9ba9ab73b6
- Web UI: - Optuna 탭 추가 및 mode_combo (최빈값 조합), 사후합격 Top 10 시각화 기능 - 파라미터 분포(p25~p75, median, mode) 히스토그램 및 과적합(Overfit) 위험도 진단 UI 신설 - 체크박스 렌더링 깨짐 현상을 네이티브(appearance: auto)로 강제 복구 (CSS) - 다단 트레일링 스탑, 꼬리 진입/돌파 손절 등 고급 조건 설정 폼 UI 고도화 - Backend (Optuna Jobs): - CLI 환경에서 구동된 Optuna json 결과물을 웹 대시보드로 읽어오는 import 기능 강화 - JSON 메타데이터에 sort_by, mode, 호가 적용 여부 등 핵심 파라미터 파싱 누락 수정 - optuna_mode_combo.py 등 최빈값 조합 및 후보군 2차 검증을 위한 신규 모듈 추가 - DB & Execution: - WebSocket 호가/틱 피드 수집 통계(api_feed_collect_stats) 메모리 캐시 최적화 - KIS client 접속 키(approval_key) 등 인프라스트럭처 안정성 및 공유 관리 구조 개선 - 테스트 및 디버깅용 briefing 마크다운 자동 생성 기능 추가
443 lines
15 KiB
Python
443 lines
15 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
kis_trader/backtest/optuna_mode_refine_runner.py — 1·2차 TPE 연쇄 (기간=폼 start/end)
|
|
=====================================================================================
|
|
1차: 넓은 Grid TPE → JSON
|
|
2차: 1차 JSON 밴드로 Grid 축소 + 동일 기간 TPE
|
|
|
|
웹: start_optuna_job(단일) · run_optuna_4strat_tpe_seq.sh(순차) → subprocess 본 스크립트.
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import argparse
|
|
import json
|
|
import logging
|
|
import os
|
|
import subprocess
|
|
import sys
|
|
import time
|
|
from datetime import datetime
|
|
from pathlib import Path
|
|
from typing import Any, Dict, List, Optional
|
|
|
|
ROOT = Path(__file__).resolve().parents[2]
|
|
if str(ROOT) not in sys.path:
|
|
sys.path.insert(0, str(ROOT))
|
|
|
|
logger = logging.getLogger("optuna_mode_refine")
|
|
|
|
|
|
def _py() -> str:
|
|
cand = ROOT / ".venv" / "bin" / "python3"
|
|
if cand.is_file():
|
|
return str(cand)
|
|
return sys.executable
|
|
|
|
|
|
def _read_json(path: str) -> Dict[str, Any]:
|
|
return json.loads(Path(path).read_text(encoding="utf-8"))
|
|
|
|
|
|
def _load_phase1_data(
|
|
*,
|
|
strategy: str,
|
|
phase1_json: Optional[str] = None,
|
|
phase1_study: Optional[str] = None,
|
|
) -> tuple:
|
|
"""1차 narrow 입력. DB(study) 우선, 없으면 JSON 파일. (data, source_label)."""
|
|
study = str(phase1_study or "").strip()
|
|
if study:
|
|
from kis_trader.backtest.optuna_study_store import load_payload_dict, payload_has_rows
|
|
|
|
data = load_payload_dict(study)
|
|
if data and payload_has_rows(data):
|
|
logger.info("📌 1차 payload DB study=%s", study)
|
|
return data, f"db:{study}"
|
|
logger.warning("⚠️ DB payload 없음 study=%s — JSON 폴백 시도", study)
|
|
path = str(phase1_json or "").strip()
|
|
if path and Path(path).is_file():
|
|
return _read_json(path), path
|
|
if study:
|
|
found = _find_json_by_study(study, strategy)
|
|
if found and Path(found).is_file():
|
|
return _read_json(found), found
|
|
raise FileNotFoundError(
|
|
f"1차 payload 없음 (study={study or '-'}, json={path or '-'})"
|
|
)
|
|
|
|
|
|
def _persist_phase1_to_db(data: Dict[str, Any], *, job_id: str, study_name: str) -> None:
|
|
"""1차 JSON → optuna_study_result (다른 PC 2차용)."""
|
|
try:
|
|
from kis_trader.backtest.optuna_study_store import ingest_out_data
|
|
|
|
out = ingest_out_data(data, job_id=job_id, replace=False)
|
|
logger.info("📌 1차 DB 저장 study=%s ok=%s", study_name, out.get("ok"))
|
|
except Exception as exc:
|
|
logger.warning("⚠️ 1차 DB 저장 실패 study=%s: %s", study_name, exc)
|
|
|
|
|
|
def _write_state(path: Path, state: Dict[str, Any]) -> None:
|
|
path.parent.mkdir(parents=True, exist_ok=True)
|
|
path.write_text(json.dumps(state, indent=2, ensure_ascii=False), encoding="utf-8")
|
|
|
|
|
|
def _find_json_by_study(study_name: str, strategy: str) -> Optional[str]:
|
|
from kis_trader.backtest.tail_param_search import _results_dir_for_write
|
|
|
|
out_dir = Path(_results_dir_for_write())
|
|
if not out_dir.is_dir():
|
|
return None
|
|
cands: List[Path] = []
|
|
patterns = [
|
|
f"optuna_{strategy}_*.json",
|
|
f"optuna_{strategy[:4]}_*.json",
|
|
"optuna_*.json",
|
|
]
|
|
seen: set = set()
|
|
for pat in patterns:
|
|
for p in out_dir.glob(pat):
|
|
if str(p) in seen:
|
|
continue
|
|
seen.add(str(p))
|
|
try:
|
|
d = json.loads(p.read_text(encoding="utf-8"))
|
|
except Exception:
|
|
continue
|
|
if str(d.get("optuna_study_name") or "") == study_name:
|
|
cands.append(p)
|
|
if not cands:
|
|
return None
|
|
cands.sort(key=lambda p: p.stat().st_mtime, reverse=True)
|
|
return str(cands[0])
|
|
|
|
|
|
def _build_optuna_cmd(
|
|
*,
|
|
strategy: str,
|
|
mode: str,
|
|
start: str,
|
|
end: str,
|
|
trials: int,
|
|
study_name: str,
|
|
sort_by: str,
|
|
min_trades: int,
|
|
hist_src: str,
|
|
entry_mode: Optional[str] = None,
|
|
sl_mode: Optional[str] = None,
|
|
ob_mode: Optional[str] = None,
|
|
symbol: Optional[str] = None,
|
|
candle_source: Optional[str] = None,
|
|
tick_source: Optional[str] = None,
|
|
ob_source: Optional[str] = None,
|
|
study_trials: Optional[int] = None,
|
|
) -> List[str]:
|
|
cmd = [
|
|
_py(), "-u",
|
|
str(ROOT / "kis_trader" / "backtest" / "param_search_optuna.py"),
|
|
"--strategy", strategy,
|
|
"--mode", mode,
|
|
"--start", start,
|
|
"--end", end,
|
|
"--trials", str(int(trials)),
|
|
"--min_trades", str(int(min_trades)),
|
|
"--min_win_rate", "0",
|
|
"--min_pf", "0",
|
|
"--no-progress",
|
|
"--study-name", study_name,
|
|
"--sort-by", sort_by,
|
|
"--universe-history-source", hist_src,
|
|
]
|
|
if strategy == "tail" and entry_mode:
|
|
cmd.extend(["--entry-mode", entry_mode])
|
|
if strategy == "breakout":
|
|
cmd.extend(["--sl-mode", sl_mode or "fixed"])
|
|
cmd.extend(["--orderbook-filter", ob_mode or "off"])
|
|
if symbol and strategy == "us_momentum":
|
|
cmd.extend(["--symbol", symbol])
|
|
if candle_source:
|
|
cmd.extend(["--candle-source", candle_source])
|
|
if tick_source:
|
|
cmd.extend(["--tick-source", tick_source])
|
|
if ob_source:
|
|
cmd.extend(["--ob-source", ob_source])
|
|
if study_trials and int(study_trials) > 0:
|
|
cmd.extend(["--study-trials", str(int(study_trials))])
|
|
return cmd
|
|
|
|
|
|
def _run_phase(
|
|
cmd: List[str],
|
|
env: Dict[str, str],
|
|
log_path: Path,
|
|
) -> int:
|
|
log_path.parent.mkdir(parents=True, exist_ok=True)
|
|
with open(log_path, "w", encoding="utf-8") as log_f:
|
|
log_f.write("CMD: %s\n\n" % " ".join(cmd))
|
|
log_f.flush()
|
|
proc = subprocess.Popen(
|
|
cmd,
|
|
cwd=str(ROOT),
|
|
env=env,
|
|
stdout=log_f,
|
|
stderr=subprocess.STDOUT,
|
|
)
|
|
return int(proc.wait())
|
|
|
|
|
|
def run_mode_refine(
|
|
*,
|
|
job_id: str,
|
|
strategy: str,
|
|
mode: str,
|
|
start: str,
|
|
end: str,
|
|
trials: int,
|
|
sort_by: str,
|
|
min_trades: int,
|
|
hist_src: str,
|
|
entry_mode: Optional[str] = None,
|
|
sl_mode: Optional[str] = None,
|
|
ob_mode: Optional[str] = None,
|
|
symbol: Optional[str] = None,
|
|
candle_source: Optional[str] = None,
|
|
tick_source: Optional[str] = None,
|
|
ob_source: Optional[str] = None,
|
|
study_trials: Optional[int] = None,
|
|
skip_phase1: bool = False,
|
|
phase1_json: Optional[str] = None,
|
|
phase1_study: Optional[str] = None,
|
|
) -> Dict[str, Any]:
|
|
from kis_trader.backtest.optuna_grid_narrow import (
|
|
build_and_write_narrow_grid,
|
|
resolve_refine_phase2_trials,
|
|
)
|
|
from kis_trader.backtest.optuna_mode_combo import resolve_mode_pool_kind
|
|
|
|
ts = datetime.now().strftime("%Y%m%d_%H%M%S")
|
|
state_path = ROOT / "logs" / f"{job_id}_refine_state.json"
|
|
narrow_path = ROOT / "logs" / f"{job_id}_narrow_grid.json"
|
|
state: Dict[str, Any] = {
|
|
"job_id": job_id,
|
|
"strategy": strategy,
|
|
"mode": mode,
|
|
"start": start,
|
|
"end": end,
|
|
"phase": "phase1",
|
|
"pool_kind": resolve_mode_pool_kind(),
|
|
}
|
|
_write_state(state_path, state)
|
|
|
|
env = os.environ.copy()
|
|
env["PYTHONUNBUFFERED"] = "1"
|
|
env["PYTHONPATH"] = str(ROOT) + (os.pathsep + env.get("PYTHONPATH", ""))
|
|
env["BACKTEST_UNIVERSE_HISTORY_SOURCE"] = hist_src
|
|
env["PARAM_SEARCH_OPTUNA_REPORT_MIN_TRADES"] = str(min_trades)
|
|
env["SORT_BY"] = sort_by
|
|
env["OPTUNA_WEB_JOB_ID"] = str(job_id)
|
|
env.pop("OPTUNA_GRID_NARROW_JSON", None)
|
|
|
|
p1_study_arg = str(phase1_study or "").strip()
|
|
p1_study = f"{strategy}_{mode}_refine1_{start.replace('-', '')}_{end.replace('-', '')}_{ts}"
|
|
p1_log = ROOT / "logs" / f"optuna_refine1_{job_id}.log"
|
|
p1_json = str(phase1_json or "").strip()
|
|
|
|
if skip_phase1 and (p1_study_arg or (p1_json and Path(p1_json).is_file())):
|
|
logger.info("⏭ 1차 스킵 — study=%s json=%s", p1_study_arg or "-", p1_json or "-")
|
|
data, src = _load_phase1_data(
|
|
strategy=strategy,
|
|
phase1_json=p1_json or None,
|
|
phase1_study=p1_study_arg or None,
|
|
)
|
|
p1_study = str(
|
|
p1_study_arg
|
|
or data.get("optuna_study_name")
|
|
or data.get("study_name")
|
|
or p1_study
|
|
).strip()
|
|
state["phase1_study"] = p1_study
|
|
state["phase1_json"] = p1_json or src
|
|
state["phase1_source"] = src
|
|
state["phase1_skipped"] = True
|
|
else:
|
|
cmd1 = _build_optuna_cmd(
|
|
strategy=strategy,
|
|
mode=mode,
|
|
start=start,
|
|
end=end,
|
|
trials=trials,
|
|
study_name=p1_study,
|
|
sort_by=sort_by,
|
|
min_trades=min_trades,
|
|
hist_src=hist_src,
|
|
entry_mode=entry_mode,
|
|
sl_mode=sl_mode,
|
|
ob_mode=ob_mode,
|
|
symbol=symbol,
|
|
candle_source=candle_source,
|
|
tick_source=tick_source,
|
|
ob_source=ob_source,
|
|
study_trials=study_trials,
|
|
)
|
|
state["phase1_study"] = p1_study
|
|
state["phase1_log"] = str(p1_log)
|
|
state["phase"] = "phase1"
|
|
_write_state(state_path, state)
|
|
logger.info("▶ 1차 TPE 시작 study=%s %s~%s trials=%s", p1_study, start, end, trials)
|
|
rc1 = _run_phase(cmd1, env, p1_log)
|
|
state["phase1_exit"] = rc1
|
|
state["phase1_log"] = str(p1_log)
|
|
state["phase1_study"] = p1_study
|
|
_write_state(state_path, state)
|
|
if rc1 != 0:
|
|
state["phase"] = "error"
|
|
state["error"] = f"phase1 exit {rc1}"
|
|
_write_state(state_path, state)
|
|
return state
|
|
p1_json = _find_json_by_study(p1_study, strategy) or ""
|
|
if not p1_json or not Path(p1_json).is_file():
|
|
state["phase"] = "error"
|
|
state["error"] = "phase1 JSON not found"
|
|
_write_state(state_path, state)
|
|
return state
|
|
state["phase1_json"] = p1_json
|
|
state["phase1_study"] = p1_study
|
|
print(f"OPTUNA_PHASE1_STUDY={p1_study}", flush=True)
|
|
try:
|
|
_persist_phase1_to_db(_read_json(p1_json), job_id=job_id, study_name=p1_study)
|
|
except Exception:
|
|
pass
|
|
|
|
try:
|
|
data = _load_phase1_data(
|
|
strategy=strategy,
|
|
phase1_json=p1_json or None,
|
|
phase1_study=str(state.get("phase1_study") or p1_study_arg or "").strip() or None,
|
|
)[0]
|
|
except FileNotFoundError as exc:
|
|
state["phase"] = "error"
|
|
state["error"] = str(exc)
|
|
_write_state(state_path, state)
|
|
return state
|
|
|
|
if state.get("phase1_skipped"):
|
|
p1_study = str(state.get("phase1_study") or p1_study).strip()
|
|
state["phase1_study"] = p1_study
|
|
data["mode_pool_kind"] = resolve_mode_pool_kind()
|
|
narrow_meta = build_and_write_narrow_grid(
|
|
data, str(narrow_path), mode=mode, strategy=strategy,
|
|
)
|
|
state["narrow_grid"] = narrow_meta
|
|
state["narrow_path"] = str(narrow_path)
|
|
|
|
p2_trials = resolve_refine_phase2_trials(trials)
|
|
p2_study = f"{strategy}_{mode}_refine2_{start.replace('-', '')}_{end.replace('-', '')}_{ts}"
|
|
p2_log = ROOT / "logs" / f"optuna_refine2_{job_id}.log"
|
|
env2 = dict(env)
|
|
env2["OPTUNA_GRID_NARROW_JSON"] = str(narrow_path)
|
|
|
|
cmd2 = _build_optuna_cmd(
|
|
strategy=strategy,
|
|
mode=mode,
|
|
start=start,
|
|
end=end,
|
|
trials=p2_trials,
|
|
study_name=p2_study,
|
|
sort_by=sort_by,
|
|
min_trades=min_trades,
|
|
hist_src=hist_src,
|
|
entry_mode=entry_mode,
|
|
sl_mode=sl_mode,
|
|
ob_mode=ob_mode,
|
|
symbol=symbol,
|
|
candle_source=candle_source,
|
|
tick_source=tick_source,
|
|
ob_source=ob_source,
|
|
study_trials=study_trials,
|
|
)
|
|
logger.info(
|
|
"▶ 2차 TPE(밴드축소) study=%s trials=%s narrow=%s",
|
|
p2_study, p2_trials, narrow_path,
|
|
)
|
|
state["phase"] = "phase2"
|
|
state["phase2_study"] = p2_study
|
|
state["phase2_log"] = str(p2_log)
|
|
state["phase2_trials"] = p2_trials
|
|
_write_state(state_path, state)
|
|
rc2 = _run_phase(cmd2, env2, p2_log)
|
|
state["phase2_exit"] = rc2
|
|
state["phase2_log"] = str(p2_log)
|
|
state["phase2_study"] = p2_study
|
|
state["phase2_trials"] = p2_trials
|
|
p2_json = _find_json_by_study(p2_study, strategy) or ""
|
|
if p2_json:
|
|
state["phase2_json"] = p2_json
|
|
state["result_json"] = p2_json
|
|
state["phase"] = "done" if rc2 == 0 else "error"
|
|
if rc2 != 0:
|
|
state["error"] = f"phase2 exit {rc2}"
|
|
state["finished_at"] = datetime.now().isoformat(timespec="seconds")
|
|
_write_state(state_path, state)
|
|
return state
|
|
|
|
|
|
def main() -> int:
|
|
logging.basicConfig(
|
|
level=logging.INFO,
|
|
format="%(asctime)s %(levelname)s %(message)s",
|
|
)
|
|
ap = argparse.ArgumentParser(description="Optuna 1·2차 TPE 연쇄 (밴드 축소 2차)")
|
|
ap.add_argument("--job-id", required=True)
|
|
ap.add_argument("--strategy", required=True)
|
|
ap.add_argument("--mode", default="tpe")
|
|
ap.add_argument("--start", required=True)
|
|
ap.add_argument("--end", required=True)
|
|
ap.add_argument("--trials", type=int, default=200)
|
|
ap.add_argument("--sort-by", default="score")
|
|
ap.add_argument("--min-trades", type=int, default=1)
|
|
ap.add_argument("--universe-history-source", default="kiwoom")
|
|
ap.add_argument("--entry-mode", default="")
|
|
ap.add_argument("--sl-mode", default="fixed")
|
|
ap.add_argument("--ob-mode", default="off")
|
|
ap.add_argument("--symbol", default="")
|
|
ap.add_argument("--candle-source", default="")
|
|
ap.add_argument("--tick-source", default="")
|
|
ap.add_argument("--ob-source", default="")
|
|
ap.add_argument("--study-trials", type=int, default=0)
|
|
ap.add_argument("--skip-phase1", action="store_true")
|
|
ap.add_argument("--phase1-json", default="")
|
|
ap.add_argument("--phase1-study", default="", help="1차 study — MariaDB payload (다른 PC 2차)")
|
|
args = ap.parse_args()
|
|
|
|
st = run_mode_refine(
|
|
job_id=str(args.job_id),
|
|
strategy=str(args.strategy).strip().lower(),
|
|
mode=str(args.mode).strip().lower() or "tpe",
|
|
start=str(args.start).strip(),
|
|
end=str(args.end).strip(),
|
|
trials=max(1, int(args.trials)),
|
|
sort_by=str(args.sort_by or "score"),
|
|
min_trades=max(1, int(args.min_trades)),
|
|
hist_src=str(args.universe_history_source or "kiwoom").strip().lower(),
|
|
entry_mode=str(args.entry_mode or "").strip() or None,
|
|
sl_mode=str(args.sl_mode or "fixed").strip() or "fixed",
|
|
ob_mode=str(args.ob_mode or "off").strip() or "off",
|
|
symbol=str(args.symbol or "").strip().upper() or None,
|
|
candle_source=str(args.candle_source or "").strip().lower() or None,
|
|
tick_source=str(args.tick_source or "").strip().lower() or None,
|
|
ob_source=str(args.ob_source or "").strip().lower() or None,
|
|
study_trials=int(args.study_trials) if int(args.study_trials or 0) > 0 else None,
|
|
skip_phase1=bool(args.skip_phase1),
|
|
phase1_json=str(args.phase1_json or "").strip() or None,
|
|
phase1_study=str(args.phase1_study or "").strip() or None,
|
|
)
|
|
if st.get("phase") == "done":
|
|
logger.info("✅ 1·2차 완료 result=%s", st.get("result_json"))
|
|
return 0
|
|
logger.error("❌ 1·2차 실패: %s", st.get("error"))
|
|
return 1
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise SystemExit(main())
|