from __future__ import annotations
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import hashlib
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import json
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import shutil
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from datetime import datetime
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from pathlib import Path
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import pandas as pd
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RUN_ID = "RUN-ANA-WUJI-FULL-2023-2026-20260608-001"
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SOURCE_RUN_ID = "RUN-ANA-WUJI-BASELINE-PILOT-20260607-001"
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CASE_MATTER_ID = "ANA-WUJI-BASELINE-2023-2026"
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DESIGN_ID = "DESIGN-WUJI-EXPAND-30-20260608"
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DESIGN_AUDIT_ID = "AUDIT-ANA-WUJI-EXPAND-30-20260608-DESIGN-001"
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EXEC_AUDIT_ID = "AUDIT-ANA-WUJI-EXPAND-30-20260608-EXEC-001"
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EXEC_REREVIEW_AUDIT_ID = "AUDIT-ANA-WUJI-EXPAND-30-20260608-EXEC-REREVIEW-001"
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BOARD_STATUS_ISSUE_ID = "ANA-ISSUE-WUJI-EXPAND-30-BOARD-STATUS-20260608-001"
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ROOT = Path(__file__).resolve().parents[1]
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PROJECT_ROOT = ROOT.parents[2]
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SOURCE_ROOT = PROJECT_ROOT / "ana-data" / "result" / SOURCE_RUN_ID
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def sha256_file(path: Path) -> str:
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h = hashlib.sha256()
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with path.open("rb") as f:
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for chunk in iter(lambda: f.read(1024 * 1024), b""):
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h.update(chunk)
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return h.hexdigest()
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def read_json(name: str) -> dict:
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return json.loads((ROOT / name).read_text(encoding="utf-8"))
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def read_csv(name: str) -> pd.DataFrame:
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return pd.read_csv(ROOT / name, encoding="utf-8-sig")
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def manifest_files() -> list[dict]:
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rows: list[dict] = []
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for path in sorted(ROOT.rglob("*")):
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if not path.is_file():
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continue
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if "__pycache__" in path.parts:
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continue
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rel = path.relative_to(ROOT).as_posix()
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if rel == "manifest.json":
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continue
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rows.append({"path": rel, "exists": True, "size": path.stat().st_size, "sha256": sha256_file(path)})
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return rows
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def maybe_copy_source_db_check() -> None:
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target = ROOT / "source_db_direct_check.json"
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source = SOURCE_ROOT / "source_db_direct_check.json"
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if not target.exists() and source.exists():
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shutil.copy2(source, target)
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def existing_outputs(names: list[str]) -> list[str]:
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return [name for name in names if (ROOT / name).exists()]
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def main() -> None:
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generated_at = datetime.now().astimezone().isoformat(timespec="seconds")
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maybe_copy_source_db_check()
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expand_config = read_json("expand_run_config.json")
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candidate_summary = read_json("candidate_generation_summary.json")
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candidate_image_summary = read_json("candidate_image_generation_summary.json")
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entry_review_summary = read_json("entry_review_generation_summary.json")
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entry_ai_summary = read_json("entry_ai_review_summary.json")
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exit_review_summary = read_json("exit_review_generation_summary.json")
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exit_ai_summary = read_json("exit_ai_review_summary.json")
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self_check = read_json("self_check.json")
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source_db = read_json("source_db_direct_check.json") if (ROOT / "source_db_direct_check.json").exists() else {}
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case_index = read_csv("case_index.csv")
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selected = read_csv("selected_candidate_ledger.csv")
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image_manifest = read_csv("image_manifest.csv")
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decisions = read_csv("decision_log.csv")
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orders = read_csv("order_ledger.csv")
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lots = read_csv("position_lot_ledger.csv")
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case_summary = read_csv("case_summary.csv")
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order_counts = {k: int(v) for k, v in orders.action.value_counts().to_dict().items()}
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lot_status_counts = {k: int(v) for k, v in lots.lot_status.value_counts().to_dict().items()}
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image_role_counts = {k: int(v) for k, v in image_manifest.chart_role.value_counts().to_dict().items()}
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decision_counts = decisions.groupby(["decision_stage", "action_status"]).size().astype(int).to_dict()
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decision_counts = {f"{k[0]}::{k[1]}": int(v) for k, v in decision_counts.items()}
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anchor_count = int((case_index.expand_case_role == "ANCHOR_REUSED_FROM_AUDITED_7_CASE_PILOT").sum())
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new_count = int((case_index.expand_case_role == "NEW_EXPAND_30_CASE").sum())
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no_trade_case_count = int((case_index.market_gate_status == "NO_TRADE_MARKET_GATE_CLOSED").sum())
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buy_case_count = int(case_summary.case_id.nunique())
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unresolved_lots = lots[lots.lot_status != "CLOSED_BY_AI_SELL"]
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completed_outputs = existing_outputs(
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[
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"expand_run_config.md",
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"expand_run_config.json",
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"run_config.md",
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"run_config.json",
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"candidate_ledger.csv",
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"candidate_date_summary.csv",
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"expand_case_index.csv",
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"case_index.csv",
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"expand_sample_selection_log.csv",
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"expand_candidate_selection_ledger.csv",
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"selected_candidate_ledger.csv",
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"image_manifest.csv",
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"case_image_board.md",
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"case_story_board.md",
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"entry_review_generation_summary.json",
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"entry_ai_review_summary.json",
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"sell_signal_candidates.csv",
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"sell_decision_log.csv",
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"exit_resolution_log.csv",
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"order_ledger.csv",
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"position_lot_ledger.csv",
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"daily_account_ledger.csv",
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"case_summary.csv",
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"chart_evidence_audit.csv",
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"link_evidence_audit.csv",
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"self_check.json",
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"self_check.md",
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]
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)
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held_items = [
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{
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"item": "unresolved_lots",
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"count": int(len(unresolved_lots)),
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"status_counts": {k: int(v) for k, v in unresolved_lots.lot_status.value_counts().to_dict().items()},
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"reason": "Non-real SELL lots are explicitly retained as WINDOW_END_VALUATION_ONLY or EXIT_DATA_GAP_HELD and are not forced into return conclusions.",
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},
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{
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"item": "return_statistics",
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"count": 1,
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"reason": "Execution audit is pending. This expansion package is not RETURN_STAT_READY and is not a full 2023-2026 baseline result.",
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},
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]
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source_validation = {
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"status": "SOURCE_DB_CHECK_INHERITED_FROM_AUDITED_PILOT" if source_db else "SOURCE_DB_CHECK_NOT_ATTACHED",
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"evidence": "source_db_direct_check.json" if source_db else "",
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}
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if source_db.get("execution_boundaries"):
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boundaries = source_db["execution_boundaries"]
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source_validation.update(
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{
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"daily_price_range": boundaries.get("daily_price_usable_range", {}),
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"minute_price_range": boundaries.get("minute_price_usable_range_for_intraday_replay", {}),
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"market_breadth_range": boundaries.get("market_breadth_daily_usable_range", {}),
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}
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)
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summary = {
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"schema_version": "1.0",
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"run_id": RUN_ID,
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"case_matter_id": CASE_MATTER_ID,
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"design_id": DESIGN_ID,
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"design_audit_id": DESIGN_AUDIT_ID,
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"source_run_id": SOURCE_RUN_ID,
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"source_audit_ids": expand_config.get("source_audit_ids", []),
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"updated_at": generated_at,
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"role_instance_id": "case_analysis.analyst",
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"stage": "EXPAND_30_EXECUTION_SELF_CHECK_DONE",
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"status": "expand_30_execution_rereview_passed",
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"review_repair_context": {
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"previous_execution_audit_id": EXEC_AUDIT_ID,
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"execution_rereview_audit_id": EXEC_REREVIEW_AUDIT_ID,
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"issue_id": BOARD_STATUS_ISSUE_ID,
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"repair_scope": "image and story board status text, board link audit, self-check, manifest",
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"repair_boundary": "Candidate pool, buy/sell decisions, ledgers, market gate, return口径 and boundary lots were not changed in this repair.",
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"rereview_status": "passed",
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},
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"completed_outputs": completed_outputs,
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"held_items": held_items,
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"conclusion_boundary": (
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"30-case controlled expansion execution package only. No complete 2023-2026 baseline return, "
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"success rate, win rate, drawdown, or strategy effectiveness conclusion."
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),
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"source_db_validation": source_validation,
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"candidate_pool": {
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"source_candidate_rows": int(candidate_summary["candidate_counts"]["candidate_rows"]),
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"source_candidate_entry_dates": int(candidate_summary["candidate_counts"]["candidate_entry_dates"]),
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"selected_case_days": int(len(case_index)),
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"selected_candidate_rows": int(len(selected)),
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"anchor_case_days": anchor_count,
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"new_case_days": new_count,
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"no_trade_case_days": no_trade_case_count,
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"buy_case_days": buy_case_count,
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"market_gate_open_dates_in_source": int(candidate_summary["candidate_counts"]["market_gate_open_entry_dates"]),
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"market_gate_closed_dates_in_source": int(candidate_summary["candidate_counts"]["market_gate_closed_entry_dates"]),
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},
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"image_package": {
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"image_count": int(len(image_manifest)),
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"role_counts": image_role_counts,
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"candidate_daily_images": int(candidate_image_summary["image_count"]),
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"entry_review_images": int(entry_review_summary["entry_review_images"]),
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"buy_decision_images": int(entry_ai_summary["buy_decision_image_count"]),
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"exit_signal_images": int(exit_review_summary["exit_signal_images"]),
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"sell_decision_images": int(image_role_counts.get("exit_1m_sell_decision_view", 0)),
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},
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"trade_ledger": {
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"order_counts": order_counts,
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"lot_status_counts": lot_status_counts,
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"case_summary_rows": int(len(case_summary)),
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"closed_lot_account_return_sum_for_recalc_only": float(exit_ai_summary["closed_lot_account_return_sum"]),
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},
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"decision_counts": decision_counts,
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"self_check": {
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"status": self_check["overall_status"],
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"check_count": int(self_check["check_count"]),
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"fail_count": int(self_check["fail_count"]),
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"evidence": "self_check.json",
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},
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"strict_baseline_return_ready_flag": False,
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"execution_review_status": "EXEC_REREVIEW_PASSED",
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}
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(ROOT / "summary.json").write_text(json.dumps(summary, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
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summary_md = [
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f"# {RUN_ID} summary",
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"",
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f"- 案例事项：`{CASE_MATTER_ID}`",
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f"- 设计：`{DESIGN_ID}`",
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f"- 设计审核：`{DESIGN_AUDIT_ID}`",
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"- 阶段：`EXPAND_30_EXECUTION_SELF_CHECK_DONE`",
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"- 状态：`expand_30_execution_rereview_passed`",
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f"- 执行审核反馈：`{EXEC_AUDIT_ID}` HELD；关联问题 `{BOARD_STATUS_ISSUE_ID}` 已返修并由 `{EXEC_REREVIEW_AUDIT_ID}` 复审通过",
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"",
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"## 当前结果",
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"",
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f"- 案例日：30（7 个已审核锚点 + 23 个新增分层案例日）",
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f"- 选中候选：{len(selected)} 行",
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f"- 市场闸门关闭不交易案例日：{no_trade_case_count}",
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f"- 有 BUY 的案例日：{buy_case_count}",
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f"- BUY：{order_counts.get('BUY', 0)}，SELL：{order_counts.get('SELL', 0)}",
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f"- lot：{len(lots)}，已闭合：{lot_status_counts.get('CLOSED_BY_AI_SELL', 0)}，边界保留：{len(unresolved_lots)}",
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f"- 图片：{len(image_manifest)} 张，图片板链接和 hash 已自检",
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f"- 自检：{self_check['check_count']} 项，失败 {self_check['fail_count']} 项",
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"",
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"## 边界",
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"",
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"- 本包只用于 30 案例日受控扩样执行复审通过记录。",
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"- 本执行复审通过不等于完整 2023-2026 baseline 结论。",
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"- 当前不是完整 2023-2026 baseline 收益率、成功率、胜率、回撤或策略有效性结论。",
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"- `WINDOW_END_VALUATION_ONLY` 与 `EXIT_DATA_GAP_HELD` 保持边界状态，不强行转 SELL。",
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"",
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"## 送审入口",
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"",
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"- `summary.json` / `summary.md`",
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"- `case_image_board.md`",
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"- `expand_run_config.md/json`",
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"- `expand_sample_selection_log.csv`",
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"- `decision_log.csv`、`order_ledger.csv`、`position_lot_ledger.csv`、`daily_account_ledger.csv`、`case_summary.csv`",
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"- `self_check.json`、`self_check_items.csv`、`chart_evidence_audit.csv`、`link_evidence_audit.csv`",
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"- `manifest.json`",
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"",
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]
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(ROOT / "summary.md").write_text("\n".join(summary_md), encoding="utf-8")
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files = manifest_files()
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manifest = {
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"schema_version": "1.0",
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"run_id": RUN_ID,
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"manifest_stage": "EXPAND_30_EXECUTION_SELF_CHECK_DONE",
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"generated_at": generated_at,
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"hash_status": "size_and_sha256_recorded_for_current_artifacts_manifest_self_excluded",
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"overall_status": self_check["overall_status"],
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"file_count": len(files),
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"files": files,
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"directories": sorted([p.relative_to(ROOT).as_posix() for p in ROOT.rglob("*") if p.is_dir() and "__pycache__" not in p.parts]),
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"notes": "30-case controlled expansion execution package manifest after board-status repair and execution re-review pass. manifest.json itself is excluded from hashing for stability. This is not a full baseline result.",
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}
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(ROOT / "manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
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if __name__ == "__main__":
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main()
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