135 lines
4.9 KiB
Python
135 lines
4.9 KiB
Python
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from __future__ import annotations
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import io
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import json
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from typing import Any, Dict, Iterable, List
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def normalize_result_dicts(results: Iterable[Any]) -> List[Dict[str, Any]]:
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normalized: List[Dict[str, Any]] = []
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for item in results:
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if hasattr(item, "to_dict"):
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normalized.append(item.to_dict())
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elif isinstance(item, dict):
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normalized.append(item)
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else:
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normalized.append(
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{
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"requirement_uid": getattr(item, "requirement_uid", ""),
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"verdict": getattr(item, "verdict", ""),
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"coverage_score": getattr(item, "coverage_score", 0.0),
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"confidence": getattr(item, "confidence", 0.0),
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"matched_functions": getattr(item, "matched_functions", []),
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"covered_points": getattr(item, "covered_points", []),
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"missing_points": getattr(item, "missing_points", []),
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"conflict_points": getattr(item, "conflict_points", []),
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"call_chain_evidence": getattr(item, "call_chain_evidence", []),
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"suggestion": getattr(item, "suggestion", ""),
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"raw_judgment": getattr(item, "raw_judgment", {}),
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}
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)
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return normalized
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def export_json(results: Iterable[Any]) -> bytes:
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return json.dumps(
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{"results": normalize_result_dicts(results)},
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ensure_ascii=False,
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indent=2,
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).encode("utf-8")
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def export_markdown(results: Iterable[Any]) -> str:
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rows = normalize_result_dicts(results)
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lines = [
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"# 需求代码一致性比对报告",
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"",
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"| 需求 ID | 判定 | 覆盖分 | 置信度 | 匹配函数 | 缺失点 | 建议 |",
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"| --- | --- | ---: | ---: | ---: | ---: | --- |",
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]
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for item in rows:
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lines.append(
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"| {uid} | {verdict} | {score:.2f} | {confidence:.2f} | {functions} | {missing} | {suggestion} |".format(
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uid=item.get("requirement_uid", ""),
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verdict=item.get("verdict", ""),
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score=float(item.get("coverage_score") or 0),
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confidence=float(item.get("confidence") or 0),
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functions=len(item.get("matched_functions") or []),
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missing=len(item.get("missing_points") or []),
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suggestion=str(item.get("suggestion") or "").replace("|", "/"),
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)
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)
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for item in rows:
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lines.extend(
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[
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"",
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f"## {item.get('requirement_uid', '')} {item.get('requirement_title', '')}",
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"",
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f"- 判定: `{item.get('verdict', '')}`",
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f"- 覆盖分: {float(item.get('coverage_score') or 0):.2f}",
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f"- 置信度: {float(item.get('confidence') or 0):.2f}",
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f"- 建议: {item.get('suggestion') or '-'}",
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"",
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"### 匹配函数",
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]
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)
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for function in item.get("matched_functions") or []:
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lines.append(
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f"- `{function.get('name')}` {function.get('file')}:{function.get('start_line')} "
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f"(similarity={float(function.get('similarity') or 0):.2f})"
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)
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lines.extend(["", "### 缺失点"])
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for point in item.get("missing_points") or ["-"]:
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lines.append(f"- {point}")
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if item.get("conflict_points"):
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lines.extend(["", "### 冲突点"])
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for point in item.get("conflict_points") or []:
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lines.append(f"- {point}")
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return "\n".join(lines)
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def export_excel(results: Iterable[Any]) -> bytes:
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try:
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from openpyxl import Workbook
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except ImportError as exc:
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raise RuntimeError("openpyxl is required to export Excel reports.") from exc
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rows = normalize_result_dicts(results)
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workbook = Workbook()
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sheet = workbook.active
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sheet.title = "Consistency"
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headers = [
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"需求ID",
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"需求标题",
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"需求类型",
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"判定",
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"覆盖分",
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"置信度",
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"匹配函数数量",
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"主要文件",
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"缺失点数量",
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"建议",
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]
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sheet.append(headers)
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for item in rows:
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functions = item.get("matched_functions") or []
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sheet.append(
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[
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item.get("requirement_uid", ""),
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item.get("requirement_title", ""),
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item.get("requirement_type", ""),
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item.get("verdict", ""),
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item.get("coverage_score", 0),
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item.get("confidence", 0),
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len(functions),
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functions[0].get("file", "") if functions else "",
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len(item.get("missing_points") or []),
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item.get("suggestion", ""),
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]
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)
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output = io.BytesIO()
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workbook.save(output)
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return output.getvalue()
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