from __future__ import annotations
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import csv
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import hashlib
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import json
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from datetime import datetime, timedelta, timezone
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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-V1-BUY-POINT-SECOND-REVIEW-20260615-001"
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SOURCE_RUN_ID = "RUN-ANA-WUJI-V1-STRICT-NOTE-FULL-RERUN-20260614-001"
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TZ = timezone(timedelta(hours=8))
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ROOT = Path(__file__).resolve().parents[1]
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DETAIL_PATH = ROOT / "buy_point_second_review_detail.csv"
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P1_LEDGER_PATH = ROOT / "p1_step_review_packets" / "p1_step_review_resolution_ledger.csv"
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P1_SUMMARY_PATH = ROOT / "p1_step_review_packets" / "p1_step_review_resolution_summary.md"
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def now_iso() -> str:
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return datetime.now(TZ).isoformat(timespec="seconds")
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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 write_csv(df: pd.DataFrame, path: Path) -> None:
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df.to_csv(path, index=False, encoding="utf-8-sig")
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def write_text(path: Path, text: str) -> None:
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path.write_text(text, encoding="utf-8-sig")
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def safe_text(value: object) -> str:
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if value is None:
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return ""
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text = str(value)
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if text.lower() == "nan":
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return ""
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return text
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def p1_lookup() -> dict[str, dict[str, str]]:
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if not P1_LEDGER_PATH.exists():
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return {}
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p1 = pd.read_csv(P1_LEDGER_PATH, dtype=str, encoding="utf-8-sig").fillna("")
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return {row["candidate_id"]: row.to_dict() for _, row in p1.iterrows()}
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def build_rollup() -> tuple[pd.DataFrame, pd.DataFrame]:
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detail = pd.read_csv(DETAIL_PATH, dtype=str, encoding="utf-8-sig").fillna("")
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p1_by_candidate = p1_lookup()
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rows: list[dict[str, str]] = []
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for _, row in detail.iterrows():
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candidate_id = row["candidate_id"]
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source_action = row["human_decision_action"]
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second_status = row["second_review_status"]
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priority = row.get("human_recheck_priority", "")
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final_action = source_action
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resolution_bucket = "SOURCE_MANUAL_CARRIED_NO_DATA_RECHECK"
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resolution_source = "SOURCE_MANUAL_DECISION_NO_LOCAL_DATA_RECHECK"
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resolution_status = "NOT_INDEPENDENTLY_CONFIRMED"
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resolution_reason = row.get("second_review_reason_cn", "")
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formal_repair_action = "NO_REPAIR_DECISION_RECORDED"
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direct_resolution_flag = "0"
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codex_direct_resolution_flag = "0"
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if candidate_id in p1_by_candidate:
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p1 = p1_by_candidate[candidate_id]
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final_action = p1["final_action"]
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resolution_bucket = "USER_P1_FINAL"
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resolution_source = "USER_MANUAL_P1_CONFIRMATION"
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resolution_status = "FINAL_CONFIRMED"
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resolution_reason = p1["resolution_reason_cn"]
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direct_resolution_flag = "1"
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if source_action == "BUY" and final_action == "REVIEW_HELD":
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formal_repair_action = "REVOKE_BUY_ORDER_LOT_AND_RECALC"
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else:
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formal_repair_action = "KEEP_SOURCE_DECISION_NO_REPAIR"
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elif second_status == "AGREE":
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resolution_bucket = "CODEX_DATA_DIRECT_AGREE"
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resolution_source = "CODEX_DATA_SECOND_REVIEW_AGREE"
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resolution_status = "DATA_DIRECT_CONFIRMED"
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resolution_reason = row.get("second_review_reason_cn", "")
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formal_repair_action = "KEEP_SOURCE_DECISION_NO_REPAIR"
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direct_resolution_flag = "1"
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codex_direct_resolution_flag = "1"
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elif priority.startswith("P2_"):
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final_action = "PENDING_HUMAN_RECHECK"
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resolution_bucket = "P2_PENDING_HUMAN_RECHECK"
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resolution_source = "SECOND_REVIEW_DISPUTE"
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resolution_status = "PENDING_RECHECK"
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formal_repair_action = "WAIT_FOR_HUMAN_RECHECK"
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elif priority.startswith("P3_"):
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final_action = "PENDING_LOW_PRIORITY_SAMPLE_RECHECK"
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resolution_bucket = "P3_PENDING_SAMPLE_RECHECK"
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resolution_source = "SECOND_REVIEW_WEAK_DISPUTE"
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resolution_status = "PENDING_LOW_PRIORITY_RECHECK"
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formal_repair_action = "WAIT_FOR_SAMPLE_RECHECK"
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rows.append(
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{
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"case_id": row["case_id"],
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"candidate_id": candidate_id,
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"symbol": row["symbol"],
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"entry_trade_date": row["entry_trade_date"],
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"source_action": source_action,
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"final_action": final_action,
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"resolution_bucket": resolution_bucket,
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"resolution_source": resolution_source,
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"resolution_status": resolution_status,
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"direct_resolution_flag": direct_resolution_flag,
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"codex_direct_resolution_flag": codex_direct_resolution_flag,
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"formal_repair_action": formal_repair_action,
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"second_review_status": second_status,
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"second_review_issue_code": row["second_review_issue_code"],
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"human_recheck_priority": priority,
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"local_minute_status": row["local_minute_status"],
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"minute_rows": row["minute_rows"],
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"close_ret_pct": row["close_ret_pct"],
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"above_open_ratio": row["above_open_ratio"],
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"early_max_ret_pct": row["early_max_ret_pct"],
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"early_max_ret_time": row["early_max_ret_time"],
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"tail_max_ret_pct": row["tail_max_ret_pct"],
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"tail_max_ret_time": row["tail_max_ret_time"],
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"source_human_reason_cn": row["human_decision_reason_cn"],
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"resolution_reason_cn": resolution_reason,
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"source_review_chart_abs_path": row["source_review_chart_abs_path"],
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}
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)
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rollup = pd.DataFrame(rows)
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p1 = pd.DataFrame(p1_by_candidate.values())
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return rollup, p1
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def table_counts(series: pd.Series) -> str:
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counts = series.value_counts(dropna=False).sort_index()
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lines = ["| item | count |", "|---|---:|"]
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for name, count in counts.items():
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lines.append(f"| `{safe_text(name)}` | {int(count)} |")
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return "\n".join(lines)
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def render_summary(rollup: pd.DataFrame, p1: pd.DataFrame, generated_at: str) -> str:
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confirmed = rollup[rollup["direct_resolution_flag"].eq("1")]
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codex = rollup[rollup["codex_direct_resolution_flag"].eq("1")]
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repair = rollup[rollup["formal_repair_action"].eq("REVOKE_BUY_ORDER_LOT_AND_RECALC")]
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source_buy_confirmed = confirmed[confirmed["final_action"].eq("BUY")]
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source_held_confirmed = confirmed[confirmed["final_action"].eq("REVIEW_HELD")]
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lines = [
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"# 买点裁决总览（含 Codex 数据直裁）",
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"",
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f"- run_id: {RUN_ID}",
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f"- source_run_id: {SOURCE_RUN_ID}",
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f"- updated_at: {generated_at}",
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f"- source_rows: {len(rollup)}",
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"",
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"## 当前结论",
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"",
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f"- 已形成明确裁决：{len(confirmed)} 条",
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f"- 其中用户 P1 最终裁决：{len(p1)} 条",
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f"- 其中 Codex 数据二审直接同意源裁决：{len(codex)} 条",
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f"- 已确认 BUY：{len(source_buy_confirmed)} 条",
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f"- 已确认 REVIEW_HELD：{len(source_held_confirmed)} 条",
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f"- 需要正式返修撤销 BUY/order/lot 并重算：{len(repair)} 条",
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f"- 仍需 P2/P3 人工复核或抽查：{len(rollup[rollup['resolution_status'].str.contains('PENDING', na=False)])} 条",
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f"- 无本地分钟数据覆盖、仅沿用源人工裁决且未二审确认：{len(rollup[rollup['resolution_bucket'].eq('SOURCE_MANUAL_CARRIED_NO_DATA_RECHECK')])} 条",
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"",
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"## 裁决来源分布",
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"",
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table_counts(rollup["resolution_bucket"]),
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"",
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"## 最终动作分布",
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"",
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table_counts(rollup["final_action"]),
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"",
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"## 输出文件",
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"",
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"- `buy_point_resolution_rollup.csv`: 1141 条总台账，合并用户 P1 裁决、Codex 数据直裁、待复核和无数据覆盖状态。",
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"- `buy_point_codex_direct_resolution.csv`: 388 条 Codex 数据二审直接同意源裁决的明细。",
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"- `buy_point_formal_repair_required.csv`: 12 条需要正式返修撤销 BUY/order/lot 并重算的明细。",
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"",
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"## 口径边界",
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"",
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"- `CODEX_DATA_DIRECT_AGREE` 表示本机分钟数据复算与源人工裁决一致，因此列入“数据二审直接同意源裁决”；它不是新的买卖规则，也不替代后续正式结果包返修。",
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"- `SOURCE_MANUAL_CARRIED_NO_DATA_RECHECK` 表示本机分钟数据没有覆盖，当前没有形成二审证据，不把它算作 Codex 直接裁决。",
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"- 正式结果包返修时，不能只改人工裁决表；凡撤销 BUY 的条目，都需要同步重算 order、lot、case 汇总和收益口径。",
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]
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return "\n".join(lines) + "\n"
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def render_p1_summary(p1: pd.DataFrame, generated_at: str) -> str:
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if p1.empty:
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return "# P1 买点逐条人工复核裁决汇总\n\n- 当前没有 P1 裁决记录。\n"
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keep = p1[p1["final_action"].eq("BUY")]
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revoke = p1[p1["final_action"].eq("REVIEW_HELD")]
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lines = [
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"# P1 买点逐条人工复核裁决汇总",
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"",
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f"- updated_at: {generated_at}",
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f"- resolved_count: {len(p1)}",
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f"- 维持 BUY: {len(keep)}",
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f"- 改为 REVIEW_HELD: {len(revoke)}",
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"",
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"| # | case | candidate | symbol | date | original | final | reason |",
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"|---:|---|---|---|---|---|---|---|",
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]
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ordered = p1.copy()
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ordered["packet_order_num"] = pd.to_numeric(ordered["packet_order"], errors="coerce")
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ordered = ordered.sort_values("packet_order_num")
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for _, row in ordered.iterrows():
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lines.append(
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"| {packet_order} | {case_id} | {candidate_id} | {symbol} | {date} | {original} | {final} | {reason} |".format(
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packet_order=row["packet_order"],
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case_id=row["case_id"],
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candidate_id=row["candidate_id"],
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symbol=row["symbol"],
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date=row["entry_trade_date"],
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original=row["original_action"],
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final=row["final_action"],
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reason=row["resolution_reason_cn"],
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)
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)
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lines.extend(
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[
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"",
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"## 待处理影响",
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"",
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"- 维持 BUY 的条目保留最新结果包中的 BUY/order/lot，不进入买点撤销重算清单。",
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"- 改为 REVIEW_HELD 的条目需要在正式返修时撤销对应 BUY/order/lot；如果已经有后续 SELL，也要一并重算 lot、case 汇总和收益口径。",
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"- `WUJI-STRICT-20250317` 同时有 `920570.BJ` 和 `603206.SH` 两条买点被判定不适合作为买点，正式返修时应作为同一个 case 合并处理。",
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]
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)
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return "\n".join(lines) + "\n"
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def update_manifest(generated_at: str, extra_paths: list[Path]) -> None:
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manifest_paths = [
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ROOT / "buy_point_second_review_action_status_counts.csv",
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ROOT / "buy_point_second_review_detail.csv",
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ROOT / "buy_point_second_review_human_recheck_report.md",
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ROOT / "buy_point_second_review_human_top80.csv",
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ROOT / "buy_point_second_review_recheck_list.csv",
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ROOT / "buy_point_second_review_strong_recheck.csv",
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ROOT / "buy_point_second_review_summary.json",
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ROOT / "buy_point_second_review_summary.md",
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ROOT / "tools" / "review_buy_point_decisions.py",
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ROOT / "tools" / "build_p1_step_review_packets.py",
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ROOT / "tools" / "build_buy_point_resolution_rollup.py",
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*extra_paths,
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]
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files = []
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for path in manifest_paths:
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if not path.exists():
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continue
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rel = path.relative_to(ROOT).as_posix()
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files.append({"path": rel, "size": path.stat().st_size, "sha256": sha256_file(path)})
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with (ROOT / "manifest.csv").open("w", encoding="utf-8-sig", newline="") as f:
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writer = csv.DictWriter(f, fieldnames=["path", "size", "sha256"])
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writer.writeheader()
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writer.writerows(files)
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manifest = {
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"run_id": RUN_ID,
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"updated_at": generated_at,
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"file_count": len(files),
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"files": files,
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}
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(ROOT / "manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8")
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def main() -> None:
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generated_at = now_iso()
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rollup, p1 = build_rollup()
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rollup_path = ROOT / "buy_point_resolution_rollup.csv"
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codex_path = ROOT / "buy_point_codex_direct_resolution.csv"
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repair_path = ROOT / "buy_point_formal_repair_required.csv"
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summary_path = ROOT / "buy_point_resolution_summary.md"
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write_csv(rollup, rollup_path)
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write_csv(rollup[rollup["codex_direct_resolution_flag"].eq("1")], codex_path)
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write_csv(rollup[rollup["formal_repair_action"].eq("REVOKE_BUY_ORDER_LOT_AND_RECALC")], repair_path)
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write_text(summary_path, render_summary(rollup, p1, generated_at))
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write_text(P1_SUMMARY_PATH, render_p1_summary(p1, generated_at))
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update_manifest(generated_at, [rollup_path, codex_path, repair_path, summary_path])
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if __name__ == "__main__":
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main()
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