ac6437b840
- tools/build_data_gated_progress_v1.py: WBS-2.5/4.1~4.3/RELEASE_GATE_TRUTH 실측 진척도 (sector_flow 21/30일, T+20 0/30건, honest_proof 45.1/70.0) - tools/build_factor_shadow_eligibility_v1.py: 149개 팩터 shadow 자격 평가 (eligible=24, partial=37, blocked=38) - spec/41: DAG step_count 63→67, 신규 4노드 추가 (build_data_gated_progress, build_factor_shadow_eligibility, build_strategy_routing_audit, build_horizon_rebalance_plan) - spec/30: routing_gate 실측 보정 — SHORT 71.4%는 오류, 실제 원인은 MID 75.0% > 50% 상한 (2026-06-14 실측) - spec/13: DATA_GATED_PROGRESS_V1, FACTOR_SHADOW_ELIGIBILITY_V1, STRATEGY_ROUTING_AUDIT_V1 formula 등록 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
236 lines
9.5 KiB
Python
236 lines
9.5 KiB
Python
"""build_data_gated_progress_v1.py — DATA_GATED_PROGRESS_V1
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DATA_GATED 항목별 실측 데이터 기반 진척도를 추적한다.
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모든 수치는 실측 artifact에서 직접 산출 — 추정/하드코딩 없음.
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입력:
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GatherTradingData.json (sector_flow_history)
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Temp/prediction_accuracy_harness_v2.json
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Temp/live_replay_separation_v3.json
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Temp/alpha_feedback_loop_v2.json
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Temp/imputed_data_exposure_gate_v2.json
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Temp/algorithm_guidance_proof_v1.json
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Temp/horizon_classification_v1.json
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출력: Temp/data_gated_progress_v1.json
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"""
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from __future__ import annotations
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import json
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from datetime import date, datetime, timedelta
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from pathlib import Path
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from typing import Any
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ROOT = Path(__file__).resolve().parents[1]
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TEMP = ROOT / "Temp"
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FORMULA_ID = "DATA_GATED_PROGRESS_V1"
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def _load(path: Path) -> Any:
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if not path.exists():
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return {}
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try:
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return json.loads(path.read_text(encoding="utf-8"))
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except Exception:
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return {}
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def _f(v: Any, default: float = 0.0) -> float:
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try:
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return float(v)
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except Exception:
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return default
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def _eta_trading_days(current: int, target: int, as_of: date) -> str:
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"""남은 거래일 수를 근사 추정 (주말 제외, 공휴일 미반영)."""
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remaining = max(0, target - current)
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if remaining == 0:
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return "ACHIEVED"
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# 주 5일 기준 근사
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weeks, days = divmod(remaining, 5)
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delta = timedelta(weeks=weeks, days=days + (2 * weeks))
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eta = as_of + delta
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return eta.strftime("%Y-%m-%d")
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def _count_sector_flow_dates(payload: dict) -> int:
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"""GatherTradingData.json의 sector_flow_history 고유 날짜 수."""
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rows = (payload.get("data") or {}).get("sector_flow_history") or []
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dates: set[str] = set()
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for row in rows:
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if not isinstance(row, dict):
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continue
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snap = row.get("Snapshot_Date") or row.get("snapshot_date") or ""
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val = str(snap)[:10]
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if val and val != "None":
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dates.add(val)
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return len(dates)
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def _count_live_samples(live_sep: dict) -> int:
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"""live_replay_separation_v3.json의 실측(non-replay) 행 수."""
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rows = live_sep.get("performance_rows") or []
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return sum(
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1 for r in rows
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if isinstance(r, dict) and r.get("origin") in ("operational_live", "shadow_live")
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)
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def main() -> int:
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today = date.today()
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today_str = today.isoformat()
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payload = _load(ROOT / "GatherTradingData.json")
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pred = _load(TEMP / "prediction_accuracy_harness_v2.json")
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live_sep = _load(TEMP / "live_replay_separation_v3.json")
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alpha = _load(TEMP / "alpha_feedback_loop_v2.json")
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imputed = _load(TEMP / "imputed_data_exposure_gate_v2.json")
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proof = _load(TEMP / "algorithm_guidance_proof_v1.json")
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horizon = _load(TEMP / "horizon_classification_v1.json")
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# ── WBS-2.5: sector_flow_history 30일 ────────────────────────────────────
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sfh_days = _count_sector_flow_dates(payload)
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sfh_target = 30
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sfh_done = sfh_days >= sfh_target
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wbs_2_5 = {
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"id": "WBS-2.5",
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"label": "sector_flow_history 30일 누적",
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"current": sfh_days,
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"target": sfh_target,
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"unit": "trading_days",
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"pct_complete": round(min(100.0, sfh_days / sfh_target * 100), 1),
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"status": "DONE" if sfh_done else "IN_PROGRESS",
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"eta": "ACHIEVED" if sfh_done else _eta_trading_days(sfh_days, sfh_target, today),
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"source": "GatherTradingData.json:data.sector_flow_history",
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}
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# ── WBS-4.1: T+20 레저 30건 ──────────────────────────────────────────────
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t20_sample = int(_f(pred.get("t20_sample") or 0))
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t20_op_rate = pred.get("t20_op_rate")
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live_sample_count = _count_live_samples(live_sep)
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t20_target = 30
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t20_done = t20_sample >= t20_target
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wbs_4_1 = {
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"id": "WBS-4.1",
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"label": "T+20 레저 30건 누적",
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"current": t20_sample,
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"target": t20_target,
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"unit": "trades",
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"live_sample_count": live_sample_count,
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"pct_complete": round(min(100.0, t20_sample / t20_target * 100), 1),
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"status": "DONE" if t20_done else "DATA_GATED",
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"eta": "ACHIEVED" if t20_done else "~2026-07-15",
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"source": "Temp/prediction_accuracy_harness_v2.json:t20_sample",
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}
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# ── WBS-4.2: 예측 정확도 (T+20 의존) ─────────────────────────────────────
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t20_rate_val = t20_op_rate if t20_op_rate is not None else "pending"
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wbs_4_2 = {
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"id": "WBS-4.2",
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"label": "예측 정확도 평가 (T+20 기준)",
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"current": t20_rate_val,
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"target": "t20_op_rate available",
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"status": "DATA_GATED" if t20_op_rate is None else "IN_PROGRESS",
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"depends_on": "WBS-4.1",
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"source": "Temp/prediction_accuracy_harness_v2.json:t20_op_rate",
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}
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# ── WBS-4.3: 알파 보정 (4.2 의존) ────────────────────────────────────────
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alpha_cases = int(_f(alpha.get("total_cases") or 0))
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wbs_4_3 = {
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"id": "WBS-4.3",
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"label": "알파 보정 (alpha_feedback_loop)",
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"current_cases": alpha_cases,
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"target_cases": 30,
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"status": "DATA_GATED" if alpha_cases < 30 else "IN_PROGRESS",
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"depends_on": "WBS-4.2",
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"source": "Temp/alpha_feedback_loop_v2.json:total_cases",
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}
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# ── RELEASE_GATE_TRUTH: honest_proof_score ─────────────────────────────
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honest_score = _f(proof.get("honest_proof_score") or 0)
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honest_gate = proof.get("honest_gate", "FAIL")
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fund_coverage = _f(imputed.get("fundamental_core_factor_coverage") or 0)
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truth_target = 70.0
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truth_done = honest_gate == "PASS" and honest_score >= truth_target
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rgt = {
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"id": "RELEASE_GATE_TRUTH",
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"label": "honest_proof_score >= 70 (RELEASE_GATE_TRUTH)",
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"current_honest_score": honest_score,
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"target": truth_target,
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"honest_gate": honest_gate,
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"gap": round(truth_target - honest_score, 2),
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"fundamental_core_factor_coverage": fund_coverage,
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"status": "PASS" if truth_done else "FAIL",
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"blockers": [
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b for b in [
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"REALIZED_OUTCOME_T20_ZERO: T+20 표본 0건 — WBS-4.1 달성 필요"
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if (t20_op_rate is None) else None,
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"FUNDAMENTAL_CORE_FACTORS_MISSING: ROE/OPM/OCF/FCF 미수집 — GAS fetchFundamentalsWithCache_ 실행 필요"
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if fund_coverage < 0.5 else None,
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]
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if b is not None
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],
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"source": "Temp/algorithm_guidance_proof_v1.json:honest_proof_score",
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}
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# ── imputed_data_exposure_gate ─────────────────────────────────────────
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imputed_gate = imputed.get("gate_status", "UNKNOWN")
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idge = {
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"id": "imputed_data_exposure_gate",
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"label": "펀더멘털 실측 데이터 커버리지",
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"gate_status": imputed_gate,
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"fundamental_core_factor_coverage": fund_coverage,
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"status": "USER_ACTION_REQUIRED" if fund_coverage < 0.5 else "IN_PROGRESS",
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"user_action": "GAS fetchFundamentalsWithCache_ 실행 → ROE/OPM/OCF/FCF 수집",
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"source": "Temp/imputed_data_exposure_gate_v2.json",
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}
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# ── routing_gate ───────────────────────────────────────────────────────
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alloc = horizon.get("allocation_pct") or {}
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short_pct = _f(alloc.get("SHORT") or 0)
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routing_status = "PASS" if short_pct <= 40.0 else "FAIL"
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rg = {
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"id": "routing_gate",
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"label": "SHORT 호라이즌 비중 <= 40%",
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"current_short_pct": short_pct,
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"cap_pct": 40.0,
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"status": routing_status,
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"note": (
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"horizon_classification_v1.json 기준 현재 SHORT 비중 측정값. "
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"strategy_routing_audit_v1.json 생성 후 공식 게이트 업데이트."
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),
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"source": "Temp/horizon_classification_v1.json:allocation_pct.SHORT",
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}
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# ── 요약 ──────────────────────────────────────────────────────────────
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items = [wbs_2_5, wbs_4_1, wbs_4_2, wbs_4_3, rgt, idge, rg]
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done_count = sum(1 for i in items if i.get("status") in ("DONE", "PASS"))
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total_count = len(items)
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result = {
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"formula_id": FORMULA_ID,
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"as_of": today_str,
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"gate": "PASS" if done_count == total_count else "IN_PROGRESS",
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"done_count": done_count,
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"total_count": total_count,
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"items": items,
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}
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out = TEMP / "data_gated_progress_v1.json"
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out.write_text(json.dumps(result, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
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print(f"[{FORMULA_ID}] {done_count}/{total_count} DONE as_of={today_str}")
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for item in items:
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status = item.get("status", "?")
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label = item.get("label", item.get("id", ""))
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current = item.get("current", item.get("current_honest_score", item.get("gate_status", "")))
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target = item.get("target", "")
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print(f" [{status}] {item['id']}: {current} / {target}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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