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feat(옵투나): score·min_trades·후처리 재탐색 및 웹 job 개선

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PnL/(MDD+ADD) score·legacy 정렬·거래일×min_trades 게이트를 공통화한다.
후처리 ob_modes·study store·4전략 TPE 순차 스크립트와 문서를 갱신한다.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Your Name
2026-08-28 16:46:27 +09:00
parent a0fe66bc11
commit 1387fbdf47
10 changed files with 583 additions and 136 deletions
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24
kis_trader/backtest/optuna_breakout.py
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@@ -385,7 +385,7 @@ def run_breakout_optuna(
min_trades: int,
min_win_rate: float,
min_pf: float,
sort_by: str = "pnl",
sort_by: str = "score",
sampler_name: str = "tpe",
seed: Optional[int] = None,
n_jobs: int = 1,
@@ -441,16 +441,18 @@ def run_breakout_optuna(
if result is None:
trial.set_user_attr("gates_ok", False)
return _FAIL_OBJECTIVE
obj = float(result["win_rate"]) if sort_by == "win_rate" else float(result["total_pnl"])
trial.set_user_attr("gates_ok", True)
trial.set_user_attr("total_pnl", float(result["total_pnl"]))
trial.set_user_attr("win_rate", float(result["win_rate"]))
trial.set_user_attr("pf", float(result.get("pf") or 0))
trial.set_user_attr("mdd", float(result.get("mdd") or 0))
trial.set_user_attr("total_trades", int(result["total_trades"]))
trial.set_user_attr("merged_json", json.dumps(result.get("merged_params") or {}, ensure_ascii=False))
from kis_trader.backtest.optuna_common import optuna_store_trial_score_user_attrs
set_optuna_trial_stability_attrs(trial, result)
return obj
return optuna_store_trial_score_user_attrs(
trial, result, sort_by, start=ctx.start, end=ctx.end, strategy="breakout",
)
logger.info("🔬 Optuna BREAKOUT | study=%s | trials=%d", study_name, n_trials)
t0 = time.time()
try:
@@ -466,6 +468,7 @@ def run_breakout_optuna(
)
elapsed = time.time() - t0
from kis_trader.backtest.optuna_common import optuna_score_fields_from_trial
passing: List[Dict[str, Any]] = []
for trial in study.trials:
if trial.state != optuna.trial.TrialState.COMPLETE:
@@ -484,15 +487,16 @@ def run_breakout_optuna(
"win_rate": float(trial.user_attrs.get("win_rate") or 0),
"total_pnl": float(trial.user_attrs.get("total_pnl") or 0),
"pf": float(trial.user_attrs.get("pf") or 0),
"mdd": float(trial.user_attrs.get("mdd") or 0),
**optuna_score_fields_from_trial(trial),
"period_daily_avg_pnl": float(trial.user_attrs.get("period_daily_avg_pnl") or 0),
"optuna_trial_number": trial.number,
}
row.update(stability_fields_from_trial_attrs(trial))
passing.append(row)
if sort_by == "win_rate":
passing.sort(key=lambda r: (-r["win_rate"], -r["total_pnl"]))
else:
passing.sort(key=lambda r: (-r["total_pnl"], -r["win_rate"]))
from kis_trader.backtest.optuna_common import _sort_optuna_rows
passing = _sort_optuna_rows(passing, sort_by)
tiers = build_optuna_result_tiers(passing, sort_by=sort_by)
hints: Dict[str, str] = {}
@@ -521,6 +525,8 @@ def run_breakout_optuna(
"elapsed_sec": round(elapsed, 1),
**tiers,
}
from kis_trader.backtest.optuna_common import annotate_optuna_period_daily_avg
annotate_optuna_period_daily_avg(out_data)
ts = datetime.now().strftime("%Y%m%d_%H%M%S")
out_path = os.path.join(_results_dir_for_write(), f"optuna_breakout_{ctx.mode}_{ts}.json")
@@ -592,7 +598,7 @@ def run_breakout_optuna(
def apply_best_breakout_trial(study: optuna.Study) -> bool:
trial = pick_gated_apply_trial(study, sort_by="pnl", fail_objective=_FAIL_OBJECTIVE)
trial = pick_gated_apply_trial(study, sort_by="score", fail_objective=_FAIL_OBJECTIVE)
if trial is None:
logger.warning(
"⚠️ 사후게이트(results_gated) 통과 trial 없음 — DB 미적용"