Initial commit: 教务系统在线平台
- 包含4个产业方向的前端项目：智能开发、智能制造、大健康、财经商贸 - 已清理node_modules、.yoyo等大文件，项目大小从2.6GB优化至631MB - 配置完善的.gitignore文件 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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frontend_大健康/fix_questions_structure.py
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frontend_大健康/fix_questions_structure.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import json
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import re
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print("修正面试题结构，移除大类标题作为题目...")
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# 读取大健康岗位简历数据
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/网页未导入数据/大健康产业/大健康岗位简历.json', 'r', encoding='utf-8') as f:
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health_data = json.load(f)
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# 备份当前文件
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/src/mocks/resumeInterviewMock.js', 'r', encoding='utf-8') as f:
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content = f.read()
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/src/mocks/resumeInterviewMock.js.backup_fix_structure', 'w', encoding='utf-8') as f:
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f.write(content)
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# 读取当前的mock数据
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/health_mock_data_full.json', 'r', encoding='utf-8') as f:
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mock_data = json.load(f)
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# 按岗位群分组，提取完整面试题
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position_groups = {}
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for item in health_data:
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group_name = item['简历岗位群']
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if group_name not in position_groups:
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position_groups[group_name] = {
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'positions': [],
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'questions_content': item.get('面试题内容', ''),
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'questions_title': item.get('面试题', '')
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}
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# 岗位群ID映射
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group_id_map = {
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'健康管理': 'health_management',
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'健康检查': 'health_check',
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'康复治疗': 'rehabilitation',
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'慢性病管理': 'chronic_disease',
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'轻医美': 'medical_beauty',
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'社群运营': 'community_operation',
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'心理健康': 'mental_health',
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'药品供应链管理': 'pharma_supply',
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'药品生产': 'pharma_production',
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'药品质量检测': 'pharma_quality',
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'药物研发': 'pharma_research'
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}
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# 解析面试题内容 - 只提取实际的问题，不包括大类标题
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def parse_questions_correctly(content, group_id, group_name, questions_title):
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if not content:
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return [{
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'id': f"{group_id}_q1",
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'question': f"{group_name}岗位群面试题",
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'subQuestions': [
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{
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'id': 'q1',
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'question': f"您如何理解{group_name}工作的核心要点？",
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'answer': f"{group_name}工作需要专业知识、实践经验和良好的沟通能力。"
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},
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{
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'id': 'q2',
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'question': f"在{group_name}领域，您认为最重要的技能是什么？",
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'answer': f"最重要的是专业技术能力、团队协作能力和持续学习能力。"
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},
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{
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'id': 'q3',
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'question': f"您为什么选择{group_name}这个职业方向？",
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'answer': f"我对{group_name}领域充满热情，希望在这个领域深耕发展。"
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}
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]
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}]
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all_sub_questions = []
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q_counter = 1
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# 提取所有大类问题，但不将大类标题作为题目
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sections = re.findall(r'#\s*([一二三四五六七八九十]+、[^\n]+)\n(.*?)(?=#\s*[一二三四五六七八九十]+、|$)', content, re.DOTALL)
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for section_idx, (section_title, section_content) in enumerate(sections):
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# 只提取该大类下的具体问题和答案
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q_pattern = r'(\d+\.\s*[^\n]+)\n\s*示例答案[：:]\s*\n(.*?)(?=\d+\.|#|$)'
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questions_match = re.findall(q_pattern, section_content, re.DOTALL)
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for question_text, answer_text in questions_match:
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# 清理问题和答案文本
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question_clean = question_text.strip()
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answer_clean = answer_text.strip()
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all_sub_questions.append({
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'id': f'q{q_counter}',
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'question': question_clean,
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'answer': answer_clean
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})
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q_counter += 1
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# 如果没有找到问题，添加默认问题
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if not all_sub_questions:
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all_sub_questions = [
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{
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'id': 'q1',
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'question': f"您如何理解{group_name}工作的核心要点？",
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'answer': f"{group_name}工作需要专业知识、实践经验和良好的沟通能力。"
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},
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{
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'id': 'q2',
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'question': f"在{group_name}领域，您认为最重要的技能是什么？",
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'answer': f"最重要的是专业技术能力、团队协作能力和持续学习能力。"
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},
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{
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'id': 'q3',
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'question': f"您为什么选择{group_name}这个职业方向？",
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'answer': f"我对{group_name}领域充满热情，希望在这个领域深耕发展。"
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}
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]
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# 创建单个面试题卡片，包含所有实际问题
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card_title = questions_title if questions_title else f"{group_name}岗位群面试题"
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return [{
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'id': f"{group_id}_q1",
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'question': card_title,
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'subQuestions': all_sub_questions
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}]
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# 更新industries中的questions - 每个岗位群只有一个面试题卡片
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for industry in mock_data['industries']:
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group_name = industry['name']
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if group_name in position_groups:
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questions_content = position_groups[group_name]['questions_content']
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questions_title = position_groups[group_name]['questions_title']
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# 生成单个卡片包含所有面试题（不包括大类标题）
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single_card_questions = parse_questions_correctly(
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questions_content,
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industry['id'],
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group_name,
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questions_title
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)
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industry['questions'] = single_card_questions
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total_questions = len(single_card_questions[0]['subQuestions']) if single_card_questions else 0
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print(f"✓ {group_name}: 1个卡片，包含 {total_questions} 个实际问题")
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# 将更新后的数据转换为JavaScript格式
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industries_js = json.dumps(mock_data['industries'], ensure_ascii=False, indent=2)
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resumeTemplates_js = json.dumps(mock_data['resumeTemplates'], ensure_ascii=False, indent=2)
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# 创建新的Mock文件内容
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new_content = f"""// 简历与面试题Mock数据
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// 岗位群列表
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const industries = {industries_js};
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// 简历模板数据
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const resumeTemplates = {resumeTemplates_js};
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// 我的简历数据
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const myResume = {{
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personalInfo: {{
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name: "张三",
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phone: "138****8888",
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email: "zhangsan@example.com",
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age: 25,
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education: "苏州信息职业技术学院 2020.9-2023.6",
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experience: "2年",
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location: "北京"
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}},
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workExperience: [
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{{
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company: "某健康管理公司",
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position: "健康管理师",
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duration: "2022.03-2024.01",
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description: "负责健康评估和健康管理方案制定工作"
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}}
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],
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skills: ["健康评估", "健康管理", "数据分析", "客户服务"],
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projects: [
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{{
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name: "企业员工健康管理项目",
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role: "健康管理师",
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duration: "2023.05-2023.12",
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description: "负责企业员工的健康评估和管理方案制定"
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}}
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]
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}};
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// 获取页面mock数据的函数
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export function getMockPageData() {{
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return resumeInterviewMockData;
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}}
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// 导出合并的数据
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export const resumeInterviewMockData = {{
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industries,
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resumeTemplates,
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myResume
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}};
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"""
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# 写入新内容
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
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f.write(new_content)
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print("\n✓ 面试题结构修正完成!")
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print(" - 已移除大类标题作为题目")
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print(" - 只保留实际的面试问题和答案")
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print(" - 原文件已备份为 resumeInterviewMock.js.backup_fix_structure")
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