55debd98a4
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>
228 lines
9.9 KiB
Python
228 lines
9.9 KiB
Python
"""build_continuous_evaluation_dashboard_v1.py — CONTINUOUS_EVALUATION_DASHBOARD_V1
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P2-020: 주간 성과 대시보드.
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- LIVE T+20 표본에서 기대수익/승률/MDD/수익반납 지표 산출
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- REPLAY 표본은 informational 섹션에만 집계 (성과 계산 혼입 금지)
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- T+20 미확정 → None으로 표기, INSUFFICIENT_DATA 게이트
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"""
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from __future__ import annotations
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import argparse
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import json
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from collections import defaultdict
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any
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from v7_hardening_common import ROOT, TEMP, load_json, save_json
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DEFAULT_HIST = ROOT / "Temp" / "proposal_evaluation_history.json"
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DEFAULT_OUT = TEMP / "continuous_evaluation_dashboard_v1.json"
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MIN_T20_FOR_METRICS = 30 # 성과 지표 신뢰성 최소 표본 수
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_REPLAY_ORIGINS = {"REPLAY_FROM_KRX_EOD", "HISTORICAL_REPLAY", "BACKTEST"}
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_REPLAY_VALIDATION = {"REPLAY", "HISTORICAL_REPLAY"}
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def _is_replay(r: dict) -> bool:
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return (
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str(r.get("data_origin") or "").upper() in _REPLAY_ORIGINS
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or str(r.get("validation_status") or "").upper() in _REPLAY_VALIDATION
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or str(r.get("record_type") or "").upper().startswith("HISTORICAL_REPLAY")
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)
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def _is_evaluated_t20(r: dict) -> bool:
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return (
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r.get("t20_evaluation_status") == "EVALUATED_T20"
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and r.get("t20_return_pct") is not None
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)
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def _iso_week(date_str: str | None) -> str | None:
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if not date_str:
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return None
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try:
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dt = datetime.strptime(str(date_str)[:10], "%Y-%m-%d")
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return dt.strftime("%G-W%V")
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except ValueError:
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return None
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def _compute_metrics(t20_returns: list[float]) -> dict[str, Any]:
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if not t20_returns:
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return {
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"expectancy_pct": None,
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"win_rate_pct": None,
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"max_drawdown_pct": None,
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"trade_count": 0,
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}
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wins = [r for r in t20_returns if r > 0]
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return {
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"expectancy_pct": round(sum(t20_returns) / len(t20_returns), 4),
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"win_rate_pct": round(len(wins) / len(t20_returns) * 100, 2),
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"max_drawdown_pct": round(min(t20_returns), 4),
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"trade_count": len(t20_returns),
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}
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def _build_weekly_scorecard(live_eval: list[dict]) -> list[dict]:
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weeks: dict[str, list[float]] = defaultdict(list)
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for r in live_eval:
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week = _iso_week(r.get("proposal_date") or r.get("created_at"))
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if week:
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weeks[week].append(float(r["t20_return_pct"]))
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scorecard = []
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for week in sorted(weeks.keys()):
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returns = weeks[week]
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m = _compute_metrics(returns)
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m["week"] = week
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scorecard.append(m)
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return scorecard
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def main() -> int:
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ap = argparse.ArgumentParser()
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ap.add_argument("--hist", default=str(DEFAULT_HIST))
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ap.add_argument("--out", default=str(DEFAULT_OUT))
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args = ap.parse_args()
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hist_raw = load_json(Path(args.hist))
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records: list[dict] = (
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hist_raw.get("records", []) if isinstance(hist_raw, dict)
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else (hist_raw if isinstance(hist_raw, list) else [])
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)
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# ── 분류 ─────────────────────────────────────────────────────────────────
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live_all = [r for r in records if not _is_replay(r)]
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replay_all = [r for r in records if _is_replay(r)]
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live_eval = [r for r in live_all if _is_evaluated_t20(r)]
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live_t20_count = len(live_eval)
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insufficient = live_t20_count < MIN_T20_FOR_METRICS
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# ── 성과 지표 (LIVE T+20 전체) ────────────────────────────────────────
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returns = [float(r["t20_return_pct"]) for r in live_eval] if live_eval else []
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overall = _compute_metrics(returns)
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# ── 주간 스코어카드 ──────────────────────────────────────────────────
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weekly_scorecard = _build_weekly_scorecard(live_eval)
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# ── gate 판정 ─────────────────────────────────────────────────────────
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exp = overall.get("expectancy_pct")
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wr = overall.get("win_rate_pct")
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if insufficient:
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gate = "INSUFFICIENT_DATA"
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elif exp is not None and wr is not None and (exp < 0 or wr < 40):
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gate = "WARNING"
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else:
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gate = "PASS"
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result = {
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"formula_id": "CONTINUOUS_EVALUATION_DASHBOARD_V1",
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"generated_at": datetime.now(timezone.utc).isoformat(),
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"gate": gate,
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# ── 전체 지표 ────────────────────────────────────────────────────
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"weekly_scorecard_generated": len(weekly_scorecard) > 0,
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"expectancy_pct": overall.get("expectancy_pct"),
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"win_rate_pct": overall.get("win_rate_pct"),
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"max_drawdown_pct": overall.get("max_drawdown_pct"),
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"profit_giveback_pct": None, # T+20 이후 추적 미구현
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"total_live_evaluated_t20": live_t20_count,
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"total_live_pending": len(live_all) - live_t20_count,
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# ── 주간 스코어카드 ─────────────────────────────────────────────
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"weekly_scorecard": weekly_scorecard,
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"weekly_scorecard_count": len(weekly_scorecard),
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# ── informational (REPLAY 분리) ──────────────────────────────────
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"replay_informational": {
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"replay_record_count": len(replay_all),
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"note": "REPLAY 표본은 성과 지표 계산에 포함되지 않음",
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},
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# ── 데이터 신뢰성 ─────────────────────────────────────────────
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"data_confidence": {
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"sufficient_for_metrics": not insufficient,
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"min_required": MIN_T20_FOR_METRICS,
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"current_live_t20": live_t20_count,
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"gap": max(0, MIN_T20_FOR_METRICS - live_t20_count),
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"estimated_ready": "~2026-07-15" if insufficient else "NOW",
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},
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"prohibitions": [
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"REPLAY 표본을 성과 지표 계산에 포함 금지",
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"T+20 미확정 거래를 EVALUATED_T20으로 분류 금지",
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"외부 가격 데이터 직접 조회 금지 (history 기록 기준만 사용)",
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],
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}
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save_json(args.out, result)
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# ── Excel 파일 기입 (GatherTradingData.xlsx > evaluation_dashboard) ──
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try:
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import openpyxl
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xlsx_path = ROOT / "GatherTradingData.xlsx"
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if xlsx_path.exists():
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wb = openpyxl.load_workbook(xlsx_path)
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sheet_name = "evaluation_dashboard"
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# 기존 시트 클리어 및 재생성
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if sheet_name in wb.sheetnames:
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ws = wb[sheet_name]
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ws.delete_rows(1, ws.max_row + 10)
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else:
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ws = wb.create_sheet(sheet_name)
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# 1. SUMMARY 섹션 기입
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ws.append(["Metric", "Value"])
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summary_metrics = [
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("Generated At", result["generated_at"]),
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("Gate Status", result["gate"]),
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("Expectancy Pct", result["expectancy_pct"]),
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("Win Rate Pct", result["win_rate_pct"]),
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("Max Drawdown Pct", result["max_drawdown_pct"]),
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("Total Live Evaluated T+20", result["total_live_evaluated_t20"]),
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("Total Live Pending", result["total_live_pending"]),
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("Replay Record Count", result["replay_informational"]["replay_record_count"]),
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("Sufficient For Metrics", result["data_confidence"]["sufficient_for_metrics"]),
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("Min Required", result["data_confidence"]["min_required"]),
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("Current Live T+20", result["data_confidence"]["current_live_t20"]),
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("Gap", result["data_confidence"]["gap"]),
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("Estimated Ready", result["data_confidence"]["estimated_ready"])
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]
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for m, v in summary_metrics:
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ws.append([m, v])
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# 2. WEEKLY SCORECARD 섹션 기입 (오른쪽 열인 D열부터 시작)
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ws.cell(row=1, column=4, value="Week")
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ws.cell(row=1, column=5, value="Expectancy_Pct")
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ws.cell(row=1, column=6, value="Win_Rate_Pct")
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ws.cell(row=1, column=7, value="Max_Drawdown_Pct")
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ws.cell(row=1, column=8, value="Trade_Count")
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for idx, w in enumerate(weekly_scorecard):
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r_num = idx + 2
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ws.cell(row=r_num, column=4, value=w.get("week"))
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ws.cell(row=r_num, column=5, value=w.get("expectancy_pct"))
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ws.cell(row=r_num, column=6, value=w.get("win_rate_pct"))
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ws.cell(row=r_num, column=7, value=w.get("max_drawdown_pct"))
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ws.cell(row=r_num, column=8, value=w.get("trade_count"))
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wb.save(xlsx_path)
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print(f"[EVALUATION_DASHBOARD] Saved evaluation_dashboard sheet to {xlsx_path.name}")
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except Exception as e:
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print(f"[EVALUATION_DASHBOARD][ERROR] Failed to save Excel sheet: {e}")
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suffix = f"(need {max(0, MIN_T20_FOR_METRICS - live_t20_count)} more LIVE T+20)" if insufficient else ""
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print(
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f"[CONTINUOUS_EVALUATION_DASHBOARD_V1] gate={gate} "
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f"live_t20={live_t20_count} "
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f"expectancy={overall.get('expectancy_pct')} "
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f"win_rate={overall.get('win_rate_pct')}% "
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f"MDD={overall.get('max_drawdown_pct')} "
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f"weeks={len(weekly_scorecard)} {suffix}"
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)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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