Files
QuantEngineByItz/tools/build_continuous_evaluation_dashboard_v1.py
kjh2064 55debd98a4 feat: 성과 모니터링 대시보드 Excel(xlsx) 출력 주입 기능 보완 (2026-06-13)
주요 변경 사항:
- tools/build_continuous_evaluation_dashboard_v1.py 수정:
  * openpyxl을 사용해 JSON 대시보드 산출 결과를 GatherTradingData.xlsx의 evaluation_dashboard 시트에 실시간 기입하도록 연동
  * 기존 데이터 자동 클리어 및 주간 스코어카드 테이블 D~H열 병렬 기입 구현
- 검증 결과: python tools/build_continuous_evaluation_dashboard_v1.py 정상 구동 및 Excel 저장 완료

Co-Authored-By: Antigravity AI <noreply@google.com>
2026-06-13 18:46:33 +09:00

228 lines
9.9 KiB
Python

"""build_continuous_evaluation_dashboard_v1.py — CONTINUOUS_EVALUATION_DASHBOARD_V1
P2-020: 주간 성과 대시보드.
- LIVE T+20 표본에서 기대수익/승률/MDD/수익반납 지표 산출
- REPLAY 표본은 informational 섹션에만 집계 (성과 계산 혼입 금지)
- T+20 미확정 → None으로 표기, INSUFFICIENT_DATA 게이트
"""
from __future__ import annotations
import argparse
import json
from collections import defaultdict
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
from v7_hardening_common import ROOT, TEMP, load_json, save_json
DEFAULT_HIST = ROOT / "Temp" / "proposal_evaluation_history.json"
DEFAULT_OUT = TEMP / "continuous_evaluation_dashboard_v1.json"
MIN_T20_FOR_METRICS = 30 # 성과 지표 신뢰성 최소 표본 수
_REPLAY_ORIGINS = {"REPLAY_FROM_KRX_EOD", "HISTORICAL_REPLAY", "BACKTEST"}
_REPLAY_VALIDATION = {"REPLAY", "HISTORICAL_REPLAY"}
def _is_replay(r: dict) -> bool:
return (
str(r.get("data_origin") or "").upper() in _REPLAY_ORIGINS
or str(r.get("validation_status") or "").upper() in _REPLAY_VALIDATION
or str(r.get("record_type") or "").upper().startswith("HISTORICAL_REPLAY")
)
def _is_evaluated_t20(r: dict) -> bool:
return (
r.get("t20_evaluation_status") == "EVALUATED_T20"
and r.get("t20_return_pct") is not None
)
def _iso_week(date_str: str | None) -> str | None:
if not date_str:
return None
try:
dt = datetime.strptime(str(date_str)[:10], "%Y-%m-%d")
return dt.strftime("%G-W%V")
except ValueError:
return None
def _compute_metrics(t20_returns: list[float]) -> dict[str, Any]:
if not t20_returns:
return {
"expectancy_pct": None,
"win_rate_pct": None,
"max_drawdown_pct": None,
"trade_count": 0,
}
wins = [r for r in t20_returns if r > 0]
return {
"expectancy_pct": round(sum(t20_returns) / len(t20_returns), 4),
"win_rate_pct": round(len(wins) / len(t20_returns) * 100, 2),
"max_drawdown_pct": round(min(t20_returns), 4),
"trade_count": len(t20_returns),
}
def _build_weekly_scorecard(live_eval: list[dict]) -> list[dict]:
weeks: dict[str, list[float]] = defaultdict(list)
for r in live_eval:
week = _iso_week(r.get("proposal_date") or r.get("created_at"))
if week:
weeks[week].append(float(r["t20_return_pct"]))
scorecard = []
for week in sorted(weeks.keys()):
returns = weeks[week]
m = _compute_metrics(returns)
m["week"] = week
scorecard.append(m)
return scorecard
def main() -> int:
ap = argparse.ArgumentParser()
ap.add_argument("--hist", default=str(DEFAULT_HIST))
ap.add_argument("--out", default=str(DEFAULT_OUT))
args = ap.parse_args()
hist_raw = load_json(Path(args.hist))
records: list[dict] = (
hist_raw.get("records", []) if isinstance(hist_raw, dict)
else (hist_raw if isinstance(hist_raw, list) else [])
)
# ── 분류 ─────────────────────────────────────────────────────────────────
live_all = [r for r in records if not _is_replay(r)]
replay_all = [r for r in records if _is_replay(r)]
live_eval = [r for r in live_all if _is_evaluated_t20(r)]
live_t20_count = len(live_eval)
insufficient = live_t20_count < MIN_T20_FOR_METRICS
# ── 성과 지표 (LIVE T+20 전체) ────────────────────────────────────────
returns = [float(r["t20_return_pct"]) for r in live_eval] if live_eval else []
overall = _compute_metrics(returns)
# ── 주간 스코어카드 ──────────────────────────────────────────────────
weekly_scorecard = _build_weekly_scorecard(live_eval)
# ── gate 판정 ─────────────────────────────────────────────────────────
exp = overall.get("expectancy_pct")
wr = overall.get("win_rate_pct")
if insufficient:
gate = "INSUFFICIENT_DATA"
elif exp is not None and wr is not None and (exp < 0 or wr < 40):
gate = "WARNING"
else:
gate = "PASS"
result = {
"formula_id": "CONTINUOUS_EVALUATION_DASHBOARD_V1",
"generated_at": datetime.now(timezone.utc).isoformat(),
"gate": gate,
# ── 전체 지표 ────────────────────────────────────────────────────
"weekly_scorecard_generated": len(weekly_scorecard) > 0,
"expectancy_pct": overall.get("expectancy_pct"),
"win_rate_pct": overall.get("win_rate_pct"),
"max_drawdown_pct": overall.get("max_drawdown_pct"),
"profit_giveback_pct": None, # T+20 이후 추적 미구현
"total_live_evaluated_t20": live_t20_count,
"total_live_pending": len(live_all) - live_t20_count,
# ── 주간 스코어카드 ─────────────────────────────────────────────
"weekly_scorecard": weekly_scorecard,
"weekly_scorecard_count": len(weekly_scorecard),
# ── informational (REPLAY 분리) ──────────────────────────────────
"replay_informational": {
"replay_record_count": len(replay_all),
"note": "REPLAY 표본은 성과 지표 계산에 포함되지 않음",
},
# ── 데이터 신뢰성 ─────────────────────────────────────────────
"data_confidence": {
"sufficient_for_metrics": not insufficient,
"min_required": MIN_T20_FOR_METRICS,
"current_live_t20": live_t20_count,
"gap": max(0, MIN_T20_FOR_METRICS - live_t20_count),
"estimated_ready": "~2026-07-15" if insufficient else "NOW",
},
"prohibitions": [
"REPLAY 표본을 성과 지표 계산에 포함 금지",
"T+20 미확정 거래를 EVALUATED_T20으로 분류 금지",
"외부 가격 데이터 직접 조회 금지 (history 기록 기준만 사용)",
],
}
save_json(args.out, result)
# ── Excel 파일 기입 (GatherTradingData.xlsx > evaluation_dashboard) ──
try:
import openpyxl
xlsx_path = ROOT / "GatherTradingData.xlsx"
if xlsx_path.exists():
wb = openpyxl.load_workbook(xlsx_path)
sheet_name = "evaluation_dashboard"
# 기존 시트 클리어 및 재생성
if sheet_name in wb.sheetnames:
ws = wb[sheet_name]
ws.delete_rows(1, ws.max_row + 10)
else:
ws = wb.create_sheet(sheet_name)
# 1. SUMMARY 섹션 기입
ws.append(["Metric", "Value"])
summary_metrics = [
("Generated At", result["generated_at"]),
("Gate Status", result["gate"]),
("Expectancy Pct", result["expectancy_pct"]),
("Win Rate Pct", result["win_rate_pct"]),
("Max Drawdown Pct", result["max_drawdown_pct"]),
("Total Live Evaluated T+20", result["total_live_evaluated_t20"]),
("Total Live Pending", result["total_live_pending"]),
("Replay Record Count", result["replay_informational"]["replay_record_count"]),
("Sufficient For Metrics", result["data_confidence"]["sufficient_for_metrics"]),
("Min Required", result["data_confidence"]["min_required"]),
("Current Live T+20", result["data_confidence"]["current_live_t20"]),
("Gap", result["data_confidence"]["gap"]),
("Estimated Ready", result["data_confidence"]["estimated_ready"])
]
for m, v in summary_metrics:
ws.append([m, v])
# 2. WEEKLY SCORECARD 섹션 기입 (오른쪽 열인 D열부터 시작)
ws.cell(row=1, column=4, value="Week")
ws.cell(row=1, column=5, value="Expectancy_Pct")
ws.cell(row=1, column=6, value="Win_Rate_Pct")
ws.cell(row=1, column=7, value="Max_Drawdown_Pct")
ws.cell(row=1, column=8, value="Trade_Count")
for idx, w in enumerate(weekly_scorecard):
r_num = idx + 2
ws.cell(row=r_num, column=4, value=w.get("week"))
ws.cell(row=r_num, column=5, value=w.get("expectancy_pct"))
ws.cell(row=r_num, column=6, value=w.get("win_rate_pct"))
ws.cell(row=r_num, column=7, value=w.get("max_drawdown_pct"))
ws.cell(row=r_num, column=8, value=w.get("trade_count"))
wb.save(xlsx_path)
print(f"[EVALUATION_DASHBOARD] Saved evaluation_dashboard sheet to {xlsx_path.name}")
except Exception as e:
print(f"[EVALUATION_DASHBOARD][ERROR] Failed to save Excel sheet: {e}")
suffix = f"(need {max(0, MIN_T20_FOR_METRICS - live_t20_count)} more LIVE T+20)" if insufficient else ""
print(
f"[CONTINUOUS_EVALUATION_DASHBOARD_V1] gate={gate} "
f"live_t20={live_t20_count} "
f"expectancy={overall.get('expectancy_pct')} "
f"win_rate={overall.get('win_rate_pct')}% "
f"MDD={overall.get('max_drawdown_pct')} "
f"weeks={len(weekly_scorecard)} {suffix}"
)
return 0
if __name__ == "__main__":
raise SystemExit(main())