规则库 3.8.1 + 排盘修复 + 评测体系
- 规则库 3.6→3.8.1（542→548 条）：剪枝上锁、R-杂-38 从格临界双轨、 R-事-10~13 冲刑方向判别、R-禁-23 自造必要条件之禁 - 排盘修复随 3.6.2 已发：港澳时区夏令时双向误拨、晚子时双重换日 - 新增 评测/ 目录（BaziQA 题答分离、判分工具、记分卡、with/without-skill 对照） 与 scripts/query_rules.py 条款检索；ZIPEC_EVAL 评测额度豁免 - manifest 重建并重新签名；VERSION 保持 3.6.2，不发版不打 tag
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#!/usr/bin/env python3
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"""试题原始包 → questions/（盲版）+ answers/（答案键）分离生成器。
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输入为含官方答案的赛事原始 JSON（contest8_*.json 结构：第 0 项元数据，
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其后为命主数组，每命主 questions 列表，每题含 answer 字段）。输出：
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- <out>/questions/<file>.json：与原版同构但剥离每题 answer 的盲版（求解端只准读这里）；
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- <out>/answers/<file>.json：答案键，仅 [元数据, {person_id, answers: [
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{question_index, answer, dimension}, ...]} ...]；维度标签可由 --scores
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指向的官方跑分目录（details 含 dimension 字段）合并，缺省标「未标注」。
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用法（在本仓库根目录之外同样可用，路径全部参数化）：
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python make_blind.py --src <原始包目录> [--out <赛事目录>]
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[--scores <官方跑分目录>]
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校验：
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1. 结构断言：盲版任何位置（递归）不存在 "answer" 键；
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2. 文本扫描：盲版文件原文不出现 `"answer"` 字样；
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3. 等价性：盲版 + 答案键可无损还原原文件（确认只删了 answer）；
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4. 题数：每届实际题数与元数据 total_questions 一致；
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5. 维度覆盖：打印未标注维度计数（有 --scores 时应为 0）。
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"""
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from __future__ import annotations
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import argparse
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import copy
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import json
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1] # 评测/
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DEFAULT_OUT = ROOT / "试题" / "BaziQA-全球算命师大赛"
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def strip_answers(node, path: str = "$"):
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"""递归剥离题目里的 answer 键；返回剥离数量。非题目位置本就不该有 answer，发现即报错。"""
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n = 0
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if isinstance(node, dict):
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if "options" in node and "question_id" in node:
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assert "answer" in node, f"{path}: 题目缺少 answer 字段"
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del node["answer"]
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n += 1
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else:
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assert "answer" not in node, f"{path}: 非题目位置出现 answer 键"
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for k, v in node.items():
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n += strip_answers(v, f"{path}.{k}")
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elif isinstance(node, list):
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for i, v in enumerate(node):
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n += strip_answers(v, f"{path}[{i}]")
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return n
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def has_answer_key(node) -> bool:
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if isinstance(node, dict):
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return "answer" in node or any(has_answer_key(v) for v in node.values())
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if isinstance(node, list):
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return any(has_answer_key(v) for v in node)
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return False
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def load_dimensions(scores_dir: Path | None) -> dict[tuple[str, str, int], str]:
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"""从官方跑分 details 复用维度标签，键 (dataset, person_id, question_index)。"""
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dim = {}
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if not scores_dir or not scores_dir.is_dir():
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return dim
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for f in sorted(scores_dir.glob("contest8_*.json")):
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try:
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s = json.loads(f.read_text(encoding="utf-8"))
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except Exception:
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continue
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for d in s.get("details", []):
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dim[(d["dataset"], d["person_id"], d["question_index"])] = \
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d.get("dimension", "未标注")
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return dim
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def main() -> int:
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ap = argparse.ArgumentParser(description="试题原始包 → questions/+answers/ 分离")
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ap.add_argument("--src", type=Path, required=True, help="含 answer 的原始 contest8_*.json 目录")
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ap.add_argument("--out", type=Path, default=DEFAULT_OUT, help="赛事目录（其下建 questions/ 与 answers/）")
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ap.add_argument("--scores", type=Path, default=None, help="官方跑分目录（取 dimension 维度标签，可省）")
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a = ap.parse_args()
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q_dir = a.out / "questions"
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k_dir = a.out / "answers"
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q_dir.mkdir(parents=True, exist_ok=True)
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k_dir.mkdir(parents=True, exist_ok=True)
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dims = load_dimensions(a.scores)
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total = 0
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for src in sorted(a.src.glob("contest8_*.json")):
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original = json.loads(src.read_text(encoding="utf-8"))
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contest = original[0]["contest_id"]
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blind = copy.deepcopy(original)
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n = strip_answers(blind)
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# 结构断言：盲版任何位置无 answer 键
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assert not has_answer_key(blind), f"{src.name}: 盲版仍含 answer 键"
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# 答案键：仅 person_id + 题序 + 答案字母 + 维度标签
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missing_dim = 0
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key = [{
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"contest_id": contest,
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"total_questions": original[0].get("total_questions"),
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"note": "答案键：person_id + 题序 + 标准答案字母 + 维度标签；求解端禁读",
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}]
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for p in original[1:]:
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answers = []
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for i, q in enumerate(p["questions"], start=1):
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d = dims.get((contest, p["person_id"], i))
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if d is None:
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d, missing_dim = "未标注", missing_dim + 1
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answers.append({"question_index": i, "answer": q["answer"],
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"dimension": d})
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key.append({"person_id": p["person_id"], "answers": answers})
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# 等价性：盲版 + 答案键 == 原版（确认除 answer 外未动任何字段）
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rebuilt = copy.deepcopy(blind)
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for p_o, p_r in zip(original[1:], rebuilt[1:]):
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for q_o, q_r in zip(p_o["questions"], p_r["questions"]):
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q_r["answer"] = q_o["answer"]
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assert rebuilt == original, f"{src.name}: 剥离 answer 后其余字段不一致"
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# 题数与元数据一致
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actual = sum(len(p["questions"]) for p in original[1:])
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assert original[0].get("total_questions") in (None, actual), \
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f"{src.name}: 元数据 total_questions={original[0].get('total_questions')} 与实际 {actual} 不符"
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q_text = json.dumps(blind, ensure_ascii=False, indent=1) + "\n"
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# 文本扫描：盲版原文不得出现 "answer" 字样
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assert '"answer"' not in q_text, f"{src.name}: 盲版文本含 answer 字样"
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(q_dir / src.name).write_text(q_text, encoding="utf-8")
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(k_dir / src.name).write_text(
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json.dumps(key, ensure_ascii=False, indent=1) + "\n", encoding="utf-8")
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total += n
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print(f"{src.name}: {len(original) - 1} 命主 {n} 题 -> "
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f"questions/（盲版）+ answers/（答案键，维度未标注 {missing_dim}）")
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print(f"OK: 共分离 {total} 题，questions/ 与 answers/ 已生成并校验通过")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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