feat: 策略数据每日自动更新——period_rollup滑窗派生1y/2y/5y行(锚定数据末端,不覆盖真实记录)+health_monitor数据驱动跟随路由激活集合+regime_perf排序改最长周期优先(防派生行污染温区行)

deploy/profile-scripts/health_monitor_daily.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-"""health_monitor_daily.py — 策略健康度每日监控（v_weak + v_oversold）
+"""health_monitor_daily.py — 策略健康度每日监控（数据驱动：跟随 strategy_weights.json 激活集合）
 
 背景（2026-08-12 事项四：健康监控注册 p_oversold）：
   evolution/health_monitor.py 能算策略健康度（实盘近7天浮盈 vs 回测基线5y 偏差 + 写 strategy_health 表 + 告警），
@@ -31,6 +31,29 @@ def _singleton_guard(tag="health_monitor_daily.py"):
         sys.exit(0)
 
 
+def _load_active_strategies():
+    """从 strategy_weights.json 读当前激活策略（A股 active + 港股 markets.hk.active）。
+
+    2026-08-15 数据驱动改造：原硬编码 (v_weak, v_oversold)，温区切换后激活策略变化
+    但监控集合不跟随，导致激活策略无健康度数据。改为读路由输出，兜底旧二元组。
+    """
+    import json as _json
+    try:
+        d = _json.loads(Path("/home/hmo/MoFin/data/strategy_weights.json").read_text(encoding="utf-8"))
+        active = list(d.get("active") or [])
+        active += list(((d.get("markets") or {}).get("hk") or {}).get("active") or [])
+        seen, out = set(), []
+        for v in active:
+            if v and v not in seen:
+                seen.add(v)
+                out.append(v)
+        if out:
+            return out
+    except Exception as e:
+        print(f"  [warn] 读 strategy_weights.json 失败({e})，兜底 v_weak/v_oversold", flush=True)
+    return ["v_weak", "v_oversold"]
+
+
 def main():
     _fd = _singleton_guard()
     print(f"[health_monitor_daily] {datetime.now().strftime('%H:%M:%S')} 策略健康度监控开始", flush=True)
@@ -44,9 +67,11 @@ def main():
         _spec.loader.exec_module(_m)
         run_health_check = _m.run_health_check
 
-    # 当前策略：v_weak（实盘在跑）+ v_oversold（新策略上线）
+    # 数据驱动：监控集合 = 路由激活策略（A股+港股），随温区切换自动跟随
+    versions = _load_active_strategies()
+    print(f"  监控策略集合: {versions}", flush=True)
     results = {}
-    for version in ("v_weak", "v_oversold"):
+    for version in versions:
         try:
             r = run_health_check(strategy_version=version)
             results[version] = r

deploy/profile-scripts/regime_perf.py

@@ -52,7 +52,9 @@ def get_trades_from_research(version):
     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",
+        # 2026-08-15：最长周期优先（LENGTH 降序：'10y' len3 > '5y'/'2y' len2）——
+        # period_rollup 每日派生 1y/2y/5y 短窗行后，字典序 period_tag DESC 会错取短窗 trades
+        "SELECT results_json FROM strategy_research WHERE version=? ORDER BY LENGTH(COALESCE(period_tag,'2y')) DESC, COALESCE(period_tag,'2y') DESC, created_at DESC LIMIT 1",
         (version,)
     ).fetchall()
     conn.close()

deploy/profile-scripts/strategy_period_rollup.py

@@ -0,0 +1,173 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""strategy_period_rollup.py — 策略周期统计每日滚动派生（2026-08-15 问题2：策略数据每日自动更新）
+
+背景：
+  dashboard 研究 Tab 的 1y/2y/5y 列依赖 strategy_research 对应 period_tag 行，
+  但 s2_panic/v_lurk_v3/v_mr4 等激活策略只有 10y 记录 → 列空、health_monitor 无 5y 基线。
+  本脚本每日从「最长周期主记录」的 trades 按窗口切出 1y/2y/5y，派生行 upsert 回表。
+
+原则：
+  1. 窗口锚定主记录数据末端（max entry_date），不锚今天——回测未重跑时窗口不缩水
+  2. 不覆盖真实研究记录：只 upsert 带 derived_from 标记的派生行；真实行存在则跳过
+  3. 派生行含 calc_summary + portfolio_sim(10槽) + portfolio_full(100槽)，
+     口径与 strategy_lab.list_strategies 的 read-time 切窗一致（1m/6m/1y 已有同类逻辑）
+调度：每日盘后（策略路由后、regime_perf 前），hermes cron。
+"""
+import sys
+import json
+import sqlite3
+from pathlib import Path
+from datetime import datetime, timedelta
+from collections import Counter
+
+_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"
+
+# 目标派生周期（10y 作为主记录源，不派生）
+TARGET_PERIODS = {"1y": 365, "2y": 730, "5y": 1826}
+# 周期强度排序（选主记录用）：越长越优先
+_PERIOD_RANK = {"10y": 6, "7y": 5, "5y": 4, "2y": 3, "1y": 2, "6m": 1, "1m": 0}
+
+
+def _period_rank(tag):
+    return _PERIOD_RANK.get(tag or "2y", 3)
+
+
+def load_master_rows(conn):
+    """每个 (version, market) 取周期最长、含 trades 的记录作为主记录"""
+    rows = conn.execute(
+        "SELECT id, version, name, summary, hypothesis, parent, config_json, results_json, "
+        "period, COALESCE(market,'all'), COALESCE(period_tag,'2y') FROM strategy_research"
+    ).fetchall()
+    best = {}
+    for r in rows:
+        key = (r[1], r[9])
+        rank = _period_rank(r[10])
+        if key not in best or (rank, r[0]) > (best[key][0], best[key][1]):
+            best[key] = (rank, r[0], r)
+    return [v[2] for v in best.values()]
+
+
+def existing_real_periods(conn, version, market):
+    """该 (version, market) 已存在的【真实】period_tag（results_json 无 derived_from 标记）"""
+    rows = conn.execute(
+        "SELECT COALESCE(period_tag,'2y'), results_json FROM strategy_research "
+        "WHERE version=? AND COALESCE(market,'all')=?",
+        (version, market)).fetchall()
+    real, derived = set(), set()
+    for tag, rj in rows:
+        try:
+            d = json.loads(rj or "{}")
+        except Exception:
+            d = {}
+        if d.get("derived_from"):
+            derived.add(tag)
+        else:
+            real.add(tag)
+    return real, derived
+
+
+def derive_period(master, target_tag, days, calc_summary, portfolio_sim):
+    """从主记录切窗派生 target_tag 记录。返回 (results_dict, period_str) 或 None"""
+    res = json.loads(master["results_json"])
+    trades = res.get("trades") or []
+    if not trades:
+        return None
+    max_date = max(t.get("entry_date", "") for t in trades)
+    if not max_date:
+        return None
+    cutoff = (datetime.strptime(max_date, "%Y-%m-%d") - timedelta(days=days)).strftime("%Y-%m-%d")
+    sliced = [t for t in trades if t.get("entry_date", "") >= cutoff]
+    if not sliced:
+        return None
+    for t in sliced:
+        t.setdefault("boost", 1.0)
+    capital = res.get("capital") or 1000000
+    summary = calc_summary(sliced, capital)
+    try:
+        summary["portfolio"] = portfolio_sim(sliced, 1000000, max_positions=10)
+        summary["portfolio_full"] = portfolio_sim(sliced, 1000000, max_positions=100)
+    except Exception as e:
+        print(f"    [warn] portfolio_sim 失败({e})", flush=True)
+    year_dist = dict(Counter(t["entry_date"][:4] for t in sliced if t.get("entry_date")))
+    out = {
+        "strategy": res.get("strategy") or master["version"],
+        "strategy_name": res.get("strategy_name") or master["name"],
+        "market": res.get("market") or master["market"],
+        "period": f"{cutoff} ~ {max_date}",
+        "period_tag": target_tag,
+        "capital": capital,
+        "total_stocks_screened": None,  # 窗口派生无法还原，置空而非伪造
+        "scored_events": None,
+        "trades": sliced,
+        "summary": summary,
+        "year_dist": year_dist,
+        "derived_from": master["period_tag"],
+        "derived_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+    }
+    return out
+
+
+def main():
+    from strategy_lab import calc_summary, portfolio_sim
+
+    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    conn = sqlite3.connect(DB, timeout=60)
+    conn.execute("PRAGMA busy_timeout=60000")
+
+    masters = load_master_rows(conn)
+    print(f"[period_rollup] {now} 主记录 {len(masters)} 个 (version, market)", flush=True)
+
+    inserted = skipped_real = skipped_empty = 0
+    for m in masters:
+        master = {
+            "id": m[0], "version": m[1], "name": m[2], "summary": m[3],
+            "hypothesis": m[4], "parent": m[5], "config_json": m[6],
+            "results_json": m[7], "period": m[8], "market": m[9], "period_tag": m[10],
+        }
+        real, derived = existing_real_periods(conn, master["version"], master["market"])
+        for tag, days in TARGET_PERIODS.items():
+            if tag == master["period_tag"]:
+                continue  # 主记录本身就是该周期
+            if _period_rank(tag) >= _period_rank(master["period_tag"]):
+                continue  # 只向更短周期派生
+            if tag in real:
+                skipped_real += 1
+                continue  # 真实研究记录存在，不覆盖
+            try:
+                res = derive_period(master, tag, days, calc_summary, portfolio_sim)
+            except Exception as e:
+                print(f"  [err] {master['version']}/{master['market']}/{tag}: {e}", flush=True)
+                continue
+            if not res:
+                skipped_empty += 1
+                continue
+            # 删旧派生行，插新派生行（保持每日最新）
+            conn.execute(
+                "DELETE FROM strategy_research WHERE version=? AND COALESCE(market,'all')=? "
+                "AND COALESCE(period_tag,'2y')=? AND results_json LIKE '%\"derived_from\"%'",
+                (master["version"], master["market"], tag))
+            conn.execute(
+                "INSERT INTO strategy_research "
+                "(version, name, summary, hypothesis, parent, config_json, results_json, "
+                " analysis_json, period, created_at, market, period_tag) "
+                "VALUES (?,?,?,?,?,?,?,?,?,?,?,?)",
+                (master["version"], master["name"], master["summary"], master["hypothesis"],
+                 master["parent"], master["config_json"], json.dumps(res, ensure_ascii=False),
+                 json.dumps({"derived": True, "from": master["period_tag"]}, ensure_ascii=False),
+                 res["period"], now, master["market"], tag))
+            inserted += 1
+            s = res["summary"]
+            print(f"  + {master['version']:<14} {master['market']:<3} {tag}: "
+                  f"{s.get('total_trades')}笔 胜率{s.get('win_rate')}% (派生自{master['period_tag']})", flush=True)
+    conn.commit()
+    conn.close()
+    print(f"[period_rollup] 完成: 派生写入 {inserted} 行 | 真实记录跳过 {skipped_real} | 空窗跳过 {skipped_empty}", flush=True)
+
+
+if __name__ == "__main__":
+    main()