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2026-07-19 228d838fdb7f7dde7edc4993fdbb9654c9c31df7
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from __future__ import annotations
 
import csv
import hashlib
import json
from datetime import datetime, timezone, timedelta
from pathlib import Path
 
 
PROJECT_ROOT = Path(__file__).resolve().parents[4]
RUN_ID = "RUN-ANA-WUJI-V1-FINAL-CONCLUSION-20260610-001"
TASK_ID = "ANA-WUJI-V1-FINAL-CONCLUSION-20260610"
SOURCE_RUN_ID = "RUN-ANA-WUJI-STRICT-SELL-ROLLING-REPAIR-20260609-001"
SOURCE_DIR = PROJECT_ROOT / "ana-data" / "result" / SOURCE_RUN_ID
OUT_DIR = PROJECT_ROOT / "ana-data" / "result" / RUN_ID
SOURCE_AUDIT_ID = "AUDIT-ANA-WUJI-STRICT-SELL-ROLLING-REPAIR-20260610-EXEC-REREVIEW-003"
DESIGN_AUDIT_ID = "AUDIT-ANA-WUJI-V1-FINAL-CONCLUSION-20260610-DESIGN-001"
 
 
def now_iso() -> str:
    return datetime.now(timezone(timedelta(hours=8))).isoformat(timespec="seconds")
 
 
def read_csv(path: Path) -> list[dict[str, str]]:
    with path.open("r", encoding="utf-8-sig", newline="") as f:
        return list(csv.DictReader(f))
 
 
def write_csv(path: Path, rows: list[dict[str, object]], fieldnames: list[str] | None = None) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    if fieldnames is None:
        fieldnames = list(rows[0].keys()) if rows else []
    with path.open("w", encoding="utf-8-sig", newline="") as f:
        writer = csv.DictWriter(f, fieldnames=fieldnames)
        writer.writeheader()
        for row in rows:
            writer.writerow(row)
 
 
def write_json(path: Path, data: object) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
 
 
def sha256(path: Path) -> str:
    h = hashlib.sha256()
    with path.open("rb") as f:
        for chunk in iter(lambda: f.read(1024 * 1024), b""):
            h.update(chunk)
    return h.hexdigest()
 
 
def file_row(path: Path, root: Path = PROJECT_ROOT) -> dict[str, object]:
    return {
        "path": path.relative_to(root).as_posix(),
        "size": path.stat().st_size,
        "sha256": sha256(path),
    }
 
 
def source_manifest(paths: list[Path]) -> list[dict[str, object]]:
    rows = []
    for p in paths:
        row = file_row(p)
        row["source_run_id"] = SOURCE_RUN_ID
        rows.append(row)
    return rows
 
 
def copy_boundary(source_rows: list[dict[str, str]]) -> list[dict[str, object]]:
    rows = []
    for r in source_rows:
        rows.append(
            {
                "boundary_id": r.get("boundary_id", ""),
                "boundary_level": r.get("boundary_level", ""),
                "case_id": r.get("case_id", ""),
                "source_lot_id": r.get("source_lot_id", ""),
                "symbol": r.get("symbol", ""),
                "boundary_category": r.get("boundary_category", ""),
                "boundary_reason": r.get("boundary_reason", ""),
                "source_table": "strict_boundary_table.csv",
                "readout_policy": "boundary_only_not_primary_return",
            }
        )
    return rows
 
 
def forbidden_claims(text: str) -> list[str]:
    claims = [
        "完整 baseline 成功率为",
        "完整 baseline 收益率为",
        "无边界 baseline 成功率",
        "无边界 baseline 收益率",
        "策略有效性已证明",
        "策略有效性已经证明",
    ]
    return [c for c in claims if c in text]
 
 
def main() -> None:
    OUT_DIR.mkdir(parents=True, exist_ok=True)
    source_paths = [
        SOURCE_DIR / "summary.json",
        SOURCE_DIR / "summary.md",
        SOURCE_DIR / "strict_case_summary.csv",
        SOURCE_DIR / "strict_return_scope_case.csv",
        SOURCE_DIR / "strict_return_scope_lot.csv",
        SOURCE_DIR / "strict_boundary_table.csv",
        SOURCE_DIR / "manual_decision_external_draft.md",
        SOURCE_DIR / "manual_decision_external_source_ledger.csv",
        SOURCE_DIR / "manual_decision_ledger.csv",
        SOURCE_DIR / "strict_order_ledger.csv",
        SOURCE_DIR / "strict_position_lot_ledger.csv",
        SOURCE_DIR / "case_image_board.md",
        SOURCE_DIR / "manifest.json",
    ]
    missing_sources = [p for p in source_paths if not p.exists()]
    if missing_sources:
        raise FileNotFoundError("Missing source files: " + ", ".join(str(p) for p in missing_sources))
 
    summary = json.loads((SOURCE_DIR / "summary.json").read_text(encoding="utf-8"))
    case_rows = read_csv(SOURCE_DIR / "strict_case_summary.csv")
    lot_rows = read_csv(SOURCE_DIR / "strict_return_scope_lot.csv")
    boundary_rows = read_csv(SOURCE_DIR / "strict_boundary_table.csv")
    order_rows = read_csv(SOURCE_DIR / "strict_order_ledger.csv")
 
    primary_cases = [r for r in case_rows if r.get("v1_primary_strict_closed_case_flag") == "1"]
    positive_cases = [r for r in primary_cases if r.get("v1_case_success_flag") == "1"]
    boundary_cases = [r for r in case_rows if r.get("v1_return_scope") != "V1_PRIMARY_STRICT_CLOSED_CASE"]
    closed_lots = [r for r in lot_rows if r.get("v1_lot_scope") == "V1_STRICT_CLOSED_LOT_RECALC_ONLY"]
    boundary_lots = [r for r in lot_rows if r.get("v1_lot_scope") != "V1_STRICT_CLOSED_LOT_RECALC_ONLY"]
    rolling_buy_orders = [
        r
        for r in order_rows
        if r.get("action") == "BUY"
        and r.get("tranche_index") == "2"
    ]
 
    account_contribution = round(sum(float(r.get("account_return_closed_lots") or 0) for r in primary_cases), 8)
    success_rate = round(len(positive_cases) / len(primary_cases), 10) if primary_cases else 0
 
    readouts = [
        {
            "readout_id": "V1_PRIMARY_STRICT_CLOSED_CASE",
            "scope": "V1 主口径严格闭合 case",
            "case_count": len(primary_cases),
            "positive_case_count": len(positive_cases),
            "non_positive_case_count": len(primary_cases) - len(positive_cases),
            "success_rate": f"{success_rate:.10f}".rstrip("0").rstrip("."),
            "account_contribution_sum": f"{account_contribution:.8f}",
            "lot_count": "",
            "boundary_count": "",
            "source": "strict_case_summary.csv",
            "citation_boundary": "必须同时引用 V1 口径、执行复审审计 ID、v1_boundary_table.csv 和 MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD。",
        },
        {
            "readout_id": "V1_ALL_BUY_CASE_COVERAGE",
            "scope": "V1 有 BUY case 覆盖口径",
            "case_count": len(case_rows),
            "positive_case_count": "",
            "non_positive_case_count": "",
            "success_rate": "",
            "account_contribution_sum": "",
            "lot_count": "",
            "boundary_count": len(boundary_cases),
            "source": "strict_case_summary.csv",
            "citation_boundary": "只说明 V1 已买入 case 覆盖和边界,不替代主成功率分母。",
        },
        {
            "readout_id": "V1_STRICT_CLOSED_LOT_RECALC_ONLY",
            "scope": "V1 lot 复算辅助口径",
            "case_count": "",
            "positive_case_count": "",
            "non_positive_case_count": "",
            "success_rate": "",
            "account_contribution_sum": "",
            "lot_count": len(lot_rows),
            "boundary_count": len(boundary_lots),
            "source": "strict_return_scope_lot.csv",
            "citation_boundary": "只用于 lot 复算和问题定位,不包装成 case 成功率。",
        },
        {
            "readout_id": "V1_ROLLING_LOW_BUY",
            "scope": "滚动低吸 BUY 订单",
            "case_count": "",
            "positive_case_count": "",
            "non_positive_case_count": "",
            "success_rate": "",
            "account_contribution_sum": "",
            "lot_count": len(rolling_buy_orders),
            "boundary_count": "",
            "source": "strict_order_ledger.csv",
            "citation_boundary": "只说明滚动低吸执行数量,不单独构成策略有效性结论。",
        },
    ]
    write_csv(OUT_DIR / "v1_final_readouts.csv", readouts)
 
    case_index = []
    for r in case_rows:
        case_id = r.get("case_id", "")
        case_index.append(
            {
                "case_id": case_id,
                "v1_return_scope": r.get("v1_return_scope", ""),
                "primary_flag": r.get("v1_primary_strict_closed_case_flag", ""),
                "success_flag": r.get("v1_case_success_flag", ""),
                "buy_lot_count": r.get("buy_lot_count", ""),
                "closed_lot_count": r.get("closed_lot_count", ""),
                "unresolved_lot_count": r.get("unresolved_lot_count", ""),
                "account_return_closed_lots": r.get("account_return_closed_lots", ""),
                "boundary_reason": r.get("v1_boundary_reason", ""),
                "case_image_board": f"../{SOURCE_RUN_ID}/cases/{case_id}/case_image_board.md",
                "case_story_board": f"../{SOURCE_RUN_ID}/cases/{case_id}/case_story_board.md",
            }
        )
    write_csv(OUT_DIR / "v1_case_readout_index.csv", case_index)
 
    v1_boundary = copy_boundary(boundary_rows)
    write_csv(OUT_DIR / "v1_boundary_table.csv", v1_boundary)
 
    src_manifest = source_manifest(source_paths)
    write_csv(OUT_DIR / "source_artifact_manifest.csv", src_manifest)
 
    top_positive = sorted(primary_cases, key=lambda r: float(r.get("account_return_closed_lots") or 0), reverse=True)[:3]
    top_negative = sorted(primary_cases, key=lambda r: float(r.get("account_return_closed_lots") or 0))[:3]
    boundary_example = boundary_cases[:1]
 
    def case_link(r: dict[str, str]) -> str:
        case_id = r.get("case_id", "")
        ret = r.get("account_return_closed_lots", "")
        return f"- `{case_id}`,收益贡献 `{ret}`,[图片板](../{SOURCE_RUN_ID}/cases/{case_id}/case_image_board.md),[故事板](../{SOURCE_RUN_ID}/cases/{case_id}/case_story_board.md)"
 
    human_review = f"""# 无忌 V1 最终结论人工审核第一入口
 
## 先看这里
 
可以引用:当前 V1 执行包已通过执行复审。允许按 `V1_PRIMARY_STRICT_CLOSED_CASE` 主口径引用 250 个严格闭合 case 的读数:99 个为正收益,成功率读数为 0.396,账户贡献合计读数为 0.12970642。
 
必须同时引用:V1 口径、执行复审审计 ID `{SOURCE_AUDIT_ID}`、`v1_boundary_table.csv`,以及 `MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD`。
 
不能引用:不能把 V1 读数写成旧 V0 包结论,不能写成无边界完整 baseline 结论,不能作出无忌策略有效性的证明结论,不能省略市场风险分钟广度数据缺口。
 
当前状态:
 
| 项目 | 内容 |
|---|---|
| 当前 run | `{RUN_ID}` |
| 来源 run | `{SOURCE_RUN_ID}` |
| 来源执行复审审计 ID | `{SOURCE_AUDIT_ID}` |
| 当前设计审核审计 ID | `{DESIGN_AUDIT_ID}` |
| RETURN_STAT_READY | `false` |
| 执行审核状态 | `待提交执行审核` |
 
## V1 三层读数
 
1. `V1_PRIMARY_STRICT_CLOSED_CASE`:250 个严格闭合 case,正收益 99 个,成功率读数 0.396,账户贡献合计 0.12970642。
2. `V1_ALL_BUY_CASE_COVERAGE`:251 个有 BUY case,其中 1 个 case 进入边界表;该口径不替代主成功率。
3. `V1_STRICT_CLOSED_LOT_RECALC_ONLY`:735 个 lot,其中 734 个闭合、1 个边界;lot 口径只用于复算和问题定位。
 
## 第一入口链接
 
- 来源 V1 图片总入口:[case_image_board.md](../{SOURCE_RUN_ID}/case_image_board.md)
- 来源 V1 摘要:[summary.md](../{SOURCE_RUN_ID}/summary.md)
- 来源 V1 手工裁决草稿:[manual_decision_external_draft.md](../{SOURCE_RUN_ID}/manual_decision_external_draft.md)
- 当前 V1 结论摘要:[v1_final_conclusion_summary.md](v1_final_conclusion_summary.md)
- 当前 V1 读数表:[v1_final_readouts.csv](v1_final_readouts.csv)
- 当前 V1 case 索引:[v1_case_readout_index.csv](v1_case_readout_index.csv)
- 当前 V1 边界表:[v1_boundary_table.csv](v1_boundary_table.csv)
 
## 代表性 case
 
主口径正收益较高样例:
{chr(10).join(case_link(r) for r in top_positive)}
 
主口径负收益较低样例:
{chr(10).join(case_link(r) for r in top_negative)}
 
边界样例:
{chr(10).join(case_link(r) for r in boundary_example)}
 
## 阅读提示
 
1. 先看本文件的可引用 / 不可引用边界。
2. 再看 `v1_final_conclusion_summary.md` 了解整体读数。
3. 需要追溯单个案例时,从 `v1_case_readout_index.csv` 找到 `case_id`,再打开对应图片板和故事板。
4. 对卖点和滚动低吸的人工裁决来源,优先看 `manual_decision_external_draft.md` 和 `manual_decision_ledger.csv`。源单 case 图板中的图片是主要证据入口;文字理由以本包摘要、手工裁决草稿和账本字段为准。
"""
    (OUT_DIR / "v1_final_human_review_index.md").write_text(human_review, encoding="utf-8")
 
    summary_md = f"""# 无忌 V1 最终结论引用包摘要
 
## 当前可引用状态
 
当前包基于已通过执行复审的 V1 结果包生成,来源审计 ID 为 `{SOURCE_AUDIT_ID}`。本包仍需执行审核;执行审核通过前,不得把 V1 读数写入正式最终案例总结。
 
## V1 主口径:V1_PRIMARY_STRICT_CLOSED_CASE
 
| 指标 | 读数 |
|---|---:|
| V1 主口径严格闭合 case | {len(primary_cases)} |
| V1 主口径正收益 case | {len(positive_cases)} |
| V1 主口径非正收益 case | {len(primary_cases) - len(positive_cases)} |
| V1 主口径成功率读数 | {success_rate:.10f} |
| V1 主口径账户贡献合计读数 | {account_contribution:.8f} |
 
## 覆盖口径
 
| 指标 | 读数 |
|---|---:|
| V1 有 BUY case | {len(case_rows)} |
| V1 边界 case | {len(boundary_cases)} |
| 滚动低吸 BUY 订单 | {len(rolling_buy_orders)} |
 
## lot 辅助口径
 
| 指标 | 读数 |
|---|---:|
| V1 lot 总数 | {len(lot_rows)} |
| V1 闭合 lot | {len(closed_lots)} |
| V1 边界 lot | {len(boundary_lots)} |
 
## 边界
 
`v1_boundary_table.csv` 完整保留来源边界表,共 {len(v1_boundary)} 行。必须特别保留 `MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD`,它表示本地数据源没有开盘 10 分钟全 A 下跌家数分钟级广度,市场风险卖点不能被无边界化。
 
## 禁止外推
 
1. 不得把 V1 读数写成旧 V0 包结论。
2. 不得写成无边界完整 baseline 成功率、收益率、胜率或回撤。
3. 不得作出无忌策略有效性的证明结论。
4. 不得省略审计 ID、V1 口径、边界表和市场风险分钟广度数据缺口。
"""
    (OUT_DIR / "v1_final_conclusion_summary.md").write_text(summary_md, encoding="utf-8")
 
    summary_json = {
        "schema_version": "1.0",
        "task_id": TASK_ID,
        "run_id": RUN_ID,
        "source_run_id": SOURCE_RUN_ID,
        "source_execution_rereview_audit_id": SOURCE_AUDIT_ID,
        "design_audit_id": DESIGN_AUDIT_ID,
        "generated_at": now_iso(),
        "execution_review_status": "PENDING_EXECUTION_REVIEW",
        "return_stat_ready": False,
        "readouts": {
            "v1_buy_case_count": len(case_rows),
            "v1_primary_strict_closed_cases": len(primary_cases),
            "v1_positive_primary_cases": len(positive_cases),
            "v1_primary_success_readout": success_rate,
            "v1_primary_account_contribution_readout": account_contribution,
            "v1_lot_total": len(lot_rows),
            "v1_closed_lots": len(closed_lots),
            "v1_boundary_lots": len(boundary_lots),
            "rolling_low_buy_orders": len(rolling_buy_orders),
            "boundary_rows": len(v1_boundary),
        },
        "required_citation_context": [
            "V1 scope",
            SOURCE_AUDIT_ID,
            "v1_boundary_table.csv",
            "MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD",
        ],
        "forbidden": [
            "old V0 package as complete note baseline",
            "no-boundary complete baseline conclusion",
            "strategy validity proven",
        ],
    }
    write_json(OUT_DIR / "v1_final_conclusion_summary.json", summary_json)
 
    (OUT_DIR / "README.md").write_text(
        f"""# 无忌 V1 最终结论引用包
 
本包是 V1 执行复审通过后的引用层整理,不重跑候选池、买卖裁决、人工裁决或账本。
 
先看:[v1_final_human_review_index.md](v1_final_human_review_index.md)
 
来源审计 ID:`{SOURCE_AUDIT_ID}`
 
设计审核 ID:`{DESIGN_AUDIT_ID}`
 
当前状态:待执行审核。执行审核通过前,不得把 V1 读数写入正式最终案例总结。
""",
        encoding="utf-8",
    )
 
    generated_text = "\n".join(
        [
            human_review,
            summary_md,
            json.dumps(summary_json, ensure_ascii=False),
        ]
    )
    forbidden_hits = forbidden_claims(generated_text)
 
    checks: list[dict[str, object]] = []
 
    def check(name: str, passed: bool, detail: str) -> None:
        checks.append({"item": name, "status": "PASS" if passed else "FAIL", "detail": detail})
 
    check(
        "SOURCE_EXECUTION_REVIEW_PASSED",
        bool(summary.get("v1_execution_review_passed")) and summary.get("execution_rereview_passed_audit_id") == SOURCE_AUDIT_ID,
        f"audit={summary.get('execution_rereview_passed_audit_id')}",
    )
    check("SOURCE_ARTIFACTS_HASHED", all(Path(row["path"]).exists() for row in src_manifest), f"sources={len(src_manifest)}")
    check(
        "READOUTS_MATCH_SOURCE",
        len(primary_cases) == int(summary["scope"]["v1_primary_strict_closed_cases"])
        and len(positive_cases) == int(summary["scope"]["v1_positive_primary_cases"])
        and round(float(summary["scope"]["v1_primary_success_readout"]), 10) == success_rate
        and round(float(summary["scope"]["v1_primary_account_contribution_readout"]), 8) == account_contribution,
        f"primary={len(primary_cases)}, positive={len(positive_cases)}, success={success_rate}, contribution={account_contribution}",
    )
    check("BOUNDARY_TABLE_PRESERVED", len(v1_boundary) == len(boundary_rows), f"boundary_rows={len(v1_boundary)}")
    check(
        "MARKET_RISK_BOUNDARY_PRESENT",
        any(r.get("boundary_category") == "MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD" for r in boundary_rows),
        "MARKET_RISK_MINUTE_BREADTH_DATA_GAP_HELD",
    )
    check(
        "SCOPE_SEPARATED",
        len(primary_cases) + len(boundary_cases) == len(case_rows) and len(closed_lots) + len(boundary_lots) == len(lot_rows),
        f"cases={len(case_rows)}, primary={len(primary_cases)}, boundary={len(boundary_cases)}, lots={len(lot_rows)}",
    )
    check(
        "ROLLING_LOW_BUY_READOUT_MATCHES_ORDER_LEDGER",
        len(rolling_buy_orders) == int(summary["scope"].get("rolling_buy_lots", len(rolling_buy_orders))),
        f"readout={len(rolling_buy_orders)}, source_scope={summary['scope'].get('rolling_buy_lots')}",
    )
    link_targets = [
        SOURCE_DIR / "case_image_board.md",
        SOURCE_DIR / "manual_decision_external_draft.md",
        SOURCE_DIR / "strict_order_ledger.csv",
        SOURCE_DIR / "strict_position_lot_ledger.csv",
    ]
    check("HUMAN_REVIEW_ENTRY_LINKS_REACHABLE", all(p.exists() for p in link_targets), f"links={len(link_targets)}")
    check("NO_OVERREAD_ASSERTIONS", not forbidden_hits, "forbidden_hits=" + "|".join(forbidden_hits))
 
    write_csv(OUT_DIR / "self_check_items.csv", checks, ["item", "status", "detail"])
    fail_count = sum(1 for r in checks if r["status"] != "PASS")
    self_check = {
        "schema_version": "1.0",
        "run_id": RUN_ID,
        "generated_at": now_iso(),
        "status": "PASS_FOR_V1_FINAL_CONCLUSION_EXECUTION_REVIEW_READY" if fail_count == 0 else "FAIL",
        "pass_count": len(checks) - fail_count,
        "fail_count": fail_count,
        "items_path": "self_check_items.csv",
    }
    write_json(OUT_DIR / "self_check.json", self_check)
    (OUT_DIR / "self_check.md").write_text(
        f"""# 自检摘要
 
- status:`{self_check['status']}`
- PASS:{self_check['pass_count']}
- FAIL:{self_check['fail_count']}
- 检查项:`self_check_items.csv`
""",
        encoding="utf-8",
    )
 
    # Build final package manifest last.
    package_files = []
    for p in OUT_DIR.rglob("*"):
        if not p.is_file():
            continue
        if p.name in {"manifest.csv", "manifest.json"}:
            continue
        package_files.append(file_row(p, OUT_DIR))
    package_files.sort(key=lambda r: str(r["path"]))
    write_csv(OUT_DIR / "manifest.csv", package_files, ["path", "size", "sha256"])
    write_json(
        OUT_DIR / "manifest.json",
        {
            "schema_version": "1.0",
            "run_id": RUN_ID,
            "generated_at": now_iso(),
            "files": package_files,
        },
    )
 
    print(
        json.dumps(
            {
                "run_id": RUN_ID,
                "status": self_check["status"],
                "primary_cases": len(primary_cases),
                "positive_cases": len(positive_cases),
                "success_rate": success_rate,
                "manifest_files": len(package_files),
            },
            ensure_ascii=False,
        )
    )
 
 
if __name__ == "__main__":
    main()