Markdown TOC MCP Server

#!/usr/bin/env python3 """ 测试脚本：针对 Apache Spark 复杂文档进行语义分析测试 """ import sys import os import json # 添加 src 目录到 Python 路径 project_root = os.path.dirname(os.path.abspath(__file__)) sys.path.insert(0, os.path.join(project_root, '..', '..', 'src')) from markdown_editor.semantic_editor import SemanticEditor, create_editor_from_markdown from markdown_editor.sir_renderer import render_sir_to_markdown def test_apache_spark_document(): """测试 Apache Spark 复杂文档的语义分析""" # 读取 Apache Spark 文档内容 spark_doc_path = os.path.join('tests', 'fixtures', 'Apache Spark 设计与实现.md') try: with open(spark_doc_path, 'r', encoding='utf-8') as f: content = f.read() print(f"文档大小: {len(content)} 字符") print(f"文档行数: {len(content.split('\n'))} 行") # 创建语义编辑器实例 editor = create_editor_from_markdown(content) # 执行语义分析 print("\n=== 执行语义分析 ===") analysis_result = editor.check_consistency() print(f"初始问题数量: {len(analysis_result.get('issues', []))}") print(f"总体状态: {analysis_result.get('overall', {}).get('status', 'unknown')}") # 显示前10个问题（如果有） issues = analysis_result.get('issues', []) if issues: print(f"\n=== 前10个问题 ===") for i, issue in enumerate(issues[:10], 1): print(f"{i}. [{issue.get('type', 'unknown')}] {issue.get('message', 'No message')}") print(f" 位置: {issue.get('location', 'unknown')}") # 执行自动修复 print("\n=== 执行自动修复 ===") repair_result = editor.auto_repair() print(f"修复操作数量: {len(repair_result.get('operations', []))}") print(f"修复后问题数量: {len(repair_result.get('remaining_issues', []))}") # 检查修复后的文档状态 print("\n=== 检查修复后状态 ===") final_check = editor.check_consistency() print(f"最终问题数量: {len(final_check.get('issues', []))}") print(f"最终状态: {final_check.get('overall', {}).get('status', 'unknown')}") # 获取修复后的文档并转换为 Markdown repaired_sir_doc = editor.get_document() repaired_markdown = render_sir_to_markdown(repaired_sir_doc) print(f"修复后文档大小: {len(repaired_markdown)} 字符") # 保存修复后的文档（可选） repaired_path = os.path.join('tests', 'fixtures', 'Apache Spark 设计与实现_REPAIRED.md') with open(repaired_path, 'w', encoding='utf-8') as f: f.write(repaired_markdown) print(f"修复后文档已保存到: {repaired_path}") return { 'original_size': len(content), 'repaired_size': len(repaired_markdown), 'initial_issues': len(analysis_result.get('issues', [])), 'remaining_issues': len(final_check.get('issues', [])), 'repair_operations': len(repair_result.get('operations', [])), 'status': final_check.get('overall', {}).get('status', 'unknown') } except FileNotFoundError: print(f"错误: 找不到文档文件 {spark_doc_path}") return None except Exception as e: print(f"错误: {e}") import traceback traceback.print_exc() return None def analyze_document_structure(): """分析文档结构""" spark_doc_path = os.path.join('tests', 'fixtures', 'Apache Spark 设计与实现.md') try: with open(spark_doc_path, 'r', encoding='utf-8') as f: content = f.read() lines = content.split('\n') # 统计各级标题数量 heading_counts = {'#': 0, '##': 0, '###': 0, '####': 0, '#####': 0, '######': 0} code_blocks = 0 tables = 0 lists = 0 for line in lines: line_stripped = line.strip() # 统计标题 if line_stripped.startswith('#'): level = line_stripped.split(' ')[0].count('#') if level <= 6: heading_counts['#' * level] += 1 # 统计代码块 if line_stripped.startswith('```'): code_blocks += 1 # 统计表格（简单检测） if '|' in line_stripped and len(line_stripped.split('|')) >= 3: tables += 1 # 统计列表项 if line_stripped.startswith(('- ', '* ', '+ ', '1. ', '2. ', '3. ')): lists += 1 print("\n=== 文档结构分析 ===") print(f"总行数: {len(lines)}") print(f"一级标题 (#): {heading_counts['#']}") print(f"二级标题 (##): {heading_counts['##']}") print(f"三级标题 (###): {heading_counts['###']}") print(f"四级标题 (####): {heading_counts['####']}") print(f"五级标题 (#####): {heading_counts['#####']}") print(f"六级标题 (######): {heading_counts['######']}") print(f"代码块数量: {code_blocks // 2} (约)") # 每个代码块有开始和结束 print(f"表格数量: {tables}") print(f"列表项数量: {lists}") except Exception as e: print(f"结构分析错误: {e}") if __name__ == "__main__": print("开始测试 Apache Spark 复杂文档语义分析...") # 分析文档结构 analyze_document_structure() # 执行语义分析测试 result = test_apache_spark_document() if result: print("\n=== 测试结果汇总 ===") print(f"原始文档大小: {result['original_size']} 字符") print(f"修复后文档大小: {result['repaired_size']} 字符") print(f"初始问题数量: {result['initial_issues']}") print(f"修复操作数量: {result['repair_operations']}") print(f"剩余问题数量: {result['remaining_issues']}") print(f"最终状态: {result['status']}") else: print("测试失败")