204 lines
7.8 KiB
Python
204 lines
7.8 KiB
Python
"""
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evolution/evolution_api.py — 进化模块 API 接口
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供 dashboard 查询健康度、教训、迭代历史
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"""
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import sys, os, json, sqlite3
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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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def get_evolution_dashboard():
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"""进化模块 Dashboard 数据"""
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conn = sqlite3.connect(DB)
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conn.row_factory = sqlite3.Row
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# 最近健康度（近30天）
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health = []
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for r in conn.execute("""
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SELECT 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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FROM strategy_health ORDER BY date DESC LIMIT 30
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""").fetchall():
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health.append(dict(r))
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# 最近教训（近20条）
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lessons = []
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for r in conn.execute("""
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SELECT strategy_version, lesson_type, lesson_text, confidence, applied, created_at
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FROM strategy_lessons ORDER BY id DESC LIMIT 20
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""").fetchall():
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lessons.append(dict(r))
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# 迭代历史
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evolution = []
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for r in conn.execute("""
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SELECT parent_version, child_version, change_description, promoted, created_at
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FROM strategy_evolution ORDER BY id DESC LIMIT 20
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""").fetchall():
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evolution.append(dict(r))
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# 当前策略基线（2026-08-11: 改为当前实盘 v_weak + 新策略 v_oversold）
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baseline = {}
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for v in ['v_weak', 'v_oversold']:
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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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""", (v,)).fetchone()
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if r:
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res = json.loads(r[0])
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s = res.get('summary', {})
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pf = s.get('portfolio_full', {})
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baseline[v] = {
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'win_rate': s.get('win_rate', 0),
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'total_return': pf.get('total_return_pct', 0),
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'cagr': pf.get('cagr_pct', 0),
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'max_dd': pf.get('portfolio_max_dd_pct', 0),
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}
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conn.close()
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return {
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'health': health,
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'lessons': lessons,
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'evolution': evolution,
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'baseline': baseline,
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}
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def get_combo_dashboard():
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"""组合方案 Dashboard 数据 (2026-08-02 新增)
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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
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"""
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conn = sqlite3.connect(DB)
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conn.row_factory = sqlite3.Row
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# 1. 当前市场阶段 (market_regime)
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regime = None
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r = conn.execute("SELECT * FROM market_regime ORDER BY date DESC LIMIT 1").fetchone()
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if r:
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regime = dict(r)
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# 2. 组合回测版本 (v_combo 家族)
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combos = []
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rows = conn.execute(
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"SELECT id, version, market, period_tag, created_at, results_json"
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" FROM strategy_research WHERE version LIKE '%combo%' OR version LIKE 'v_combo%'"
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" ORDER BY id DESC"
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).fetchall()
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for r in rows:
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d = dict(r)
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res = json.loads(d.pop("results_json") or "{}")
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s = res.get("summary", {})
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pf = s.get("portfolio_full", {})
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p5 = s.get("portfolio", {})
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d["summary_stats"] = {
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"total_trades": s.get("total_trades"),
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"win_rate": s.get("win_rate"),
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"avg_profit_pct": s.get("avg_profit_pct"),
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"avg_hold_days": s.get("avg_hold_days"),
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"sharpe_ratio": s.get("sharpe_ratio"),
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"profit_factor": s.get("profit_factor"),
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"universality": s.get("universality", {}),
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"portfolio": p5,
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"portfolio_full": pf,
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}
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combos.append(d)
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# 3. 组合成员策略的独立指标
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# 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
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# v_next4 移除（池内卫星仓，全市场失效；现有池子票不是它选的）
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members = {}
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for v in ["v_weak", "p_oversold"]:
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sel_v = "v_weak" if v == "v_mr" else None
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candidates = [sel_v, "v_mr_sel", v] if sel_v else [v]
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r = None
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used_sel = False
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for cv in candidates:
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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='10y' ORDER BY id DESC LIMIT 1",
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(cv,),
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).fetchone()
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if r:
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used_sel = (cv == "v_weak")
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break
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if r:
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res = json.loads(r[0])
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s = res.get("summary", {})
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pf = s.get("portfolio_full", {})
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p5 = s.get("portfolio", {})
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members[v] = {
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"role": "弱市超跌确认（实盘）" if v == "v_weak" else "预测超跌反弹（新策略）",
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"version": ("v_weak" if used_sel else "v_mr") if v == "v_mr" else v,
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"is_sel": used_sel,
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"trades": s.get("total_trades"),
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"win_rate": s.get("win_rate"),
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"avg_profit_pct": s.get("avg_profit_pct"),
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"avg_hold_days": s.get("avg_hold_days"),
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"cagr_pct": p5.get("cagr_pct"),
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"return_pct": p5.get("total_return_pct"),
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"max_dd_pct": p5.get("portfolio_max_dd_pct"),
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"slots": p5.get("slots") or 6,
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"universality": s.get("universality", {}),
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# 组合模拟实际执行笔数(扣费后) + 年均(手工可行性参考)
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"positions_taken_5slot": p5.get("positions_taken"),
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"positions_taken_full": pf.get("positions_taken"),
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}
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# 2026-08-11：p_oversold 无回测数据时给兜底卡片（新策略待回测）
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if "p_oversold" not in members:
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members["p_oversold"] = {
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"role": "预测超跌反弹（新策略）",
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"version": "p_oversold",
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"is_sel": False,
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"trades": None, "win_rate": None, "avg_profit_pct": None,
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"avg_hold_days": None, "cagr_pct": None, "return_pct": None,
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"max_dd_pct": None, "slots": 10,
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"universality": {},
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"positions_taken_5slot": None, "positions_taken_full": None,
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"note": "新策略，待回测/实盘验证",
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}
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conn.close()
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return {
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"regime": regime,
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"combos": combos,
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"members": members,
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"routing": [
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{"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"},
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{"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"},
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{"regime": "trend_down", "active": "v_weak", "action": "深超跌管理", "desc": "下跌市, v_weak 管理超跌持仓"},
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],
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}
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def get_health_trend(version='v_weak', days=30):
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"""健康度趋势"""
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conn = sqlite3.connect(DB)
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conn.row_factory = sqlite3.Row
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rows = conn.execute("""
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SELECT date, health_score, deviation, live_trades
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FROM strategy_health WHERE strategy_version=? ORDER BY date DESC LIMIT ?
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""", (version, days)).fetchall()
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conn.close()
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return [dict(r) for r in rows]
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def record_evolution(parent, child, description, backtest_result=None, promoted=0):
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"""记录一次策略迭代"""
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conn = sqlite3.connect(DB)
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conn.execute("""
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INSERT INTO strategy_evolution (parent_version, child_version, change_description, backtest_result, promoted)
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VALUES (?, ?, ?, ?, ?)
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""", (parent, child, description, json.dumps(backtest_result) if backtest_result else None, promoted))
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conn.commit()
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conn.close()
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if __name__ == '__main__':
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d = get_evolution_dashboard()
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print(f"健康度: {len(d['health'])}条, 教训: {len(d['lessons'])}条, 迭代: {len(d['evolution'])}条")
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print(f"基线: {list(d['baseline'].keys())}")
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