__ == '__main__':
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import sys
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sys.path.insert(0, '/home/hmo/MoFin/evolution')
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from __init__ import init_evolution_tables
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init_evolution_tables()
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run_health_check()
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