데이터 게이트 검증기와 DAG 연결
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"""validate_operational_alpha_calibration_v2.py — OPERATIONAL_ALPHA_CALIBRATION_VALIDATE_V2
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Temp/operational_alpha_calibration_v2.json의 최소 계약을 검증한다.
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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 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_INPUT = ROOT / "Temp" / "operational_alpha_calibration_v2.json"
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DEFAULT_OUT = ROOT / "Temp" / "validate_operational_alpha_calibration_v2.json"
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FORMULA_ID = "OPERATIONAL_ALPHA_CALIBRATION_VALIDATE_V2"
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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 _is_dict(value: Any) -> bool:
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return isinstance(value, dict)
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def main() -> int:
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ap = argparse.ArgumentParser()
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ap.add_argument("--input", default=str(DEFAULT_INPUT))
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ap.add_argument("--out", default=str(DEFAULT_OUT))
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args = ap.parse_args()
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input_path = Path(args.input)
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input_path = input_path if input_path.is_absolute() else ROOT / input_path
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out_path = Path(args.out)
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out_path = out_path if out_path.is_absolute() else ROOT / out_path
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payload = _load(input_path)
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errors: list[str] = []
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if not _is_dict(payload):
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errors.append("payload must be object")
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else:
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if payload.get("formula_id") != "OPERATIONAL_ALPHA_CALIBRATION_V2":
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errors.append("formula_id mismatch")
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if payload.get("gate") not in {"PERFORMANCE_READY", "NOT_READY"}:
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errors.append(f"gate={payload.get('gate')}")
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if "performance_ready" not in payload or not isinstance(payload.get("performance_ready"), bool):
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errors.append("performance_ready must be bool")
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if "confidence_score" not in payload or not isinstance(payload.get("confidence_score"), (int, float)):
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errors.append("confidence_score must be numeric")
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for key in ["metrics", "targets", "readiness_reasons"]:
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if key not in payload:
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errors.append(f"missing field: {key}")
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metrics = payload.get("metrics")
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if isinstance(metrics, dict):
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for key in [
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"outcome_quality_score",
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"t20_operational_sample",
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"t20_operational_pass_rate",
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"t5_operational_sample",
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"t5_operational_pass_rate",
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"trade_quality_t5_score",
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"value_damage_pct_avg",
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]:
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if key not in metrics:
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errors.append(f"missing field: metrics.{key}")
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targets = payload.get("targets")
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if isinstance(targets, dict):
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for key in [
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"outcome_quality_score_min",
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"t20_operational_sample_min",
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"t20_operational_pass_rate_min",
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"t5_operational_sample_min",
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"t5_operational_pass_rate_min",
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"trade_quality_t5_score_min",
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"value_damage_pct_avg_max",
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]:
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if key not in targets:
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errors.append(f"missing field: targets.{key}")
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reasons = payload.get("readiness_reasons")
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if isinstance(reasons, list):
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if payload.get("gate") == "PERFORMANCE_READY" and reasons:
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errors.append("PERFORMANCE_READY must not have readiness reasons")
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if payload.get("gate") == "NOT_READY" and not reasons:
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errors.append("NOT_READY must have readiness reasons")
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result = {
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"formula_id": FORMULA_ID,
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"gate": "PASS" if not errors else "FAIL",
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"checked_file": str(Path(args.input).as_posix()),
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"errors": errors,
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}
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out_path.write_text(json.dumps(result, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
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print(json.dumps(result, ensure_ascii=False, indent=2))
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return 0 if not errors else 1
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if __name__ == "__main__":
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raise SystemExit(main())
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