feat: 리밸런싱 엔진 V1 + GAS 버그 수정 (2026-06-13)
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>
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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 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_JSON = ROOT / "GatherTradingData.json"
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DEFAULT_TRUTH = ROOT / "Temp" / "operational_truth_score_v1.json"
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DEFAULT_DQ = ROOT / "Temp" / "data_quality_reconciliation_v1.json"
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DEFAULT_FJ = ROOT / "Temp" / "final_judgment_gate_v1.json"
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DEFAULT_SCR = ROOT / "Temp" / "smart_cash_recovery_v7.json"
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DEFAULT_HARDENING = ROOT / "Temp" / "strategy_hardening_harness_v2.json"
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DEFAULT_OUT = ROOT / "Temp" / "execution_readiness_matrix_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 _as_float(value: Any, default: float = 0.0) -> float:
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try:
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if value is None or value == "":
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return default
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return float(value)
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except Exception:
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return default
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def _clamp_score(value: Any) -> float:
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return round(max(0.0, min(100.0, _as_float(value))), 2)
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def _axis_gate(score: float, hard_block: bool = False) -> str:
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if hard_block or score < 50.0:
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return "BLOCK"
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if score < 100.0:
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return "WATCH"
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return "PASS_100"
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def _axis(axis: str, score: Any, source_json: str, formula_id: str, reason: str = "", hard_block: bool = False) -> dict[str, Any]:
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s = _clamp_score(score)
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gate = _axis_gate(s, hard_block=hard_block)
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return {
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"axis": axis,
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"score_0_100": s,
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"gate": gate,
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"blocking_reason": reason if gate != "PASS_100" else "NONE",
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"source_json": source_json,
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"formula_id": formula_id,
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}
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def main() -> int:
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ap = argparse.ArgumentParser(description="Build EXECUTION_READINESS_MATRIX_V1.")
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ap.add_argument("--json", default=str(DEFAULT_JSON))
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ap.add_argument("--truth", default=str(DEFAULT_TRUTH))
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ap.add_argument("--dq", default=str(DEFAULT_DQ))
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ap.add_argument("--fj", default=str(DEFAULT_FJ))
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ap.add_argument("--scr", default=str(DEFAULT_SCR))
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ap.add_argument("--hardening", default=str(DEFAULT_HARDENING))
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ap.add_argument("--out", default=str(DEFAULT_OUT))
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args = ap.parse_args()
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def _rp(path_str: str) -> Path:
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path = Path(path_str)
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return path if path.is_absolute() else ROOT / path
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truth = _load(_rp(args.truth))
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dq = _load(_rp(args.dq))
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fj = _load(_rp(args.fj))
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scr = _load(_rp(args.scr))
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hardening = _load(_rp(args.hardening))
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domain_scores = hardening.get("domain_scores") if isinstance(hardening.get("domain_scores"), dict) else {}
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meta_scores = hardening.get("meta_scores") if isinstance(hardening.get("meta_scores"), dict) else {}
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cap_basis = _clamp_score(dq.get("confidence_cap_basis_score", truth.get("data_truth_score")))
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fundamental_domain = _clamp_score(domain_scores.get("fundamental"))
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fundamental_score = min(fundamental_domain, cap_basis)
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scr_allowed = bool(scr.get("execution_allowed"))
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scr_status = str(scr.get("status") or "UNKNOWN")
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scr_damage = _as_float(scr.get("value_damage_pct_avg"))
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if scr_allowed and scr_status == "PASS" and scr_damage <= 10.0:
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cash_recovery_score = 100.0
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cash_recovery_reason = ""
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cash_recovery_hard_block = False
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else:
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cash_recovery_score = 0.0
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cash_recovery_reason = f"SCR_STATUS={scr_status};EXECUTION_ALLOWED={scr_allowed};VALUE_DAMAGE={round(scr_damage, 2)}"
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cash_recovery_hard_block = True
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final_judgment_score = 100.0
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final_judgment_reason = ""
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fj_gate = str(fj.get("gate") or "MISSING")
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fj_coverage = _as_float(fj.get("coverage_pct"))
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fj_silent = int(_as_float(fj.get("silent_pass_violations")))
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if fj_gate != "PASS" or fj_coverage < 100.0 or fj_silent > 0:
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final_judgment_score = 0.0
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final_judgment_reason = f"FJ_GATE={fj_gate};COVERAGE={round(fj_coverage, 2)};SILENT={fj_silent}"
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axes = [
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_axis("data_integrity", truth.get("data_truth_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "DATA_TRUTH_LT_100"),
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_axis("routing_serving", domain_scores.get("routing_serving"), "strategy_hardening_harness_v2.json", "STRATEGY_HARDENING_HARNESS_V2", "ROUTING_SERVING_LT_100"),
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_axis("serving_output_lock", truth.get("report_consistency_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "REPORT_CONSISTENCY_LT_100"),
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_axis("decision_governance", truth.get("decision_truth_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "DECISION_TRUTH_LT_100"),
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_axis("final_judgment_lock", final_judgment_score, "final_judgment_gate_v1.json", "FINAL_JUDGMENT_GATE_V1", final_judgment_reason),
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_axis("fundamental_basis", fundamental_score, "data_quality_reconciliation_v1.json", "DATA_QUALITY_RECONCILIATION_V1", "CONFIDENCE_CAP_BASIS_LT_100"),
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_axis("horizon_policy", domain_scores.get("horizon_short_mid_long"), "strategy_hardening_harness_v2.json", "STRATEGY_HARDENING_HARNESS_V2", "HORIZON_POLICY_LT_100"),
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_axis("smart_money_liquidity", domain_scores.get("smart_money_liquidity"), "strategy_hardening_harness_v2.json", "STRATEGY_HARDENING_HARNESS_V2", "SMART_MONEY_LIQUIDITY_LT_100"),
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_axis("cash_recovery_execution", cash_recovery_score, "smart_cash_recovery_v7.json", "SMART_CASH_RECOVERY_V7", cash_recovery_reason, cash_recovery_hard_block),
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_axis("execution_availability", truth.get("execution_truth_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "EXECUTION_TRUTH_LT_100"),
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_axis("performance_readiness", truth.get("performance_readiness_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "PERFORMANCE_READINESS_LT_100"),
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_axis("report_consistency", truth.get("report_consistency_score"), "operational_truth_score_v1.json", "OPERATIONAL_TRUTH_SCORE_V1", "REPORT_CONSISTENCY_LT_100"),
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]
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scores = [float(row["score_0_100"]) for row in axes]
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hard_blocks = [row for row in axes if row["gate"] == "BLOCK"]
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min_axis_score = round(min(scores), 2) if scores else 0.0
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average_axis_score = round(sum(scores) / len(scores), 2) if scores else 0.0
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truth_gate = str(truth.get("gate") or "MISSING")
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readiness_gate = str(meta_scores.get("readiness_gate") or "MISSING")
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if hard_blocks:
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gate = "BLOCK_EXECUTION"
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elif min_axis_score == 100.0 and truth_gate == "PASS_100" and readiness_gate == "PERFORMANCE_READY":
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gate = "PASS_100"
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else:
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gate = "WATCH_PENDING_SAMPLE"
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result = {
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"formula_id": "EXECUTION_READINESS_MATRIX_V1",
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"gate": gate,
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"min_axis_score": min_axis_score,
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"average_axis_score": average_axis_score,
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"hard_block_count": len(hard_blocks),
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"blocking_reasons": [str(row["blocking_reason"]) for row in axes if row["gate"] != "PASS_100"],
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"axes": axes,
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"targets": {
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"pass_100_rule": "all axes score_0_100 == 100, truth gate PASS_100, readiness_gate PERFORMANCE_READY",
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"block_rule": "any axis gate BLOCK",
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"watch_rule": "no BLOCK but at least one axis below 100 or insufficient performance sample",
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},
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"metric_basis": {
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"truth_gate": truth_gate,
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"truth_score_0_100": truth.get("score_0_100"),
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"readiness_gate": readiness_gate,
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"confidence_cap_basis_score": cap_basis,
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"fundamental_domain_score": fundamental_domain,
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"smart_cash_recovery_status": scr_status,
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"smart_cash_recovery_execution_allowed": scr_allowed,
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"smart_cash_recovery_value_damage_pct": round(scr_damage, 2),
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},
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}
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out_path = _rp(args.out)
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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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