kjh2064
ee3e799de1
주요 변경: - tools/build_rebalance_engine_v1.py: REBALANCE_ENGINE_V1 신규 * account_snapshot 직접 합산(_build_snap_position_map) → 소수주 분리 행 병합 * 레짐 소스 macro.REGIME_PRELIM 최우선 (GAS 와 동일) - src/gas_adapter_parts/gdf_06_rebalance.gs: runRebalanceSheet_() 신규 * Logger.log / getSpreadsheet_() 로 run_all 연동 수정 - src/gas_adapter_parts/gdc_01_fetch_fundamentals.gs * _mergePositionRecord_(): 소수주 중복 행 합산 신규 * parseInt → parseFloat (qty, availQty) - src/gas_adapter_parts/gdf_01_price_metrics.gs * 미보유 종목 SELL_READY → WATCH_EXIT_SIGNAL - spec/41_release_dag.yaml: build_rebalance_sheet 노드 추가 (step_count 63) - spec/51_formula_lifecycle_registry.yaml: REBALANCE_ENGINE_V1 등록 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
112 lines
4.4 KiB
Python
112 lines
4.4 KiB
Python
from __future__ import annotations
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import argparse
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import json
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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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DEFAULT_OUT = ROOT / "Temp" / "root_cause_recovery_plan_v1.json"
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def _load(path: Path) -> dict[str, Any]:
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if not path.exists():
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return {}
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try:
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obj = json.loads(path.read_text(encoding="utf-8"))
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except Exception:
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return {}
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return obj if isinstance(obj, dict) else {}
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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 main() -> int:
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ap = argparse.ArgumentParser()
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ap.add_argument("--out", default=str(DEFAULT_OUT))
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args = ap.parse_args()
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out_path = Path(args.out)
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if not out_path.is_absolute():
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out_path = ROOT / out_path
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op = _load(ROOT / "Temp" / "operational_report.json")
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sh = _load(ROOT / "Temp" / "strategy_hardening_harness_v1.json")
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oq = _load(ROOT / "Temp" / "outcome_quality_score_v1.json")
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pi = _load(ROOT / "Temp" / "prediction_improvement_harness.json")
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di = _load(ROOT / "Temp" / "data_integrity_score_v1.json")
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rb = _load(ROOT / "Temp" / "rebound_sell_efficiency_v1.json")
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pf = _load(ROOT / "Temp" / "perf_recovery_harness_v1.json")
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eg = _load(ROOT / "Temp" / "engine_harness_gate_result.json")
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baseline = {
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"data_integrity_score": _f(di.get("score")),
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"outcome_quality_score": _f(oq.get("score")),
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"t20_pass_rate": _f((oq.get("metrics") or {}).get("t20_pass_rate")),
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"algorithm_guidance_proof_score": _f((sh.get("domain_scores") or {}).get("algorithm_guidance_proof")),
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"overall_hardening_score": _f((sh.get("meta_scores") or {}).get("overall_hardening_score")),
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"prediction_match_rate_pct": _f((pi.get("summary") or {}).get("match_rate_pct")),
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"rebound_efficiency_score": _f((rb.get("metrics") or {}).get("rebound_efficiency_score")),
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"value_damage_pct_avg": _f((rb.get("metrics") or {}).get("value_damage_pct_avg")),
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"execution_quality_gate": str((pf.get("metrics") or {}).get("execution_quality_gate") or ""),
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"late_chase_status": str((pf.get("metrics") or {}).get("late_chase_status") or ""),
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"engine_gate_status": str(eg.get("status") or ""),
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"json_validation_status": str((op.get("summary") or {}).get("json_validation_status") or ""),
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}
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failed_dimensions: list[str] = []
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if baseline["data_integrity_score"] < 100.0:
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failed_dimensions.append("data_integrity")
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if baseline["outcome_quality_score"] < 60.0:
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failed_dimensions.append("outcome_quality")
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if baseline["t20_pass_rate"] < 60.0:
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failed_dimensions.append("t20_pass_rate")
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if baseline["prediction_match_rate_pct"] < 60.0:
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failed_dimensions.append("prediction_match_rate")
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if baseline["value_damage_pct_avg"] > 10.0:
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failed_dimensions.append("cash_recovery_value_damage")
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if baseline["execution_quality_gate"] in {"FAIL", "WATCH_PENDING_SAMPLE"}:
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failed_dimensions.append("execution_quality")
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if baseline["algorithm_guidance_proof_score"] < 95.0:
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failed_dimensions.append("algorithm_guidance_proof")
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top_errors = (pi.get("top_errors") or []) if isinstance(pi.get("top_errors"), list) else []
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top_errors = [x for x in top_errors if isinstance(x, dict)][:10]
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result = {
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"formula_id": "ROOT_CAUSE_RECOVERY_PLAN_V1",
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"baseline_scores": baseline,
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"failed_dimensions": failed_dimensions,
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"top_error_categories": top_errors,
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"required_harness_actions": [
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"OPERATIONAL_OUTCOME_LOCK_V1",
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"SMART_CASH_RECOVERY_V5",
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"STRATEGY_HARDENING_HARNESS_V2",
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"DATA_INTEGRITY_100_LOCK_V2",
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],
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"unlock_criteria": {
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"data_integrity_score": 100.0,
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"outcome_quality_score_min": 60.0,
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"t20_pass_rate_min": 60.0,
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"prediction_match_rate_pct_min": 60.0,
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"value_damage_pct_avg_max": 10.0,
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"algorithm_guidance_proof_min": 95.0,
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},
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"no_fake_100_statement": "PASS_100 is valid only when all lock criteria are numerically satisfied.",
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}
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out_path.parent.mkdir(parents=True, exist_ok=True)
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out_path.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
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print(json.dumps(result, ensure_ascii=False, indent=2))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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