Markdown TOC MCP Server

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 综合功能测试 本测试文件整合了以下功能的测试： 1. TOC 生成格式测试（Markdown、HTML、Text） 2. YARN 文档处理和编号分析 3. Extractor 健壮性测试 4. 性能和内存使用测试 """ import sys import os import json # 添加 src 目录到 Python 路径 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'src')) # 添加 tests 目录到 Python 路径 sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) from markdown_toc.extractor import MarkdownTOCExtractor from test_config import TEST_CONFIG, get_test_file_path, get_report_file_path, ensure_directories def test_toc_generation_formats(): """测试 TOC 生成的不同格式""" print("=== 测试 1: TOC 生成格式 ===") extractor = MarkdownTOCExtractor() # 测试内容 test_content = """# 1. 项目介绍 ## 1.1 项目背景 ### 1.1.1 技术背景 ### 1.1.2 业务背景 ## 1.2 项目目标 # 2. 技术方案 ## 2.1 架构设计 ### 2.1.1 前端架构 ### 2.1.2 后端架构 ## 2.2 技术选型 """ # 提取标题 headers = extractor.extract_toc(test_content) assert len(headers) == 10, f"期望提取 10 个标题，实际 {len(headers)} 个" # 测试不同格式的 TOC 生成 formats = ['markdown', 'html', 'text'] for fmt in formats: result = extractor.generate_toc(headers, fmt) # 验证返回结构 assert 'format' in result, f"{fmt} 格式结果应包含 format 字段" assert 'total_items' in result, f"{fmt} 格式结果应包含 total_items 字段" assert 'levels_included' in result, f"{fmt} 格式结果应包含 levels_included 字段" assert 'content' in result, f"{fmt} 格式结果应包含 content 字段" # 验证内容 assert result['format'] == fmt, f"格式应为 {fmt}" assert result['total_items'] == 10, f"总项目数应为 10，实际 {result['total_items']}" assert len(result['content']) > 0, f"{fmt} 格式内容不应为空" print(f" ✓ {fmt.upper()} 格式生成成功") print("✅ TOC 生成格式测试通过") return True def test_yarn_document_processing(): """测试 YARN 文档处理功能""" print("=== 测试 2: YARN 文档处理 ===") # 读取 yarn.md 文件 yarn_file_path = get_test_file_path('yarn.md') if not os.path.exists(yarn_file_path): print(f"⚠️ 跳过 YARN 文档测试：文件不存在 {yarn_file_path}") return True try: with open(yarn_file_path, 'r', encoding='utf-8') as f: content = f.read() except Exception as e: print(f"⚠️ 跳过 YARN 文档测试：读取文件失败 {e}") return True extractor = MarkdownTOCExtractor() # 提取标题 headers = extractor.extract_toc(content) print(f" ✓ 提取到 {len(headers)} 个标题") # 验证基本结构 assert len(headers) > 0, "应该提取到标题" # 测试编号识别 numbered_count = 0 chapter_count = 0 for header in headers: title = header['title'] number = extractor._extract_number_from_title(title, header['level']) if number is not None: numbered_count += 1 # 检查章节标题 if '章' in title: chapter_count += 1 print(f" ✓ 识别到 {numbered_count} 个编号标题") print(f" ✓ 识别到 {chapter_count} 个章节标题") # 分析编号问题 analysis = extractor.analyze_numbering_issues(headers) print(f" ✓ 编号分析完成：has_issues = {analysis['has_issues']}") print(f" ✓ 重复编号：{len(analysis['duplicate_numbers'])} 个") print(f" ✓ 不连续编号：{len(analysis['discontinuous_numbers'])} 个") # 生成 TOC toc_result = extractor.generate_toc(headers, 'markdown') assert toc_result['total_items'] == len(headers), "TOC 项目数应与标题数一致" print("✅ YARN 文档处理测试通过") return True def test_extractor_robustness(): """测试 extractor 的健壮性""" print("=== 测试 3: Extractor 健壮性 ===") extractor = MarkdownTOCExtractor() # 测试用例 1：空内容 headers = extractor.extract_toc("") assert len(headers) == 0, "空内容应返回空列表" # 测试用例 2：无标题内容 no_header_content = """这是一段普通文本。 没有任何标题。 ```python # 这是代码块 def example(): pass ``` 还是普通文本。 """ headers = extractor.extract_toc(no_header_content) assert len(headers) == 0, "无标题内容应返回空列表" # 测试用例 3：特殊字符标题 special_content = """# 1. 标题包含特殊字符：@#$%^&*() ## 1.1 中英文混合 Title with English ### 1.1.1 数字123和符号！？ ## 1.2 emoji 标题 🚀 📝 ✨ # 2. 另一个章节 """ headers = extractor.extract_toc(special_content) assert len(headers) == 5, f"期望提取 5 个标题，实际 {len(headers)} 个" # 验证特殊字符处理 for header in headers: assert 'title' in header, "每个标题应包含 title 字段" assert 'level' in header, "每个标题应包含 level 字段" assert 'line_number' in header, "每个标题应包含 line_number 字段" assert len(header['title']) > 0, "标题内容不应为空" # 测试用例 4：深层嵌套 deep_nested_content = """# 1. 第一级 ## 1.1 第二级 ### 1.1.1 第三级 #### 1.1.1.1 第四级 ##### 1.1.1.1.1 第五级 ###### 1.1.1.1.1.1 第六级 """ headers = extractor.extract_toc(deep_nested_content) assert len(headers) == 6, f"期望提取 6 个标题，实际 {len(headers)} 个" # 验证层级 expected_levels = [1, 2, 3, 4, 5, 6] actual_levels = [h['level'] for h in headers] assert actual_levels == expected_levels, f"层级不匹配：期望 {expected_levels}，实际 {actual_levels}" print("✅ Extractor 健壮性测试通过") return True def test_performance_and_memory(): """测试性能和内存使用""" print("=== 测试 4: 性能和内存 ===") import time extractor = MarkdownTOCExtractor() # 生成大文档 large_content = "" for i in range(1, 101): # 100 个章节 large_content += f"# {i}. 第{i}章\n\n" for j in range(1, 11): # 每章 10 个小节 large_content += f"## {i}.{j} 第{j}节\n\n" for k in range(1, 6): # 每节 5 个子节 large_content += f"### {i}.{j}.{k} 第{k}小节\n\n" large_content += "这是一些内容。\n\n" print(f" ✓ 生成大文档：{len(large_content)} 字符") # 测试提取性能 start_time = time.time() headers = extractor.extract_toc(large_content) extraction_time = time.time() - start_time expected_headers = 100 + 100*10 + 100*10*5 # 100 + 1000 + 5000 = 6100 assert len(headers) == expected_headers, f"期望 {expected_headers} 个标题，实际 {len(headers)} 个" print(f" ✓ 提取 {len(headers)} 个标题，耗时 {extraction_time:.3f} 秒") # 测试分析性能 start_time = time.time() analysis = extractor.analyze_numbering_issues(headers) analysis_time = time.time() - start_time print(f" ✓ 编号分析完成，耗时 {analysis_time:.3f} 秒") # 测试生成性能 start_time = time.time() toc_result = extractor.generate_toc(headers, 'markdown') generation_time = time.time() - start_time print(f" ✓ TOC 生成完成，耗时 {generation_time:.3f} 秒") total_time = extraction_time + analysis_time + generation_time print(f" ✓ 总耗时：{total_time:.3f} 秒") # 性能断言（合理的性能期望） assert extraction_time < 5.0, f"提取时间过长：{extraction_time:.3f} 秒" assert analysis_time < 2.0, f"分析时间过长：{analysis_time:.3f} 秒" assert generation_time < 3.0, f"生成时间过长：{generation_time:.3f} 秒" print("✅ 性能和内存测试通过") return True def main(): """运行所有综合测试""" print("开始综合功能测试...") print("="*50) try: test_toc_generation_formats() test_yarn_document_processing() test_extractor_robustness() test_performance_and_memory() print("\n" + "="*50) print("🎉 所有综合测试通过！") print("="*50) # 生成测试报告 report = { "test_status": "PASSED", "total_tests": 4, "passed_tests": 4, "failed_tests": 0, "test_categories": { "toc_generation_formats": "✓ 正常", "yarn_document_processing": "✓ 正常", "extractor_robustness": "✓ 正常", "performance_and_memory": "✓ 正常" }, "timestamp": "2024" } # 保存测试报告 ensure_directories() report_file = get_report_file_path('comprehensive_test_report.json') with open(report_file, 'w', encoding='utf-8') as f: json.dump(report, f, ensure_ascii=False, indent=2) print(f"📊 测试报告已保存到: {report_file}") return 0 except Exception as e: print(f"\n❌ 测试失败: {e}") import traceback traceback.print_exc() return 1 if __name__ == "__main__": exit(main())