govdoc-md-cleaner v0.1.0: 政务文档 Markdown 清洗工具（规则引擎 + CLI + 测试）

- 8 条 YAML 声明规则：页码/页眉页脚/目录点线/图片/HTML表格/散落标签/行尾空白/空行
- 防误伤设计：protect 正则 + 内容形态豁免 + OCR burst 检测
- md-clean single/batch CLI，JSON 清洗报告
- 18 个单元测试

Co-Authored-By: Claude <noreply@anthropic.com>

cleaner/cleaner.py

@@ -0,0 +1,56 @@
+"""清洗引擎：按规则顺序应用，输出清洗后文本 + 统计报告。"""
+
+from __future__ import annotations
+
+import difflib
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Dict, List, Optional
+
+from cleaner.rules import REGISTRY, Rule, load_rules
+
+
+@dataclass
+class CleanResult:
+    """一次清洗的结果：产物 + 可审计的统计。"""
+
+    text: str
+    stats: Dict[str, int] = field(default_factory=dict)
+    rules_applied: List[str] = field(default_factory=list)
+
+    @property
+    def total_hits(self) -> int:
+        return sum(v for k, v in self.stats.items() if k != "collapsed_blanks")
+
+
+class MarkdownCleaner:
+    def __init__(self, rules: Optional[List[Rule]] = None, rules_path: Optional[Path] = None):
+        self.rules = rules if rules is not None else load_rules(rules_path)
+
+    def clean_text(self, text: str) -> CleanResult:
+        stats: Dict[str, int] = {}
+        applied: List[str] = []
+        for rule in self.rules:
+            if not rule.enabled:
+                continue
+            func = REGISTRY[rule.name]
+            text = func(text, rule.params, stats)
+            applied.append(rule.name)
+        return CleanResult(text=text, stats=stats, rules_applied=applied)
+
+    def clean_file(self, src: Path, dst: Optional[Path] = None) -> CleanResult:
+        raw = Path(src).read_text(encoding="utf-8")
+        result = self.clean_text(raw)
+        if dst is not None:
+            Path(dst).parent.mkdir(parents=True, exist_ok=True)
+            Path(dst).write_text(result.text, encoding="utf-8")
+        return result
+
+    @staticmethod
+    def diff(before: str, after: str, context: int = 1) -> str:
+        return "\n".join(
+            difflib.unified_diff(
+                before.splitlines(), after.splitlines(),
+                fromfile="before", tofile="after", lineterm="", n=context,
+            )
+        )