kjh2064
0823d1b5a8
- ci.yml: venv 해시 기반 캐싱 적용 (validate_specs.py md5 기준), requirements.txt 불필요 스텝 제거 - harness_coverage_auditor.py: sector_trend_analysis.py, etf_representative_monitor.py PY_FILES 등록 - render_operational_report.py: _portfolio_sector_exposure_summary 개선 — account_snapshot 실데이터 집계 + Top5 섹터별 상위 보유 종목 상세 테이블 + _display() 누락값 표시 - update_workbook_sector_insights.py: row-2 헤더 처리 + sector_holdings 상세 추적 + _display() 누락값 표시 - operational_report_contract.py: portfolio_sector_exposure_summary REPORT_SECTION_ORDER 등록 - validate_report_section_completeness_v1.py: 동일 섹션 추가 - build_architecture_boundaries_v2.py: sparkline/idx/basket-delta UI 프리미티브 whitelist 추가 - runtime/refactor_baseline_v1.yaml: 엔트로피 베이스라인 갱신 (1692 files, gate=PASS) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1391 lines
71 KiB
Python
1391 lines
71 KiB
Python
#!/usr/bin/env python3
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"""
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render_operational_report.py — 30개 섹션 완전 렌더링.
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섹션 처리 오류는 section_errors 배열에 기록되어 하네스 검증에 노출된다.
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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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import sys
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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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ROOT = Path(__file__).resolve().parents[1]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from src.quant_engine.etf_representative_monitor import build_etf_representative_monitor
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from src.quant_engine.sector_trend_analysis import build_sector_trend_analysis
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SECTION_ORDER = [
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"exec_safety_declaration", "final_judgment_table", "final_execution_decision",
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"concise_hts_input_sheet", "watch_breakout_gate",
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"single_conclusion", "immediate_execution_playbook", "market_context_learning_note",
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"portfolio_performance_summary",
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"portfolio_sector_exposure_summary",
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"sector_trend_analysis_v1", "etf_representative_monitor_v1", "investment_quality_headline", "operational_truth_score",
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"execution_readiness_matrix", "pass_100_criteria",
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"today_decision_summary_card", "routing_serving_trace",
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"export_gate_diagnosis", "QEH_AUDIT_BLOCK",
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"fundamental_quality_gate_v1", "horizon_allocation_lock_v1",
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"smart_money_liquidity_gate_v1", "routing_serving_trace_v2",
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"fundamental_multifactor_v2", "earnings_growth_quality_v1",
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"market_share_proxy_v1", "cashflow_stability_v1",
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"routing_decision_explain_v1",
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"benchmark_relative_harness_table", "index_relative_health_table",
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"entry_freshness_gate_table", "sell_value_preservation_gate_table",
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"watch_release_checklist", "alpha_feedback_loop_report",
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"backdata_feature_bank_table", "alpha_lead_table", "anti_distribution_table",
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"profit_preservation_table", "smart_cash_raise_table", "execution_quality_table",
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"sell_priority_decision_table", "strategy_performance_scoreboard",
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"outcome_eval_window_monitor",
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"decision_trace_table", "anti_whipsaw_reentry_gate", "proposal_reference_sheet",
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"satellite_buy_proposal_sheet", "core_satellite_timing_gate_table",
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"engine_feedback_loop_report", "prediction_evaluation_improvement_report",
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"rule_lifecycle_governance_report",
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]
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SECTION_TITLES = {
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"exec_safety_declaration": "집행 안전 선언",
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"final_judgment_table": "최종 판단 테이블",
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"final_execution_decision": "최종 실행 결정",
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"concise_hts_input_sheet": "HTS 입력 요약표",
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"watch_breakout_gate": "투명한 감시 원장 / 돌파 감시 게이트",
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"single_conclusion": "단일 결론",
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"immediate_execution_playbook": "즉시 실행 플레이북",
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"market_context_learning_note": "시장 컨텍스트 학습 노트",
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"portfolio_performance_summary": "포트폴리오 성과 요약",
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"portfolio_sector_exposure_summary": "포트폴리오 섹터 노출",
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"sector_trend_analysis_v1": "섹터 동향 분석",
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"etf_representative_monitor_v1": "ETF 대표 종목 모니터",
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"investment_quality_headline": "투자 품질 헤드라인",
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"operational_truth_score": "운영 진실성 점수",
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"execution_readiness_matrix": "실행 준비도 매트릭스",
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"pass_100_criteria": "PASS_100 기준",
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"today_decision_summary_card": "오늘의 의사결정 요약 카드",
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"routing_serving_trace": "라우팅 서빙 추적",
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"export_gate_diagnosis": "내보내기 게이트 진단",
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"QEH_AUDIT_BLOCK": "QEH 감사 블록",
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"fundamental_quality_gate_v1": "FUNDAMENTAL_QUALITY_GATE_V1",
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"horizon_allocation_lock_v1": "HORIZON_ALLOCATION_LOCK_V1",
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"smart_money_liquidity_gate_v1": "SMART_MONEY_LIQUIDITY_GATE_V1",
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"routing_serving_trace_v2": "ROUTING_SERVING_DECISION_TRACE_V2",
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"fundamental_multifactor_v2": "FUNDAMENTAL_MULTI_FACTOR_SCORE_V2",
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"earnings_growth_quality_v1": "EARNINGS_GROWTH_QUALITY_GATE_V1",
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"market_share_proxy_v1": "MARKET_SHARE_MOMENTUM_PROXY_V1",
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"cashflow_stability_v1": "CASHFLOW_STABILITY_GATE_V1",
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"routing_decision_explain_v1": "ROUTING_DECISION_EXPLAIN_LOCK_V1",
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"benchmark_relative_harness_table": "benchmark_relative_harness_table",
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"index_relative_health_table": "index_relative_health_table",
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"entry_freshness_gate_table": "entry_freshness_gate_table",
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"sell_value_preservation_gate_table": "sell_value_preservation_gate_table",
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"watch_release_checklist": "watch_release_checklist",
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"alpha_feedback_loop_report": "alpha_feedback_loop_report",
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"backdata_feature_bank_table": "백데이터 특성 원장",
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"alpha_lead_table": "알파 선행 테이블",
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"anti_distribution_table": "분산 매도 위험 테이블",
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"profit_preservation_table": "수익 보존 테이블",
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"smart_cash_raise_table": "현금 확보 테이블",
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"execution_quality_table": "체결 품질 테이블",
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"sell_priority_decision_table": "매도 우선순위 결정 테이블",
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"strategy_performance_scoreboard": "전략 성과 스코어보드",
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"outcome_eval_window_monitor": "성과 평가 윈도우 모니터",
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"decision_trace_table": "판단 추적 테이블",
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"anti_whipsaw_reentry_gate": "반등 재진입 감시 게이트",
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"proposal_reference_sheet": "제안 참조 시트",
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"satellite_buy_proposal_sheet": "위성 신규 매수 제안 원장",
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"core_satellite_timing_gate_table": "코어·위성 타이밍 게이트",
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"engine_feedback_loop_report": "엔진 피드백 루프 보고서",
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"prediction_evaluation_improvement_report": "예측 평가 보고서",
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"rule_lifecycle_governance_report": "규칙 생애주기 거버넌스 보고서",
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}
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# ── 공통 유틸 ─────────────────────────────────────────────────────────────────
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def _sj(v: Any) -> Any:
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if isinstance(v, (list, dict)):
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return v
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if isinstance(v, str):
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s = v.strip()
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if s and s[0] in ('[', '{'):
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try:
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return json.loads(s)
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except Exception:
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pass
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return v
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def _kv(rows: list[tuple[str, Any]]) -> str:
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lines = ["| 항목 | 값 |", "| --- | --- |"]
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for k, v in rows:
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lines.append(f"| {k} | {v} |")
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return "\n".join(lines)
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def _tbl(items: list[dict], keys: list[str], max_rows: int = 50) -> str:
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if not items:
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return "_데이터 없음_"
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valid_keys = [k for k in keys if k]
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if not valid_keys:
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valid_keys = list(items[0].keys())[:6] if isinstance(items[0], dict) else []
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header = "| " + " | ".join(valid_keys) + " |"
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sep = "| " + " | ".join(["---"] * len(valid_keys)) + " |"
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rows = []
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for item in items[:max_rows]:
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row = "| " + " | ".join(str(item.get(k, "")).replace("|", "ㅣ") for k in valid_keys) + " |"
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rows.append(row)
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suffix = f"\n\n_...총 {len(items)}행 중 {max_rows}행 표시_" if len(items) > max_rows else ""
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all_lines = [header, sep]
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all_lines.extend(rows)
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return "".join(["\n".join(all_lines), suffix])
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def _err(section_errors: list, name: str, reason: str) -> str:
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section_errors.append({"section": name, "error": reason})
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return f"**[오류] {name}: {reason}**"
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def _first_keys(items: list, n: int = 6) -> list[str]:
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if items and isinstance(items[0], dict):
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return list(items[0].keys())[:n]
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return []
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def _num(value: Any, default: float = 0.0) -> float:
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try:
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return float(value)
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except Exception:
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return default
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def _sparkline(values: list[Any]) -> str:
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points: list[float] = []
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for value in values:
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try:
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points.append(float(value))
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except Exception:
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continue
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if not points:
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return "n/a"
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lo = min(points)
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hi = max(points)
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bars = "▁▂▃▄▅▆▇█"
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if hi == lo:
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return bars[len(bars) // 2] * len(points)
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out = []
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for value in points:
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idx = int(round((value - lo) / (hi - lo) * (len(bars) - 1)))
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out.append(bars[max(0, min(len(bars) - 1, idx))])
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return "".join(out)
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# ── PHASE-0 렌더러 ────────────────────────────────────────────────────────────
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def _exec_safety_declaration(hctx: dict, se: list) -> str:
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cr = _sj(hctx.get("consistency_report_json", {}))
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if not isinstance(cr, dict):
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return _err(se, "exec_safety_declaration", "consistency_report_json 파싱 실패")
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allowed = hctx.get("allowed_actions", [])
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blocked = hctx.get("blocked_actions", [])
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return "## CORE-0 집행 안전 선언\n\n" + _kv([
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("일관성 점수", cr.get("consistency_score", hctx.get("consistency_score", ""))),
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("CV 판정", cr.get("cv_verdict", hctx.get("cv_verdict", ""))),
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("차단 상태", cr.get("block_status", "")),
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("현금 바닥 상태", hctx.get("cash_floor_status", "")),
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("허용 액션", ", ".join(allowed) if isinstance(allowed, list) else str(allowed)),
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("차단 액션", ", ".join(blocked) if isinstance(blocked, list) else str(blocked)),
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("하네스 생성 상태", hctx.get("harness_generation_status", "N/A")),
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])
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def _final_judgment_table(hctx: dict, se: list) -> str:
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items = _sj(hctx.get("decisions_json", []))
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if not isinstance(items, list) or not items:
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return _err(se, "final_judgment_table", "decisions_json 없음")
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return _tbl(items, ["ticker", "name", "base_action", "final_action", "gate_changed", "rs_verdict"])
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def _final_execution_decision(hctx: dict, se: list) -> str:
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eg = _sj(hctx.get("export_gate_json", {}))
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if not isinstance(eg, dict):
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return _err(se, "final_execution_decision", "export_gate_json 파싱 실패")
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failed = eg.get("failed_checks", [])
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return _kv([
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("내보내기 게이트 상태", eg.get("export_gate_status", "")),
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("JSON 검증 상태", eg.get("json_validation_status", "")),
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("HTS 입력 허용", eg.get("hts_entry_allowed", "")),
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("모든 검사 통과", eg.get("all_checks_passed", "")),
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("실패 검사", ", ".join(str(f) for f in failed) if isinstance(failed, list) and failed else "없음"),
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("CLA 종료 상태", hctx.get("cla_exit_status", "N/A")),
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("하네스 생성 상태", hctx.get("harness_generation_status", "N/A")),
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])
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def _concise_hts_input_sheet(hctx: dict, se: list) -> str:
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items = _sj(hctx.get("decisions_json", []))
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if not isinstance(items, list) or not items:
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return _err(se, "concise_hts_input_sheet", "decisions_json 없음")
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return _tbl(items, ["ticker", "name", "final_action", "gate_trace", "rs_verdict"])
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def _watch_breakout_gate(hctx: dict, se: list) -> str:
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bq = _sj(hctx.get("breakout_quality_gate_json", []))
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vel = _sj(hctx.get("anti_chasing_velocity_json", []))
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parts = [_kv([
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("돌파 감시 판정", hctx.get("anti_chasing_verdict", "N/A")),
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("돌파 품질 점수", hctx.get("breakout_quality_score", "N/A")),
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("기준시점(종가/장중)", hctx.get("price_basis_label", "DATA_MISSING — 하네스 업데이트 필요")),
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("참고익절상태(tp1/tp2)", "tp1=DATA_MISSING tp2=DATA_MISSING"),
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])]
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if isinstance(bq, list) and bq:
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parts.append("\n\n**돌파 품질 게이트**\n\n" + _tbl(bq, _first_keys(bq)))
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if isinstance(vel, list) and vel:
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parts.append("\n\n**반추격 속도**\n\n" + _tbl(vel, _first_keys(vel)))
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return "".join(parts)
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# ── PHASE-1 렌더러 ────────────────────────────────────────────────────────────
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def _single_conclusion(hctx: dict, se: list) -> str:
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allowed = hctx.get("allowed_actions", [])
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blocked = hctx.get("blocked_actions", [])
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return _kv([
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("현금 현황 (D2%)", hctx.get("cash_current_pct_d2", "")),
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("현금 목표(%)", hctx.get("cash_target_pct", "")),
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("현금 바닥 상태", hctx.get("cash_floor_status", "")),
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("허용 액션", ", ".join(allowed) if isinstance(allowed, list) else str(allowed)),
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("차단 액션", ", ".join(blocked) if isinstance(blocked, list) else str(blocked)),
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("매수 여력 (KRW)", hctx.get("buy_power_krw", "")),
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("현금 부족액 (KRW)", hctx.get("cash_shortfall_min_krw", "")),
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("목표 달성율(%)", hctx.get("goal_achievement_pct", "")),
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("목표 상태", hctx.get("goal_status", "")),
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])
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def _immediate_execution_playbook(hctx: dict, se: list) -> str:
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items = _sj(hctx.get("decisions_json", []))
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plan = _sj(hctx.get("cash_recovery_plan_json", {}))
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parts = []
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if isinstance(items, list) and items:
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parts.append("**실행 결정**\n\n" + _tbl(items, ["ticker", "name", "final_action", "gate_trace"]))
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else:
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parts.append(_err(se, "immediate_execution_playbook", "decisions_json 없음"))
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if isinstance(plan, dict):
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sell_seq = plan.get("sell_sequence", "")
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parts.append("\n\n**현금 회수 계획**\n\n" + _kv([
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("매도 시퀀스", str(sell_seq)[:120]),
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("예상 즉시 회수 (KRW)", plan.get("expected_total_krw", "")),
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("부족액 충족", plan.get("shortfall_met", "")),
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("필요 건수", plan.get("items_needed", "")),
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]))
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return "".join(parts)
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def _market_context_learning_note(hctx: dict, se: list) -> str:
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macro = _sj(hctx.get("macro_event_json", {}))
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regime = _sj(hctx.get("regime_transition_json", {}))
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rows = [("BRT 판정", hctx.get("brt_verdict", "N/A"))]
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if isinstance(macro, dict):
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rows += [
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("매크로 위험 점수", macro.get("macro_risk_score", "")),
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("매크로 위험 레짐", macro.get("macro_risk_regime", "")),
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]
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if isinstance(regime, dict):
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rows += [
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("레짐 전환 유형", regime.get("transition_type", "")),
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("이전 레짐", regime.get("prev_regime", "")),
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("현재 레짐", regime.get("current_regime", regime.get("cur_regime", ""))),
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]
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rows.append(("열 게이트 상태", hctx.get("heat_gate_status", "N/A")))
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return _kv(rows)
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def _portfolio_performance_summary(data_root: dict, hctx: dict, se: list) -> str:
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def _display(v: Any) -> Any:
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return v if v not in (None, "") else "DATA_MISSING — 하네스 업데이트 필요"
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data = data_root.get("data", {}) if isinstance(data_root.get("data"), dict) else {}
|
|
daily = _sj(data.get("daily_history", []))
|
|
monthly = _sj(data.get("monthly_history", []))
|
|
account = _sj(data.get("account_snapshot", []))
|
|
if not isinstance(daily, list):
|
|
daily = []
|
|
if not isinstance(monthly, list):
|
|
monthly = []
|
|
if not isinstance(account, list):
|
|
account = []
|
|
|
|
latest_daily = daily[-1] if daily else {}
|
|
latest_month = monthly[-1] if monthly else {}
|
|
latest_capture = ""
|
|
latest_holdings: list[dict[str, Any]] = []
|
|
for row in account:
|
|
if not isinstance(row, dict):
|
|
continue
|
|
cap = str(row.get("captured_at", "") or "")
|
|
if cap and cap >= latest_capture:
|
|
latest_capture = cap
|
|
if latest_capture:
|
|
latest_holdings = [r for r in account if isinstance(r, dict) and str(r.get("captured_at", "") or "") == latest_capture]
|
|
|
|
asset_series = []
|
|
mdd_series = []
|
|
monthly_return_series = []
|
|
for row in daily[-10:]:
|
|
if isinstance(row, dict):
|
|
asset_series.append(row.get("Total_Asset_KRW", row.get("total_asset_krw", "")))
|
|
mdd_series.append(row.get("MDD_Pct", row.get("mdd_pct", "")))
|
|
for row in monthly[-10:]:
|
|
if isinstance(row, dict):
|
|
monthly_return_series.append(row.get("Actual_Return_Pct", row.get("actual_return_pct", "")))
|
|
|
|
rows = [
|
|
("최신 일간 자산", _display(latest_daily.get("Total_Asset_KRW", latest_daily.get("total_asset_krw", "")))),
|
|
("최신 일간 MDD(%)", _display(latest_daily.get("MDD_Pct", latest_daily.get("mdd_pct", "")))),
|
|
("최신 월간 자산", _display(latest_month.get("Total_Asset", latest_month.get("total_asset", "")))),
|
|
("최신 월간 실현 수익률(%)", _display(latest_month.get("Actual_Return_Pct", latest_month.get("actual_return_pct", "")))),
|
|
("최신 월간 MoM 수익률(%)", _display(latest_month.get("MoM_Return_Pct", latest_month.get("mom_return_pct", "")))),
|
|
("최신 월간 YTD 수익률(%)", _display(latest_month.get("YTD_Return_Pct", latest_month.get("ytd_return_pct", "")))),
|
|
("최신 스냅샷 시각", _display(latest_capture or hctx.get("captured_at", ""))),
|
|
("최신 보유 수", _display(len(latest_holdings))),
|
|
]
|
|
md = "## 포트폴리오 성과 요약\n\n" + _kv(rows)
|
|
md += "\n\n**일간 자산 추이** \n" + _sparkline(asset_series)
|
|
md += "\n\n**일간 MDD 추이** \n" + _sparkline(mdd_series)
|
|
md += "\n\n**월간 수익률 추이** \n" + _sparkline(monthly_return_series)
|
|
if latest_holdings:
|
|
md += "\n\n**최신 보유 상위 스냅샷**\n\n"
|
|
md += _tbl(latest_holdings[:10], ["name", "ticker", "holding_quantity", "market_value", "return_pct"], max_rows=10)
|
|
else:
|
|
md += "\n\n_최신 보유 스냅샷 없음_"
|
|
return md
|
|
|
|
|
|
def _portfolio_sector_exposure_summary(data_root: dict, hctx: dict, se: list) -> str:
|
|
data = data_root.get("data", {}) if isinstance(data_root.get("data"), dict) else {}
|
|
account = _sj(data.get("account_snapshot", []))
|
|
universe = _sj(data.get("universe", []))
|
|
if not isinstance(account, list):
|
|
account = []
|
|
if not isinstance(universe, list):
|
|
universe = []
|
|
|
|
sector_map: dict[str, str] = {}
|
|
for row in universe:
|
|
if not isinstance(row, dict):
|
|
continue
|
|
ticker = str(row.get("Ticker", "") or "").zfill(6)
|
|
sector = str(row.get("Sector", "") or "").strip()
|
|
if ticker and sector:
|
|
sector_map[ticker] = sector
|
|
|
|
latest_capture = ""
|
|
for row in account:
|
|
if not isinstance(row, dict):
|
|
continue
|
|
cap = str(row.get("captured_at", "") or "")
|
|
if cap and cap >= latest_capture:
|
|
latest_capture = cap
|
|
latest_rows = [r for r in account if isinstance(r, dict) and str(r.get("captured_at", "") or "") == latest_capture]
|
|
if not latest_rows:
|
|
return "## 포트폴리오 섹터 노출\n\n_섹터 노출 데이터 없음_"
|
|
|
|
exposure: dict[str, dict[str, float]] = {}
|
|
holdings_by_sector: dict[str, list[dict[str, Any]]] = {}
|
|
total_mv = 0.0
|
|
for row in latest_rows:
|
|
ticker = str(row.get("ticker", "") or "").zfill(6)
|
|
sector = sector_map.get(ticker, "미분류")
|
|
mv = _num(row.get("market_value", 0))
|
|
pl = _num(row.get("profit_loss", 0))
|
|
cost = _num(row.get("total_cost", 0))
|
|
total_mv += mv
|
|
bucket = exposure.setdefault(sector, {"market_value": 0.0, "profit_loss": 0.0, "cost": 0.0, "count": 0.0})
|
|
bucket["market_value"] += mv
|
|
bucket["profit_loss"] += pl
|
|
bucket["cost"] += cost
|
|
bucket["count"] += 1
|
|
holdings_by_sector.setdefault(sector, []).append({
|
|
"ticker": ticker,
|
|
"name": row.get("name", ""),
|
|
"market_value": mv,
|
|
"profit_loss": pl,
|
|
"return_pct": row.get("return_pct", ""),
|
|
})
|
|
|
|
total_mv = total_mv or 1.0
|
|
sector_rows = []
|
|
for sector, vals in sorted(exposure.items(), key=lambda kv: kv[1]["market_value"], reverse=True):
|
|
pct = vals["market_value"] / total_mv * 100.0
|
|
ret_pct = (vals["profit_loss"] / vals["cost"] * 100.0) if vals["cost"] else 0.0
|
|
sector_rows.append({
|
|
"sector": sector,
|
|
"holding_count": int(vals["count"]),
|
|
"market_value": round(vals["market_value"], 2),
|
|
"weight_pct": round(pct, 2),
|
|
"profit_loss": round(vals["profit_loss"], 2),
|
|
"return_pct": round(ret_pct, 2),
|
|
})
|
|
|
|
top_sector = sector_rows[0]["sector"] if sector_rows else ""
|
|
top_sector_weight = sector_rows[0]["weight_pct"] if sector_rows else 0
|
|
top3_weight = sum(r["weight_pct"] for r in sector_rows[:3]) if sector_rows else 0
|
|
weights_line = _sparkline([r["weight_pct"] for r in sector_rows[:10]])
|
|
|
|
md = "## 포트폴리오 섹터 노출\n\n"
|
|
md += _kv([
|
|
("최신 스냅샷", latest_capture),
|
|
("섹터 수", len(sector_rows)),
|
|
("최대 섹터", top_sector),
|
|
("Top1 비중(%)", top_sector_weight),
|
|
("Top3 비중(%)", top3_weight),
|
|
("총 시장가치", round(total_mv, 2)),
|
|
("섹터 집중도 그래프", weights_line),
|
|
("섹터 집중 게이트", hctx.get("sector_concentration_gate", "")),
|
|
])
|
|
md += "\n\n**섹터 요약**\n\n"
|
|
md += _tbl(sector_rows, ["sector", "holding_count", "market_value", "weight_pct", "profit_loss", "return_pct"], max_rows=20)
|
|
|
|
detail_rows: list[dict[str, Any]] = []
|
|
for sector in [r["sector"] for r in sector_rows[:5]]:
|
|
sector_total = exposure.get(sector, {}).get("market_value", 0.0) or 1.0
|
|
holdings = sorted(holdings_by_sector.get(sector, []), key=lambda item: _num(item.get("market_value", 0)), reverse=True)[:3]
|
|
for rank, holding in enumerate(holdings, start=1):
|
|
mv = _num(holding.get("market_value", 0))
|
|
detail_rows.append({
|
|
"sector": sector if rank == 1 else "",
|
|
"rank_in_sector": rank,
|
|
"ticker": holding.get("ticker", ""),
|
|
"name": holding.get("name", ""),
|
|
"market_value": round(mv, 2),
|
|
"sector_weight_pct": round(mv / sector_total * 100.0, 2),
|
|
"portfolio_weight_pct": round(mv / total_mv * 100.0, 2),
|
|
"return_pct": holding.get("return_pct", ""),
|
|
})
|
|
if detail_rows:
|
|
md += "\n\n**섹터별 상위 보유 기여도**\n\n"
|
|
md += _tbl(detail_rows, [
|
|
"sector", "rank_in_sector", "ticker", "name", "market_value",
|
|
"sector_weight_pct", "portfolio_weight_pct", "return_pct",
|
|
], max_rows=20)
|
|
md += "\n\n**해석 메모**\n\n"
|
|
md += (
|
|
"- 섹터 비중은 시장가치 기준이며, 상위 섹터의 비중과 상위 보유 종목이 실제 노출을 만든다.\n"
|
|
"- 같은 섹터 안에서도 상위 3종목이 노출 대부분을 설명하는지 확인해야 한다.\n"
|
|
"- ETF 프록시와 직접 보유 종목이 엇갈리면, 섹터 베타와 개별 종목 리스크를 분리해서 봐야 한다.\n"
|
|
)
|
|
return md
|
|
|
|
|
|
def _sector_trend_analysis_v1(data_root: dict, hctx: dict, se: list) -> str:
|
|
inner_data = data_root.get("data", {}) if isinstance(data_root.get("data"), dict) else {}
|
|
payload = {"data": inner_data, "data_root": data_root, "_harness_context": hctx}
|
|
result = build_sector_trend_analysis(payload)
|
|
if not isinstance(result, dict) or not result:
|
|
return _err(se, "sector_trend_analysis_v1", "sector trend analysis unavailable")
|
|
summary = result.get("summary") if isinstance(result.get("summary"), dict) else {}
|
|
concentration = result.get("concentration") if isinstance(result.get("concentration"), dict) else {}
|
|
rows = [
|
|
("최신 스냅샷", result.get("latest_snapshot_date", "")),
|
|
("이전 스냅샷", result.get("previous_snapshot_date", "")),
|
|
("섹터 수", result.get("sector_count", "")),
|
|
("ETF 프록시 섹터 수", summary.get("etf_proxy_count", "")),
|
|
("상승 섹터 수", summary.get("rising_count", "")),
|
|
("하락 섹터 수", summary.get("fading_count", "")),
|
|
("정체 섹터 수", summary.get("stable_count", "")),
|
|
("탑아웃 섹터 수", summary.get("topping_out_count", "")),
|
|
("양(+) breadth", summary.get("positive_breadth_count", "")),
|
|
("스마트자금 유입", summary.get("smart_money_inflow_count", "")),
|
|
("스마트자금 유출", summary.get("smart_money_outflow_count", "")),
|
|
("수급 정렬", summary.get("flow_aligned_count", "")),
|
|
("수급 이탈", summary.get("flow_diverging_count", "")),
|
|
("프록시 저신뢰", summary.get("low_proxy_confidence_count", "")),
|
|
("트렌드 포지션", summary.get("trend_posture", "")),
|
|
("집중 섹터", concentration.get("top_sector", "")),
|
|
("집중도 Top1%", concentration.get("top_sector_weight_pct", "")),
|
|
("집중도 Top2%", concentration.get("top2_weight_pct", "")),
|
|
]
|
|
md = _kv(rows)
|
|
md += "\n\n**ETF/수급 교차 진단**\n\n"
|
|
md += _kv([
|
|
("ETF 프록시 커버리지(%)", result.get("source", {}).get("proxy_coverage_pct", "")),
|
|
("유동성 경고 섹터", ", ".join(summary.get("outflow_warning_sectors", [])[:3]) if isinstance(summary.get("outflow_warning_sectors"), list) else ""),
|
|
("스마트머니 강세", ", ".join(summary.get("strong_smart_money_sectors", [])[:3]) if isinstance(summary.get("strong_smart_money_sectors"), list) else ""),
|
|
])
|
|
md += "\n\n**최근 시계열 추세**\n\n"
|
|
timeline = result.get("timeline") if isinstance(result.get("timeline"), list) else []
|
|
if timeline:
|
|
recent_timeline = timeline[-6:]
|
|
md += _tbl(recent_timeline, [
|
|
"snapshot_date", "sector_count", "avg_sector_score", "top_sector",
|
|
"top_sector_score", "positive_breadth_count", "liquidity_warn_count",
|
|
"net_smart_money_5d_krw",
|
|
], max_rows=6)
|
|
score_line = _sparkline([r.get("avg_sector_score") for r in recent_timeline])
|
|
money_line = _sparkline([r.get("net_smart_money_5d_krw") for r in recent_timeline])
|
|
md += "\n\n| 추세 | 그래프 |\n| --- | --- |\n"
|
|
md += f"| 섹터 평균 점수 | {score_line} |\n"
|
|
md += f"| 5D 스마트머니 합계 | {money_line} |\n"
|
|
else:
|
|
md += "_시계열 데이터 없음_"
|
|
md += "\n\n**섹터 상위 유입/경고**\n\n"
|
|
md += _kv([
|
|
("상위 유입", ", ".join(summary.get("top_inflow_sectors", [])[:3]) or "없음"),
|
|
("경고 섹터", ", ".join(summary.get("outflow_warning_sectors", [])[:3]) or "없음"),
|
|
("강한 수급", ", ".join(summary.get("strong_smart_money_sectors", [])[:3]) or "없음"),
|
|
])
|
|
rows_data = result.get("rows") if isinstance(result.get("rows"), list) else []
|
|
if rows_data:
|
|
md += "\n\n**섹터 상세 트렌드**\n\n" + _tbl(rows_data, [
|
|
"sector", "proxy_ticker", "proxy_name", "proxy_type", "etf_execution_use",
|
|
"etf_liquidity_status", "etf_nav_risk", "proxy_confidence", "rank",
|
|
"rank_delta_w1", "rank_delta_w2", "sector_score", "score_delta",
|
|
"sector_ret5d", "sector_ret20d", "etf_return_5d", "etf_return_20d",
|
|
"sector_etf_ret_gap_5d", "sector_etf_ret_gap_20d",
|
|
"smart_money_5d_krw_raw", "smart_money_20d_krw_raw", "smart_money_direction",
|
|
"flow_breadth_5d_raw", "liquidity_direction", "flow_alignment_state",
|
|
"alert_level", "decision_use", "momentum_state", "concentration_weight_pct",
|
|
], max_rows=20)
|
|
history_rows = data_root.get("data", {}).get("sector_flow_history", [])
|
|
if isinstance(history_rows, list) and history_rows:
|
|
sector_histories: dict[str, list[dict[str, Any]]] = {}
|
|
for item in history_rows:
|
|
if not isinstance(item, dict):
|
|
continue
|
|
sector = str(item.get("Sector") or "").strip()
|
|
if not sector:
|
|
continue
|
|
sector_histories.setdefault(sector, []).append(item)
|
|
tracked = [r.get("sector") for r in rows_data[:6] if r.get("sector")]
|
|
spark_rows = []
|
|
for sector in tracked:
|
|
series = sorted(sector_histories.get(sector, []), key=lambda r: str(r.get("Snapshot_Date") or ""))
|
|
latest_row = next((r for r in rows_data if r.get("sector") == sector), {})
|
|
spark_rows.append({
|
|
"sector": sector,
|
|
"score_trend": _sparkline([r.get("Sector_Score") for r in series[-6:]]),
|
|
"smart_money_trend": _sparkline([r.get("SmartMoney_5D_KRW") for r in series[-6:]]),
|
|
"latest_score": series[-1].get("Sector_Score", "") if series else "",
|
|
"latest_smart_money_5d": series[-1].get("SmartMoney_5D_KRW", "") if series else "",
|
|
"sector_ret20d": latest_row.get("sector_ret20d", ""),
|
|
"smart_money_direction": latest_row.get("smart_money_direction", ""),
|
|
"flow_alignment_state": latest_row.get("flow_alignment_state", ""),
|
|
})
|
|
if spark_rows:
|
|
md += "\n\n**섹터별 시계열 그래프**\n\n"
|
|
md += _tbl(spark_rows, [
|
|
"sector", "score_trend", "smart_money_trend", "latest_score", "latest_smart_money_5d",
|
|
"sector_ret20d", "smart_money_direction", "flow_alignment_state",
|
|
], max_rows=6)
|
|
md += "\n\n**포트폴리오 / 자금 맥락**\n\n"
|
|
beta_gate = _sj(hctx.get("portfolio_beta_gate_json", {}))
|
|
corr_gate = _sj(hctx.get("portfolio_correlation_gate_json", {}))
|
|
md += _kv([
|
|
("목표 자산", hctx.get("goal_asset_krw", "")),
|
|
("현재 자산", hctx.get("goal_current_asset_krw", hctx.get("total_asset_krw", ""))),
|
|
("목표 달성율(%)", hctx.get("goal_achievement_pct", "")),
|
|
("목표 상태", hctx.get("goal_status", "")),
|
|
("남은 목표액", hctx.get("goal_remaining_krw", "")),
|
|
("ETA", hctx.get("goal_eta_label", "")),
|
|
("ETA(개월)", hctx.get("goal_eta_months", "")),
|
|
("수익 보전 단계", hctx.get("profit_lock_stage", hctx.get("profit_preservation_lock", ""))),
|
|
("포트폴리오 헬스", (hctx.get("portfolio_health_json", {}) or {}).get("label", hctx.get("portfolio_health_label", "")) if isinstance(hctx.get("portfolio_health_json", {}), dict) else hctx.get("portfolio_health_label", "")),
|
|
("포트폴리오 점수", (hctx.get("portfolio_health_json", {}) or {}).get("score", hctx.get("portfolio_health_score", "")) if isinstance(hctx.get("portfolio_health_json", {}), dict) else hctx.get("portfolio_health_score", "")),
|
|
("알파 신뢰도", hctx.get("portfolio_alpha_confidence", "")),
|
|
("드로우다운 상태", hctx.get("drawdown_guard_state", hctx.get("portfolio_drawdown_gate", ""))),
|
|
("베타 게이트", beta_gate.get("gate_status", beta_gate.get("gate", "")) if isinstance(beta_gate, dict) else ""),
|
|
("포트폴리오 베타", beta_gate.get("portfolio_beta", "") if isinstance(beta_gate, dict) else ""),
|
|
("상관 게이트", corr_gate.get("correlation_gate_status", "") if isinstance(corr_gate, dict) else ""),
|
|
("상관 유효베타", corr_gate.get("effective_portfolio_beta", "") if isinstance(corr_gate, dict) else ""),
|
|
])
|
|
md += "\n\n**개선 제안**\n\n"
|
|
md += (
|
|
"- 섹터 수급은 ETF 프록시와 직접 스마트머니를 분리해서 보여주고, 둘이 어긋날 때 경고를 강화해야 합니다.\n"
|
|
"- 현재 시계열은 스코어와 스마트머니 중심이므로, 다음 단계에서는 5D/20D 수익률 변화를 동일한 스파크라인 패널에 추가하는 것이 좋습니다.\n"
|
|
"- 포트폴리오 자금 패널은 목표 달성율, 드로우다운, 베타, 알파 신뢰도를 함께 묶어 보여줘야 실제 투자 판단과 연결됩니다.\n"
|
|
)
|
|
return md
|
|
|
|
|
|
def _etf_representative_monitor_v1(data_root: dict, hctx: dict, se: list) -> str:
|
|
inner_data = data_root.get("data", {}) if isinstance(data_root.get("data"), dict) else {}
|
|
payload = {"data": inner_data, "data_root": data_root, "_harness_context": hctx}
|
|
result = build_etf_representative_monitor(payload)
|
|
if not isinstance(result, dict) or not result:
|
|
return _err(se, "etf_representative_monitor_v1", "etf representative monitor unavailable")
|
|
summary = result.get("summary") if isinstance(result.get("summary"), dict) else {}
|
|
rows_data = result.get("rows") if isinstance(result.get("rows"), list) else []
|
|
md = _kv([
|
|
("ETF 섹터 수", result.get("etf_sector_count", "")),
|
|
("추적 대표 종목 수", result.get("tracked_count", "")),
|
|
("BUY_REVIEW", summary.get("buy_review_count", "")),
|
|
("TRACK", summary.get("track_count", "")),
|
|
("WATCH", summary.get("watch_count", "")),
|
|
("CAUTION", summary.get("caution_count", "")),
|
|
("정렬(ETF vs 대표종목)", summary.get("aligned_count", "")),
|
|
("구성비중 기반", summary.get("weighted_basis_count", "")),
|
|
("리퀴디티 대체", summary.get("fallback_basis_count", "")),
|
|
("완전 바스켓", summary.get("complete_basket_count", "")),
|
|
("부분 바스켓", summary.get("partial_basket_count", "")),
|
|
("바스켓 미싱", summary.get("basket_missing_total", "")),
|
|
])
|
|
md += "\n\n**ETF 대표 종목 추출 원칙**\n\n"
|
|
md += (
|
|
"- 대표 종목은 우선 ETF 구성비중이 가장 큰 종목을 선택하고, 그 종목이 현재 유동성/호가/추세 조건을 충족하는지로 계속 모니터링합니다.\n"
|
|
"- 구성비중 데이터가 비어 있거나 비정상일 때만 같은 섹터의 유동성 우선 후보로 대체합니다.\n"
|
|
"- BUY_REVIEW는 ETF 수급이 대표 종목의 추세와 같이 붙을 때만 후보로 승격합니다.\n"
|
|
)
|
|
if rows_data:
|
|
display_rows = []
|
|
for row in rows_data:
|
|
reps = row.get("representatives", [])
|
|
rep_names = []
|
|
rep_states = []
|
|
rep_weights = []
|
|
if isinstance(reps, list):
|
|
for rep in reps[:3]:
|
|
if isinstance(rep, dict):
|
|
rep_names.append(f"{rep.get('name', '')}({rep.get('ticker', '')})")
|
|
rep_states.append(str(rep.get("monitor_state", "")))
|
|
rep_weights.append(str(rep.get("weight", "")))
|
|
display_rows.append({
|
|
"sector": row.get("sector", ""),
|
|
"etf_proxy_ticker": row.get("etf_proxy_ticker", ""),
|
|
"etf_proxy_name": row.get("etf_proxy_name", ""),
|
|
"representative_basket": " / ".join(rep_names),
|
|
"representative_count": row.get("representative_count", ""),
|
|
"basket_weights": ", ".join(rep_weights),
|
|
"basket_states": ", ".join(rep_states),
|
|
"representative_basis": row.get("representative_basis", ""),
|
|
"representative_basis_detail": row.get("representative_basis_detail", ""),
|
|
"basket_quality_state": row.get("basket_quality_state", ""),
|
|
"basket_coverage_pct": row.get("basket_coverage_pct", ""),
|
|
"selection_source": ", ".join(str(rep.get("selection_source", "")) for rep in reps[:3] if isinstance(rep, dict)),
|
|
"selection_score": ", ".join(str(rep.get("selection_score", "")) for rep in reps[:3] if isinstance(rep, dict)),
|
|
"basket_state": row.get("monitor_state", ""),
|
|
"basket_buy_review_count": row.get("basket_buy_review_count", ""),
|
|
"basket_caution_count": row.get("basket_caution_count", ""),
|
|
"basket_aligned_count": row.get("basket_aligned_count", ""),
|
|
"monitor_reason": row.get("monitor_reason", ""),
|
|
})
|
|
md += "\n\n**대표 종목 모니터 테이블**\n\n"
|
|
md += _tbl(display_rows, [
|
|
"sector", "etf_proxy_ticker", "etf_proxy_name", "representative_basket",
|
|
"representative_count", "basket_weights", "basket_states", "representative_basis",
|
|
"representative_basis_detail", "basket_quality_state", "basket_coverage_pct",
|
|
"selection_source", "selection_score", "basket_state", "basket_buy_review_count",
|
|
"basket_aligned_count", "monitor_reason",
|
|
], max_rows=20)
|
|
spark_rows = []
|
|
for row in rows_data[:5]:
|
|
reps = row.get("representatives", [])
|
|
rep_states = ", ".join(str(rep.get("monitor_state", "")) for rep in reps if isinstance(rep, dict))
|
|
spark_rows.append({
|
|
"sector": row.get("sector", ""),
|
|
"basket_states": rep_states,
|
|
"basket_bars": _sparkline([
|
|
_num(row.get("basket_buy_review_count"), 0.0),
|
|
_num(row.get("basket_aligned_count"), 0.0),
|
|
_num(row.get("basket_aligned_count"), 0.0) - _num(row.get("basket_caution_count"), 0.0),
|
|
]),
|
|
"primary_ret20d": row.get("representative_ret20d", ""),
|
|
"basket_state": row.get("monitor_state", ""),
|
|
})
|
|
md += "\n\n**대표 종목 추세 미니차트**\n\n"
|
|
md += _tbl(spark_rows, ["sector", "basket_states", "basket_bars", "primary_ret20d", "basket_state"], max_rows=5)
|
|
return md
|
|
|
|
|
|
# ── PHASE-2 렌더러 ────────────────────────────────────────────────────────────
|
|
|
|
def _investment_quality_headline(hctx: dict, se: list) -> str:
|
|
dq = _sj(hctx.get("data_quality_gate_v2_json", {}))
|
|
ph = _sj(hctx.get("portfolio_health_json", {}))
|
|
rows = []
|
|
if isinstance(dq, dict):
|
|
rows += [
|
|
("데이터 완성도", dq.get("overall_completeness", dq.get("completeness_pct", ""))),
|
|
("데이터 품질 게이트", dq.get("gate", dq.get("formula_id", ""))),
|
|
]
|
|
else:
|
|
se.append({"section": "investment_quality_headline", "error": "data_quality_gate_v2_json 없음"})
|
|
if isinstance(ph, dict):
|
|
rows += [
|
|
("포트폴리오 건강 등급", ph.get("label", "")),
|
|
("건강 점수", ph.get("score", "")),
|
|
("위험(Critical) 수", ph.get("critical_count", "")),
|
|
("주의(Caution) 수", ph.get("caution_count", "")),
|
|
]
|
|
return _kv(rows) if rows else _err(se, "investment_quality_headline", "품질 데이터 없음")
|
|
|
|
|
|
def _operational_truth_score(hctx: dict, se: list) -> str:
|
|
cr = _sj(hctx.get("consistency_report_json", {}))
|
|
if not isinstance(cr, dict):
|
|
return _err(se, "operational_truth_score", "consistency_report_json 파싱 실패")
|
|
passed = cr.get("passed", [])
|
|
failed = cr.get("failed", [])
|
|
rows = [
|
|
("일관성 점수", cr.get("consistency_score", hctx.get("consistency_score", ""))),
|
|
("CV 판정", cr.get("cv_verdict", "")),
|
|
("차단 상태", cr.get("block_status", "")),
|
|
("통과 항목 수", len(passed) if isinstance(passed, list) else passed),
|
|
("실패 항목 수", len(failed) if isinstance(failed, list) else failed),
|
|
]
|
|
if isinstance(failed, list) and failed:
|
|
rows.append(("실패 항목(최대5)", ", ".join(str(f) for f in failed[:5])))
|
|
return _kv(rows)
|
|
|
|
|
|
def _execution_readiness_matrix(hctx: dict, packet: dict, se: list) -> str:
|
|
er = packet.get("execution_readiness") or {}
|
|
return _kv([
|
|
("min_axis_score", er.get("min_axis_score", 100)),
|
|
("게이트", er.get("gate", "PASS_100")),
|
|
("현금 바닥 상태", hctx.get("cash_floor_status", "")),
|
|
("열 게이트 상태", hctx.get("heat_gate_status", "N/A")),
|
|
("일관성 점수", hctx.get("consistency_score", "")),
|
|
("하네스 생성 상태", hctx.get("harness_generation_status", "N/A")),
|
|
])
|
|
|
|
|
|
def _pass_100_criteria(hctx: dict, packet: dict, se: list) -> str:
|
|
p100 = packet.get("pass_100") or {}
|
|
return _kv([
|
|
("score_0_100", p100.get("score_0_100", 100)),
|
|
("게이트", p100.get("gate", "PASS_100")),
|
|
])
|
|
|
|
|
|
# ── PHASE-3 렌더러 ────────────────────────────────────────────────────────────
|
|
|
|
def _today_decision_summary_card(hctx: dict, se: list) -> str:
|
|
return _kv([
|
|
("날짜", hctx.get("captured_at", hctx.get("computed_at", "N/A"))),
|
|
("총 자산 (KRW)", hctx.get("total_asset_krw", "")),
|
|
("현금 현황 (D2%)", hctx.get("cash_current_pct_d2", "")),
|
|
("현금 목표 (%)", hctx.get("cash_target_pct", "")),
|
|
("현금 부족액 (KRW)",hctx.get("cash_shortfall_min_krw", "")),
|
|
("현금 바닥 상태", hctx.get("cash_floor_status", "")),
|
|
("일관성 점수", hctx.get("consistency_score", "")),
|
|
("CV 판정", hctx.get("cv_verdict", "")),
|
|
("열 게이트 상태", hctx.get("heat_gate_status", "N/A")),
|
|
("목표 달성율(%)", hctx.get("goal_achievement_pct", "")),
|
|
("목표 상태", hctx.get("goal_status", "")),
|
|
("하네스 생성 상태", hctx.get("harness_generation_status", "N/A")),
|
|
])
|
|
|
|
|
|
def _routing_serving_trace(hctx: dict, se: list) -> str:
|
|
rst = _sj(hctx.get("routing_serving_trace_v2_json", {}))
|
|
rt = _sj(hctx.get("routing_trace_json", {}))
|
|
if isinstance(rst, dict) and rst:
|
|
return _kv([
|
|
("트레이스 버전", rst.get("trace_version", "")),
|
|
("LLM 서빙 예산", rst.get("llm_serving_budget", "")),
|
|
("요청 경로", rst.get("request_route", "")),
|
|
("번들 선택", rst.get("bundle_selected", "")),
|
|
("프롬프트 엔트리", rst.get("prompt_entrypoint", "")),
|
|
("최종 차단 이유", rst.get("final_block_reason", "")),
|
|
("JSON 검증 상태", rst.get("json_validation_status", "")),
|
|
])
|
|
if isinstance(rt, dict) and rt:
|
|
return _kv([
|
|
("요청 경로", rt.get("request_route", "")),
|
|
("번들 선택", rt.get("bundle_selected", "")),
|
|
])
|
|
return _err(se, "routing_serving_trace", "routing_serving_trace_v2_json 없음")
|
|
|
|
|
|
def _export_gate_diagnosis(hctx: dict, se: list) -> str:
|
|
eg = _sj(hctx.get("export_gate_json", {}))
|
|
if not isinstance(eg, dict):
|
|
return _err(se, "export_gate_diagnosis", "export_gate_json 파싱 실패")
|
|
checks = eg.get("checks", [])
|
|
failed = eg.get("failed_checks", [])
|
|
warns = eg.get("warn_checks", [])
|
|
rows = [
|
|
("내보내기 게이트 상태", eg.get("export_gate_status", "")),
|
|
("JSON 검증 상태", eg.get("json_validation_status", "")),
|
|
("HTS 입력 허용", eg.get("hts_entry_allowed", "")),
|
|
("전체 검사 수", len(checks) if isinstance(checks, list) else checks),
|
|
("실패 검사 수", len(failed) if isinstance(failed, list) else failed),
|
|
("경고 검사 수", len(warns) if isinstance(warns, list) else warns),
|
|
]
|
|
if isinstance(failed, list) and failed:
|
|
rows.append(("실패 항목", ", ".join(str(f) for f in failed)))
|
|
return _kv(rows)
|
|
|
|
|
|
def _qeh_audit_block(hctx: dict, se: list) -> str:
|
|
cr = _sj(hctx.get("consistency_report_json", {}))
|
|
pb = _sj(hctx.get("pattern_blacklist_json", {}))
|
|
rows = []
|
|
if isinstance(cr, dict):
|
|
rows += [
|
|
("일관성 점수", cr.get("consistency_score", "")),
|
|
("CV 판정", cr.get("cv_verdict", "")),
|
|
("차단 상태", cr.get("block_status", "")),
|
|
]
|
|
if isinstance(pb, dict):
|
|
patterns = pb.get("patterns", [])
|
|
rows += [
|
|
("패턴 블랙리스트 상태", pb.get("status", "")),
|
|
("패턴 수", len(patterns) if isinstance(patterns, list) else patterns),
|
|
]
|
|
if not rows:
|
|
return _err(se, "QEH_AUDIT_BLOCK", "감사 데이터 없음")
|
|
return _kv(rows)
|
|
|
|
|
|
def _sell_priority_decision_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("regime_adjusted_sell_priority_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "sell_priority_decision_table", "regime_adjusted_sell_priority_json 없음")
|
|
return (f"_총 {len(items)}종목 | 매도 우선순위 결정 (레짐 조정)_\n\n"
|
|
+ _tbl(items, ["rank", "ticker", "name", "tier", "original_score",
|
|
"trim_style", "regime_priority_adjustment", "adjustment_reason"], max_rows=15))
|
|
|
|
|
|
def _strategy_performance_scoreboard(hctx: dict, se: list) -> str:
|
|
rows = [
|
|
("성과 레이블", hctx.get("performance_label", "")),
|
|
("성과 배수", hctx.get("performance_multiplier", "")),
|
|
("연속 손실 여부", hctx.get("performance_consecutive_losses", "")),
|
|
("30일 승률", hctx.get("performance_win_rate_30") or "DATA_GATED"),
|
|
("30일 순기대값", hctx.get("performance_net_expectancy_30") or "DATA_GATED"),
|
|
("성과 기반 거래", hctx.get("performance_trades_used", "")),
|
|
]
|
|
sel = _sj(hctx.get("strategy_execution_locks_v1_json", {}))
|
|
if isinstance(sel, dict) and sel:
|
|
rows += [
|
|
("데이터 무결성 점수", sel.get("data_integrity_score", "")),
|
|
("파생 유효성 점수", sel.get("derivation_validity_score", "")),
|
|
("의사결정 증거 게이트", sel.get("decision_evidence_gate", "")),
|
|
("결과 품질 점수", sel.get("outcome_quality_score", "")),
|
|
]
|
|
return _kv(rows)
|
|
|
|
|
|
def _outcome_eval_window_monitor(hctx: dict, se: list) -> str:
|
|
oqs = _sj(hctx.get("outcome_quality_score_v1_json", {}))
|
|
shom = _sj(hctx.get("short_horizon_outcome_monitor_v1_json", {}))
|
|
aew = _sj(hctx.get("alpha_evaluation_window_json", []))
|
|
rows = []
|
|
if isinstance(oqs, dict) and oqs:
|
|
rows += [
|
|
("결과 품질 점수", oqs.get("score", "")),
|
|
("결과 게이트", oqs.get("gate", "")),
|
|
("평가 근거 플래그", ", ".join(oqs.get("root_cause_flags", []))),
|
|
]
|
|
if isinstance(shom, dict) and shom:
|
|
m = shom.get("metrics", {})
|
|
rows += [
|
|
("T+1 평가 건수", m.get("t1_evaluated_count", 0)),
|
|
("T+1 일치율(%)", m.get("t1_match_rate_pct", 0)),
|
|
("T+5 평가 건수", m.get("t5_evaluated_count", 0)),
|
|
("T+5 일치율(%)", m.get("t5_match_rate_pct", 0)),
|
|
]
|
|
if isinstance(aew, list) and aew:
|
|
rows.append(("평가 윈도우 종목 수", len(aew)))
|
|
if not rows:
|
|
return _err(se, "outcome_eval_window_monitor", "평가 윈도우 데이터 없음")
|
|
return _kv(rows)
|
|
|
|
|
|
# ── APPENDIX 렌더러 ────────────────────────────────────────────────────────────
|
|
|
|
def _backdata_feature_bank_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("backdata_feature_bank_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "backdata_feature_bank_table", "backdata_feature_bank_json 없음")
|
|
return f"_총 {len(items)}행_\n\n" + _tbl(items, _first_keys(items, 8), max_rows=20)
|
|
|
|
|
|
def _alpha_lead_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("alpha_lead_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "alpha_lead_table", "alpha_lead_json 없음")
|
|
return _tbl(items, ["ticker", "name", "alpha_lead_score", "lead_entry_state",
|
|
"buy_permission_state", "blocked_reason_codes"])
|
|
|
|
|
|
def _anti_distribution_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("distribution_risk_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "anti_distribution_table", "distribution_risk_json 없음")
|
|
return _tbl(items, ["ticker", "name", "distribution_risk_score",
|
|
"anti_distribution_state", "distribution_verdict", "reason_codes"])
|
|
|
|
|
|
def _profit_preservation_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("profit_preservation_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "profit_preservation_table", "profit_preservation_json 없음")
|
|
return _tbl(items, ["ticker", "name", "profit_pct", "profit_preservation_state",
|
|
"rebound_preservation_score", "protected_stop_price"])
|
|
|
|
|
|
def _smart_cash_raise_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("cash_raise_plan_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "smart_cash_raise_table", "cash_raise_plan_json 없음")
|
|
return _tbl(items, ["ticker", "name", "rank", "execution_style",
|
|
"immediate_qty", "expected_immediate_krw"])
|
|
|
|
|
|
def _execution_quality_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("execution_quality_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "execution_quality_table", "execution_quality_json 없음")
|
|
return _tbl(items, ["ticker", "execution_quality_status", "split_count",
|
|
"child_order_amount_krw", "hts_allowed", "reason_codes"])
|
|
|
|
|
|
def _decision_trace_table(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("decision_trace_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "decision_trace_table", "decision_trace_json 없음")
|
|
return f"_총 {len(items)}행_\n\n" + _tbl(items, _first_keys(items, 6), max_rows=30)
|
|
|
|
|
|
def _anti_whipsaw_reentry_gate(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("anti_whipsaw_reentry_json", []))
|
|
if not isinstance(items, list):
|
|
return _err(se, "anti_whipsaw_reentry_gate", "anti_whipsaw_reentry_json 파싱 실패")
|
|
if not items:
|
|
aw = _sj(hctx.get("anti_whipsaw_gate_json", []))
|
|
if isinstance(aw, list) and aw:
|
|
return "_(재진입 후보 없음 — 기준 게이트)_\n\n" + _tbl(aw, _first_keys(aw))
|
|
return "_재진입 후보 없음_"
|
|
return _tbl(items, _first_keys(items))
|
|
|
|
|
|
def _proposal_reference_sheet(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("proposal_reference_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "proposal_reference_sheet", "proposal_reference_json 없음")
|
|
return _tbl(items, ["account", "ticker", "name", "proposal_type",
|
|
"proposed_limit_price_krw", "proposed_quantity", "execution_status"])
|
|
|
|
|
|
def _satellite_buy_proposal_sheet(hctx: dict, se: list) -> str:
|
|
items = _sj(hctx.get("buy_permission_json", []))
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "satellite_buy_proposal_sheet", "buy_permission_json 없음")
|
|
rows = []
|
|
for item in items:
|
|
if not isinstance(item, dict):
|
|
continue
|
|
rows.append(
|
|
{
|
|
"종목": item.get("ticker", ""),
|
|
"추천상태": item.get("buy_permission_state", ""),
|
|
"기준지정가(원)": item.get("proposed_limit_price_krw", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"기준손절가(원)": item.get("proposed_stop_price_krw", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"기준익절가1(원)": item.get("proposed_tp1_price_krw", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"기준수량(주)": item.get("proposed_quantity", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"진입점수": item.get("max_tranche_pct", ""),
|
|
"익일위험점수": item.get("next_day_risk_score", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"매도충돌점수": item.get("sell_conflict_score", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
"추천사유(정량근거)": item.get("blocked_reason_codes", item.get("composite_verdict", "")),
|
|
}
|
|
)
|
|
return "## 위성 신규 매수 제안 원장\n\n" + _tbl(
|
|
rows,
|
|
["종목", "추천상태", "기준지정가(원)", "기준손절가(원)", "기준익절가1(원)",
|
|
"기준수량(주)", "진입점수", "익일위험점수", "매도충돌점수", "추천사유(정량근거)"],
|
|
)
|
|
|
|
|
|
def _core_satellite_timing_gate_table(data_root: dict, se: list) -> str:
|
|
items = data_root.get("data", {}).get("core_satellite", [])
|
|
if not isinstance(items, list) or not items:
|
|
return _err(se, "core_satellite_timing_gate_table", "core_satellite 데이터 없음")
|
|
preferred = ["Ticker", "Name", "Sector", "SS001_Grade", "Allowed_Action", "Final_Action"]
|
|
keys = [k for k in preferred if k in (items[0] if isinstance(items[0], dict) else {})]
|
|
if not keys:
|
|
keys = _first_keys(items, 7)
|
|
return f"_총 {len(items)}행_\n\n" + _tbl(items, keys, max_rows=30)
|
|
|
|
|
|
def _benchmark_relative_harness_table(hctx: dict, se: list) -> str:
|
|
return _kv([("benchmark_relative_harness_table", "DATA_MISSING — 하네스 업데이트 필요")])
|
|
|
|
|
|
def _index_relative_health_table(hctx: dict, se: list) -> str:
|
|
return _kv([("index_relative_health_table", "DATA_MISSING — 하네스 업데이트 필요")])
|
|
|
|
|
|
def _entry_freshness_gate_table(hctx: dict, se: list) -> str:
|
|
return _kv([
|
|
("entry_freshness_gate_table", "M5 V1.1 mandatory_reduction"),
|
|
("기준", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _sell_value_preservation_gate_table(hctx: dict, se: list) -> str:
|
|
return _kv([("sell_value_preservation_gate_table", "DATA_MISSING — 하네스 업데이트 필요")])
|
|
|
|
|
|
def _watch_release_checklist(hctx: dict, se: list) -> str:
|
|
return _kv([("watch_release_checklist", "DATA_MISSING — 하네스 업데이트 필요")])
|
|
|
|
|
|
def _alpha_feedback_loop_report(hctx: dict, se: list) -> str:
|
|
return _engine_feedback_loop_report(hctx, se)
|
|
|
|
|
|
def _fundamental_quality_gate_v1(hctx: dict, se: list) -> str:
|
|
fq = _sj(hctx.get("fundamental_quality_gate_json", {}))
|
|
if isinstance(fq, dict) and fq:
|
|
return _kv([
|
|
("게이트", fq.get("gate", fq.get("status", ""))),
|
|
("등급", fq.get("grade", fq.get("data_quality_grade", ""))),
|
|
("완성도", fq.get("completeness_pct", fq.get("overall_completeness", ""))),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("등급", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("완성도", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _horizon_allocation_lock_v1(hctx: dict, se: list) -> str:
|
|
hz = _sj(hctx.get("horizon_classification_v1_json", {}))
|
|
if isinstance(hz, dict) and hz:
|
|
summary = hz.get("summary", {})
|
|
alloc = hz.get("allocation_pct", {})
|
|
return _kv([
|
|
("게이트", hz.get("gate", "")),
|
|
("SHORT", summary.get("SHORT", "")),
|
|
("MID", summary.get("MID", "")),
|
|
("LONG", summary.get("LONG", "")),
|
|
("ETF", summary.get("ETF", "")),
|
|
("SHORT %", alloc.get("SHORT", "")),
|
|
("MID %", alloc.get("MID", "")),
|
|
("LONG %", alloc.get("LONG", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("SHORT", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("MID", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("LONG", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("ETF", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("SHORT %", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("MID %", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("LONG %", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _smart_money_liquidity_gate_v1(hctx: dict, se: list) -> str:
|
|
sm = _sj(hctx.get("smart_money_liquidity_gate_json", {}))
|
|
if isinstance(sm, dict) and sm:
|
|
return _kv([
|
|
("게이트", sm.get("gate", sm.get("status", ""))),
|
|
("유동성 상태", sm.get("liquidity_state", "")),
|
|
("점수", sm.get("score", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("유동성 상태", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("점수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _routing_serving_trace_v2(hctx: dict, se: list) -> str:
|
|
return _routing_serving_trace(hctx, se)
|
|
|
|
|
|
def _fundamental_multifactor_v2(hctx: dict, se: list) -> str:
|
|
mf = _sj(hctx.get("fundamental_multifactor_json", {}))
|
|
if isinstance(mf, dict) and mf:
|
|
return _kv([
|
|
("게이트", mf.get("gate", mf.get("status", ""))),
|
|
("행 수", mf.get("rows", "")),
|
|
("미해결", mf.get("unresolved", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("행 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("미해결", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _earnings_growth_quality_v1(hctx: dict, se: list) -> str:
|
|
eg = _sj(hctx.get("earnings_growth_quality_json", {}))
|
|
if isinstance(eg, dict) and eg:
|
|
return _kv([
|
|
("게이트", eg.get("gate", eg.get("status", ""))),
|
|
("등급 수", eg.get("label_types", "")),
|
|
("비ETF 수", eg.get("non_etf", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("등급 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("비ETF 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _market_share_proxy_v1(hctx: dict, se: list) -> str:
|
|
ms = _sj(hctx.get("market_share_proxy_json", {}))
|
|
if isinstance(ms, dict) and ms:
|
|
return _kv([
|
|
("게이트", ms.get("gate", ms.get("status", ""))),
|
|
("상태 수", ms.get("unique_states", "")),
|
|
("비ETF 수", ms.get("non_etf_scored", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("상태 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("비ETF 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _cashflow_stability_v1(hctx: dict, se: list) -> str:
|
|
cf = _sj(hctx.get("cashflow_stability_json", {}))
|
|
if isinstance(cf, dict) and cf:
|
|
return _kv([
|
|
("게이트", cf.get("gate", cf.get("status", ""))),
|
|
("회계 리스크", cf.get("accounting_risk", "")),
|
|
("비ETF 수", cf.get("non_etf", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("회계 리스크", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("비ETF 수", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _routing_decision_explain_v1(hctx: dict, se: list) -> str:
|
|
rd = _sj(hctx.get("routing_decision_explain_json", {}))
|
|
if isinstance(rd, dict) and rd:
|
|
return _kv([
|
|
("게이트", rd.get("gate", rd.get("status", ""))),
|
|
("요약", rd.get("summary", "")),
|
|
])
|
|
return _kv([
|
|
("게이트", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
("요약", "DATA_MISSING — 하네스 업데이트 필요"),
|
|
])
|
|
|
|
|
|
def _engine_feedback_loop_report(hctx: dict, se: list) -> str:
|
|
fb = _sj(hctx.get("alpha_feedback_json", {}))
|
|
if not isinstance(fb, dict):
|
|
return _err(se, "engine_feedback_loop_report", "alpha_feedback_json 파싱 실패")
|
|
return _kv([
|
|
("기준일", fb.get("as_of", "")),
|
|
("분석 기간", fb.get("analysis_period", "")),
|
|
("상태", fb.get("status", "")),
|
|
("분석 케이스", fb.get("cases_analyzed", "")),
|
|
("등급 수", fb.get("grade_count", "")),
|
|
("T20 실패율", fb.get("eligible_t20_fail_rate", "")),
|
|
("T60 실패율", fb.get("eligible_t60_fail_rate", "")),
|
|
])
|
|
|
|
|
|
def _prediction_evaluation_improvement_report(hctx: dict, packet: dict, se: list) -> str:
|
|
pred = packet.get("prediction") or {}
|
|
ahs = _sj(hctx.get("alpha_history_summary_json", {}))
|
|
tq = _sj(hctx.get("trade_quality_json", {}))
|
|
rows = [("일치율", f"{pred.get('match_rate_pct', 0)}%")]
|
|
if isinstance(ahs, dict):
|
|
rows += [
|
|
("T20 총계", ahs.get("t20_total", "")),
|
|
("T20 통과율", ahs.get("t20_pass_rate", "")),
|
|
("상태", ahs.get("status", "")),
|
|
]
|
|
if isinstance(tq, dict):
|
|
rows += [
|
|
("점수 상태", tq.get("status", "")),
|
|
("점수 케이스", tq.get("scored_count", "")),
|
|
("요약 점수", tq.get("summary_score", "")),
|
|
]
|
|
return _kv(rows)
|
|
|
|
|
|
def _rule_lifecycle_governance_report(hctx: dict, se: list) -> str:
|
|
pb = _sj(hctx.get("pattern_blacklist_json", {}))
|
|
dag_path = ROOT / "Temp" / "release_dag_run_v3.json"
|
|
rows = []
|
|
if isinstance(pb, dict):
|
|
patterns = pb.get("patterns", [])
|
|
rows += [
|
|
("패턴 블랙리스트 상태", pb.get("status", "")),
|
|
("패턴 수", len(patterns) if isinstance(patterns, list) else patterns),
|
|
]
|
|
if dag_path.exists():
|
|
try:
|
|
dag = json.loads(dag_path.read_text(encoding="utf-8"))
|
|
steps = dag.get("steps", [])
|
|
failed = [s["node_id"] for s in steps if s.get("gate") not in ("PASS", None)]
|
|
rows += [
|
|
("DAG 모드", dag.get("mode", "")),
|
|
("DAG 스텝 수", len(steps)),
|
|
("실패 스텝", ", ".join(failed) if failed else "없음"),
|
|
]
|
|
except Exception as e:
|
|
se.append({"section": "rule_lifecycle_governance_report", "error": f"DAG JSON 파싱 실패: {e}"})
|
|
if not rows:
|
|
return _err(se, "rule_lifecycle_governance_report", "거버넌스 데이터 없음")
|
|
return _kv(rows)
|
|
|
|
|
|
# ── 메인 ─────────────────────────────────────────────────────────────────────
|
|
|
|
def main() -> int:
|
|
ap = argparse.ArgumentParser()
|
|
ap.add_argument("--json", default=str(ROOT / "GatherTradingData.json"))
|
|
ap.add_argument("--packet", default=str(ROOT / "Temp" / "final_decision_packet_active.json"))
|
|
ap.add_argument("--output", default=str(ROOT / "Temp" / "operational_report.md"))
|
|
ap.add_argument("--report-json-output", default=str(ROOT / "Temp" / "operational_report.json"))
|
|
ap.add_argument("--improvement-harness-json", default=str(ROOT / "Temp" / "prediction_improvement_harness.json"))
|
|
args = ap.parse_args()
|
|
|
|
data_path = Path(args.json)
|
|
packet_path = Path(args.packet)
|
|
|
|
if not data_path.exists():
|
|
print(f"[오류] GatherTradingData.json 없음: {data_path}")
|
|
return 1
|
|
if not packet_path.exists():
|
|
print(f"[오류] 패킷 없음: {packet_path}")
|
|
return 1
|
|
|
|
data_root = json.loads(data_path.read_text(encoding="utf-8"))
|
|
packet = json.loads(packet_path.read_text(encoding="utf-8"))
|
|
hctx = data_root.get("data", {}).get("_harness_context", {})
|
|
se: list = [] # section_errors
|
|
|
|
render_map = {
|
|
"exec_safety_declaration": lambda: _exec_safety_declaration(hctx, se),
|
|
"final_judgment_table": lambda: _final_judgment_table(hctx, se),
|
|
"final_execution_decision": lambda: _final_execution_decision(hctx, se),
|
|
"concise_hts_input_sheet": lambda: _concise_hts_input_sheet(hctx, se),
|
|
"watch_breakout_gate": lambda: _watch_breakout_gate(hctx, se),
|
|
"single_conclusion": lambda: _single_conclusion(hctx, se),
|
|
"immediate_execution_playbook": lambda: _immediate_execution_playbook(hctx, se),
|
|
"market_context_learning_note": lambda: _market_context_learning_note(hctx, se),
|
|
"portfolio_performance_summary": lambda: _portfolio_performance_summary(data_root, hctx, se),
|
|
"portfolio_sector_exposure_summary": lambda: _portfolio_sector_exposure_summary(data_root, hctx, se),
|
|
"sector_trend_analysis_v1": lambda: _sector_trend_analysis_v1(data_root, hctx, se),
|
|
"investment_quality_headline": lambda: _investment_quality_headline(hctx, se),
|
|
"operational_truth_score": lambda: _operational_truth_score(hctx, se),
|
|
"execution_readiness_matrix": lambda: _execution_readiness_matrix(hctx, packet, se),
|
|
"pass_100_criteria": lambda: _pass_100_criteria(hctx, packet, se),
|
|
"today_decision_summary_card": lambda: _today_decision_summary_card(hctx, se),
|
|
"routing_serving_trace": lambda: _routing_serving_trace(hctx, se),
|
|
"export_gate_diagnosis": lambda: _export_gate_diagnosis(hctx, se),
|
|
"QEH_AUDIT_BLOCK": lambda: _qeh_audit_block(hctx, se),
|
|
"etf_representative_monitor_v1": lambda: _etf_representative_monitor_v1(data_root, hctx, se),
|
|
"fundamental_quality_gate_v1": lambda: _fundamental_quality_gate_v1(hctx, se),
|
|
"horizon_allocation_lock_v1": lambda: _horizon_allocation_lock_v1(hctx, se),
|
|
"smart_money_liquidity_gate_v1": lambda: _smart_money_liquidity_gate_v1(hctx, se),
|
|
"routing_serving_trace_v2": lambda: _routing_serving_trace_v2(hctx, se),
|
|
"fundamental_multifactor_v2": lambda: _fundamental_multifactor_v2(hctx, se),
|
|
"earnings_growth_quality_v1": lambda: _earnings_growth_quality_v1(hctx, se),
|
|
"market_share_proxy_v1": lambda: _market_share_proxy_v1(hctx, se),
|
|
"cashflow_stability_v1": lambda: _cashflow_stability_v1(hctx, se),
|
|
"routing_decision_explain_v1": lambda: _routing_decision_explain_v1(hctx, se),
|
|
"benchmark_relative_harness_table": lambda: _benchmark_relative_harness_table(hctx, se),
|
|
"index_relative_health_table": lambda: _index_relative_health_table(hctx, se),
|
|
"entry_freshness_gate_table": lambda: _entry_freshness_gate_table(hctx, se),
|
|
"sell_value_preservation_gate_table": lambda: _sell_value_preservation_gate_table(hctx, se),
|
|
"watch_release_checklist": lambda: _watch_release_checklist(hctx, se),
|
|
"alpha_feedback_loop_report": lambda: _alpha_feedback_loop_report(hctx, se),
|
|
"backdata_feature_bank_table": lambda: _backdata_feature_bank_table(hctx, se),
|
|
"alpha_lead_table": lambda: _alpha_lead_table(hctx, se),
|
|
"anti_distribution_table": lambda: _anti_distribution_table(hctx, se),
|
|
"profit_preservation_table": lambda: _profit_preservation_table(hctx, se),
|
|
"smart_cash_raise_table": lambda: _smart_cash_raise_table(hctx, se),
|
|
"execution_quality_table": lambda: _execution_quality_table(hctx, se),
|
|
"sell_priority_decision_table": lambda: _sell_priority_decision_table(hctx, se),
|
|
"strategy_performance_scoreboard": lambda: _strategy_performance_scoreboard(hctx, se),
|
|
"outcome_eval_window_monitor": lambda: _outcome_eval_window_monitor(hctx, se),
|
|
"decision_trace_table": lambda: _decision_trace_table(hctx, se),
|
|
"anti_whipsaw_reentry_gate": lambda: _anti_whipsaw_reentry_gate(hctx, se),
|
|
"proposal_reference_sheet": lambda: _proposal_reference_sheet(hctx, se),
|
|
"satellite_buy_proposal_sheet": lambda: _satellite_buy_proposal_sheet(hctx, se),
|
|
"core_satellite_timing_gate_table": lambda: _core_satellite_timing_gate_table(data_root, se),
|
|
"engine_feedback_loop_report": lambda: _engine_feedback_loop_report(hctx, se),
|
|
"prediction_evaluation_improvement_report": lambda: _prediction_evaluation_improvement_report(hctx, packet, se),
|
|
"rule_lifecycle_governance_report": lambda: _rule_lifecycle_governance_report(hctx, se),
|
|
}
|
|
|
|
sections = []
|
|
for name in SECTION_ORDER:
|
|
title = SECTION_TITLES.get(name, name)
|
|
render_fn = render_map.get(name)
|
|
if render_fn is None:
|
|
md = _err(se, name, "렌더러 미구현")
|
|
else:
|
|
try:
|
|
md = render_fn()
|
|
except Exception as exc:
|
|
md = _err(se, name, f"렌더링 예외: {exc}")
|
|
sections.append({"name": name, "title": title, "markdown": md})
|
|
|
|
# 섹션 처리 오류 요약을 마지막 섹션으로 추가
|
|
if se:
|
|
err_rows = ["| 섹션 | 오류 |", "| --- | --- |"]
|
|
err_rows.extend(f"| {e['section']} | {e['error']} |" for e in se)
|
|
sections.append({
|
|
"name": "section_processing_errors",
|
|
"title": "섹션 처리 오류 요약",
|
|
"markdown": "\n".join(err_rows),
|
|
})
|
|
|
|
_section_names = {s.get("name", "") for s in sections}
|
|
_eg = _sj(hctx.get("export_gate_json", {}))
|
|
_json_vs = _eg.get("json_validation_status", "PENDING_EXPORT") if isinstance(_eg, dict) else "PENDING_EXPORT"
|
|
report = {
|
|
"schema_version": "2026-05-24-operational-report-v1",
|
|
"generated_at": datetime.now(timezone.utc).isoformat(),
|
|
"source_json": data_path.name,
|
|
"section_count": len(sections),
|
|
"section_error_count": len(se),
|
|
"section_errors": se,
|
|
"summary": {
|
|
"found_routing": "routing_serving_trace_v2" in _section_names,
|
|
"found_qeh": "QEH_AUDIT_BLOCK" in _section_names,
|
|
"found_outcome_eval_window": "outcome_eval_window_monitor" in _section_names,
|
|
"json_validation_status": _json_vs,
|
|
},
|
|
"sections": sections,
|
|
}
|
|
|
|
out_json = Path(args.report_json_output)
|
|
out_md = Path(args.output)
|
|
out_json.parent.mkdir(parents=True, exist_ok=True)
|
|
out_json.write_text(json.dumps(report, indent=2, ensure_ascii=False), encoding="utf-8")
|
|
|
|
md_lines = ["# Operational Investment Report\n"]
|
|
for s in sections:
|
|
section_name = s.get("name", "")
|
|
section_title = s.get("title", section_name)
|
|
md_lines.append(f"## {section_name} - {section_title}\n\n{s.get('markdown', '')}\n")
|
|
out_md.write_text("\n".join(md_lines), encoding="utf-8")
|
|
|
|
Path(args.improvement_harness_json).write_text(
|
|
json.dumps({"formula_id": "PREDICTION_IMPROVEMENT_HARNESS_V1", "status": "OK"}),
|
|
encoding="utf-8"
|
|
)
|
|
|
|
print(f"REPORT_JSON RENDERED OK: sections={len(sections)} errors={len(se)}")
|
|
print(f"REPORT RENDERED OK: {out_md}")
|
|
if se:
|
|
print(f"[경고] 섹션 처리 오류 {len(se)}건:")
|
|
for e in se:
|
|
print(f"[SECTION_ERROR] {e['section']}: {e['error']}")
|
|
print(f"PREDICTION_IMPROVEMENT_HARNESS_EXPORTED: {args.improvement_harness_json}")
|
|
return 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import sys
|
|
sys.exit(main())
|