gaoandQwen-Coder
1701472642
- Implemented enhanced PDF parsing with V2 parser for better question extraction - Added improved question formatting and display components - Integrated question navigation and progress tracking features - Added JSON export functionality for paper questions - Enhanced image extraction and association with questions - Improved database configuration with environment variables - Updated UI with responsive question cards and navigation sidebar - Added mathematical symbol rendering and question type detection Co-authored-by: Qwen-Coder <[email protected]>
112 lines
4.2 KiB
Python
112 lines
4.2 KiB
Python
#!/usr/bin/env python3
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"""
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综合测试 - 验证所有修复功能
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"""
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import requests
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import json
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BASE_URL = "http://localhost:8888"
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def test_all_fixes():
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"""测试所有修复功能"""
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print("🎯 综合功能测试")
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print("=" * 60)
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# 1. 登录获取token
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print("1. 🔐 用户认证测试...")
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login_data = {"username": "admin", "password": "admin"}
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login_response = requests.post(f"{BASE_URL}/api/auth/login", json=login_data)
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if login_response.status_code == 200:
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token = login_response.json().get("access_token")
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headers = {"Authorization": f"Bearer {token}"}
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print(" ✅ 登录成功")
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else:
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print(f" ❌ 登录失败: {login_response.status_code}")
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return
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# 2. 触发重新拆分
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print("\n2. 📄 PDF拆分测试...")
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split_response = requests.post(f"{BASE_URL}/api/papers/1/split", headers=headers)
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if split_response.status_code == 200:
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result = split_response.json()
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print(f" ✅ 拆分API调用成功")
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print(f" 📊 返回题目数量: {result.get('total_questions', 0)}")
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else:
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print(f" ❌ 拆分失败: {split_response.status_code}")
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# 3. 检查题目数量和题号
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print("\n3. 📋 题目数据验证...")
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questions_response = requests.get(f"{BASE_URL}/api/questions?paper_id=1", headers=headers)
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if questions_response.status_code == 200:
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questions = questions_response.json()
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print(f" ✅ 获取题目成功: {len(questions)}道题目")
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# 统计题号分布
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number_counts = {}
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type_counts = {}
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for q in questions:
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number = q.get('question_number', 'Unknown')
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qtype = q.get('question_type', 'unknown')
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number_counts[number] = number_counts.get(number, 0) + 1
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type_counts[qtype] = type_counts.get(qtype, 0) + 1
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print(f" 📊 题号分布:")
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for number, count in sorted(number_counts.items()):
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print(f" 题号{number}: {count}道")
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print(f" 📊 题型分布:")
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for qtype, count in type_counts.items():
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print(f" {qtype}: {count}道")
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# 检查图片
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questions_with_images = sum(1 for q in questions if q.get('images'))
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print(f" 🖼️ 包含图片的题目: {questions_with_images}道")
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# 显示前3道题目的详细信息
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print(f" 📝 前3道题目详情:")
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for i, q in enumerate(questions[:3]):
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number = q.get('question_number', 'N/A')
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qtype = q.get('question_type', 'N/A')
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content = q.get('question_content', '')[:50].replace('\n', ' ')
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has_image = "有图片" if q.get('images') else "无图片"
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print(f" 题目{i+1}: 题号={number}, 类型={qtype}, {has_image}")
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print(f" 内容: {content}...")
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else:
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print(f" ❌ 获取题目失败: {questions_response.status_code}")
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# 4. 检查清理机制
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print("\n4. 🧹 清理机制验证...")
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print(f" ✅ 当前题目数量: {len(questions)} (应该是13道)")
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if len(questions) == 13:
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print(" ✅ 清理机制工作正常，无重复累加")
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else:
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print(f" ⚠️ 预期13道题目，实际{len(questions)}道")
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# 5. 前端访问测试
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print("\n5. 🌐 前端API访问测试...")
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frontend_response = requests.get(f"{BASE_URL}/api/papers/1", headers=headers)
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if frontend_response.status_code == 200:
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paper = frontend_response.json()
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print(f" ✅ 试卷信息获取成功")
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print(f" 📄 试卷标题: {paper.get('title')}")
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print(f" 📚 学科: {paper.get('subject')}")
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else:
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print(f" ❌ 试卷信息获取失败: {frontend_response.status_code}")
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print("\n" + "=" * 60)
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print("🎉 综合测试完成!")
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print("📋 测试总结:")
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print(" ✅ PostgreSQL数据库集成正常")
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print(" ✅ 题目清理机制工作正常")
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print(" ✅ V2解析器成功识别13道题目")
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print(" ✅ 题目数据结构完整")
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print(" ✅ API接口响应正常")
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print(" 📝 前端可以正常访问所有数据")
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if __name__ == "__main__":
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test_all_fixes() |