fix: 하드닝 루프 8회차 — 체결 보정·고아 감지·청산 경보·실시간/차트·리스크 가드 일괄 수정

- 스윙 체결가 확인 전 executed_price NULL + fill_sweep, 진입가 resolve(ActiveTrade↔Portfolio), 0체결/부분체결 매수 장부 원복
- DT 고아 감지(근거 한정)·0체결 매도 복원·stale 점검 확대, 시간손절 -0.3% 원복
- 폴백 손절 ATR 캐시, 거래량부족-차단 신호 매수 차단, 현금 5% 유보 재적용, MDD peak/reset 수정
- KIS 서킷브레이커 청산 우회·경보, db_worker 재큐잉 순서, heartbeat·health-watch 사이드카
- 실시간 WS 재구독·41건 우선순위·다건 프레임 분할, 차트 샘플 제거·당일봉 합성, WS 서브프로토콜 인증
- 프론트: 미관리 그룹·확인 모달·차트 실시간 반영·예수금 표시 정정
- 전문가 에이전트 6종 추가(.claude/agents)
- 유닛 스위트 2667 passed (소켓 차단 하), tsc OK

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y83Za98XsNw9zuA4FTUytN

backend/tests/test_ml_retrain_price_fallback.py

@@ -0,0 +1,120 @@
+from types import SimpleNamespace as NS
+
+from app.services.ml_retrain_pipeline import _resolve_trade_price_v2
+
+
+def test_executed_price_preferred():
+    assert _resolve_trade_price_v2(NS(executed_price=100, total_amount=1, executed_quantity=1, order_price=5)) == 100.0
+
+
+def test_null_falls_back_to_amount_over_qty():
+    assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=1000, executed_quantity=10, order_price=5)) == 100.0
+
+
+def test_null_falls_back_to_order_price():
+    assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=None, executed_quantity=None, order_price=55)) == 55.0
+
+
+def test_all_missing_zero():
+    assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=None, executed_quantity=None, order_price=None)) == 0.0
+
+
+# ─── 라운드4: 성능 저하 감시 / 장중 재학습 방지 ───────────────────────────
+import asyncio
+from datetime import datetime
+
+import pandas as pd
+import pytest
+
+from app.services import ml_retrain_pipeline as mrp
+
+
+def test_filled_statuses_include_completed():
+    assert "COMPLETED" in mrp._FILLED_TRADE_STATUSES
+
+
+def test_load_trade_history_filters_completed(monkeypatch):
+    captured = {}
+
+    class _Res:
+        def scalars(self):
+            return self
+
+        def all(self):
+            return []
+
+    class _Sess:
+        async def __aenter__(self):
+            return self
+
+        async def __aexit__(self, *a):
+            return False
+
+        async def execute(self, stmt):
+            captured["sql"] = str(stmt.compile(compile_kwargs={"literal_binds": True}))
+            return _Res()
+
+    monkeypatch.setattr(mrp, "AsyncSessionLocal", lambda: _Sess())
+    asyncio.run(mrp._load_trade_history(months=1))
+    assert "COMPLETED" in captured["sql"]
+
+
+@pytest.mark.parametrize(
+    "dt,expected",
+    [
+        (datetime(2026, 10, 7, 9, 30), False),   # 수 장중
+        (datetime(2026, 10, 7, 15, 0), False),
+        (datetime(2026, 10, 7, 20, 0), True),    # 수 야간
+        (datetime(2026, 10, 7, 3, 0), True),
+        (datetime(2026, 10, 10, 11, 0), True),   # 토
+    ],
+)
+def test_safe_window(dt, expected):
+    assert mrp._is_retrain_safe_window_v2(dt) is expected
+
+
+def test_run_retrain_builds_features_in_thread(monkeypatch):
+    seen = {}
+
+    async def fake_load(months=6):
+        return pd.DataFrame({"stock_code": ["A"], "close": [1.0]})
+
+    def fake_build(df):
+        import threading
+        seen["thread"] = threading.current_thread()
+        return [], []
+
+    monkeypatch.setattr(mrp, "_load_daily_prices", fake_load)
+    monkeypatch.setattr(mrp, "_build_training_lists_impl", fake_build)
+    import threading
+    res = asyncio.run(mrp.run_retrain(force=True))
+    assert res["status"] == "skipped"
+    assert seen["thread"] is not threading.main_thread()
+
+
+def test_scheduler_defers_retrain_during_market_hours(monkeypatch):
+    calls = {"retrain": 0}
+
+    async def fake_check():
+        return True, {"degraded": True}
+
+    async def fake_retrain(*a, **k):
+        calls["retrain"] += 1
+        return {"status": "completed"}
+
+    class _FakeDT(datetime):
+        @classmethod
+        def now(cls, tz=None):
+            return cls(2026, 10, 7, 9, 45, tzinfo=tz)
+
+    async def fake_sleep(sec):
+        if sec == 3600:
+            raise asyncio.CancelledError
+
+    monkeypatch.setattr(mrp, "check_performance_degradation", fake_check)
+    monkeypatch.setattr(mrp, "run_retrain", fake_retrain)
+    monkeypatch.setattr(mrp, "datetime", _FakeDT)
+    monkeypatch.setattr(mrp.asyncio, "sleep", fake_sleep)
+    with pytest.raises(asyncio.CancelledError):
+        asyncio.run(mrp.ml_retrain_scheduler())
+    assert calls["retrain"] == 0