shuim
a264561576
- 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
83 lines
3.0 KiB
Python
83 lines
3.0 KiB
Python
"""walk_forward: 실전 청산 모델(kr_backtest_engine)을 돌리고, 엔진이 소비하는 키만 탐색한다."""
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import asyncio
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from datetime import date
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import pytest
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from app.core.config import settings
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from app.services import walk_forward as wf
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from app.services.kr_backtest_engine import (
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BacktestMetrics, BacktestResult, KrBacktestEngine, MeanReversionBacktest,
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)
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class _Trial:
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def __init__(self):
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self.suggested = []
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def suggest_int(self, name, lo, hi):
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self.suggested.append(name)
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return lo
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def suggest_float(self, name, lo, hi, step=None):
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self.suggested.append(name)
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return lo
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def _cfg(**kw):
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return wf.WalkForwardConfig(stock_codes=["005930"], start_date=date(2025, 1, 1),
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end_date=date(2025, 12, 31), **kw)
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@pytest.fixture(autouse=True)
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def _block_toy_engine(monkeypatch):
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"""구 장난감 엔진 호출은 즉시 예외 (거짓 통과 방지)."""
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import app.services.backtest_engine as toy
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def boom(*a, **k):
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raise AssertionError("장난감 backtest_engine 사용")
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monkeypatch.setattr(toy.BacktestEngine, "run_backtest", boom)
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def test_search_space_only_engine_consumed_keys():
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t = _Trial()
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params = wf.WalkForwardOptimizer()._build_params_from_trial_v2(t)
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consumed = set(MeanReversionBacktest().default_params())
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assert set(params) <= consumed, set(params) - consumed
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assert "MEAN_REVERSION_RSI_THRESHOLD" not in params
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assert params["stop_loss_pct"] > 0
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def test_run_uses_kr_engine_and_normalizes_units(monkeypatch):
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seen = {}
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async def fake_run(self, **kw):
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seen.update(kw)
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return BacktestResult(metrics=BacktestMetrics(
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total_return_pct=10.0, max_drawdown_pct=-5.0, win_rate=60.0,
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sharpe_ratio=1.2, total_trades=7))
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monkeypatch.setattr(KrBacktestEngine, "run", fake_run)
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out = asyncio.run(wf.WalkForwardOptimizer()._run_single_backtest_v2(
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["005930"], date(2025, 1, 1), date(2025, 6, 1),
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{"bb_period": 20}, _cfg(position_size=0.5, max_positions=99)))
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assert out["mdd_pct"] == pytest.approx(-0.05)
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assert out["win_rate"] == pytest.approx(0.6)
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assert out["total_return_pct"] == pytest.approx(0.10)
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assert out["total_trades"] == 7
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assert seen["params"]["position_size_pct"] <= settings.MAX_POSITION_SIZE
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assert seen["params"]["max_positions"] <= settings.MAX_HOLDINGS_COUNT
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def test_default_params_from_settings():
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d = wf.WalkForwardOptimizer._default_params_v2()
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assert d["stop_loss_pct"] == abs(settings.STOP_LOSS_PERCENT)
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assert d["atr_stop_multiplier"] == settings.ATR_STOP_MULTIPLIER
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def test_recommended_params_keys():
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wr = wf.WindowResult(0, "a", "b", "c", "d", {"bb_period": 18, "atr_stop_multiplier": 2.0,
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"stop_loss_pct": 5.0}, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0.0, False)
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rec = wf.WalkForwardOptimizer()._compute_recommended_params([wr])
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assert rec == {"bb_period": 18, "atr_stop_multiplier": 2.0, "stop_loss_pct": 5.0}
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