cd2e307402
主要内容： - 包含12个产业的完整教务系统前端代码 - 智能启动脚本 (start-industry.sh) - 可视化产业导航页面 (index.html) - 项目文档 (README.md) 优化内容： - 删除所有node_modules和.yoyo文件夹，从7.5GB减少到2.7GB - 添加.gitignore文件避免上传不必要的文件 - 自动依赖管理和智能启动系统 产业列表： 1. 文旅产业 (5150) 2. 智能制造 (5151) 3. 智能开发 (5152) 4. 财经商贸 (5153) 5. 视觉设计 (5154) 6. 交通物流 (5155) 7. 大健康 (5156) 8. 土木水利 (5157) 9. 食品产业 (5158) 10. 化工产业 (5159) 11. 能源产业 (5160) 12. 环保产业 (5161) 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
245 lines
9.0 KiB
Python
245 lines
9.0 KiB
Python
#!/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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from collections import defaultdict
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def load_health_data():
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"""加载大健康数据"""
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with open('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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resume_data = json.load(f)
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with open('网页未导入数据/大健康产业/大健康问答内容.json', 'r', encoding='utf-8') as f:
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qa_data = json.load(f)
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return resume_data, qa_data
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def map_level(level_tag):
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"""映射岗位等级"""
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level_map = {
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'基础岗': '普通岗',
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'技术骨干岗': '技术骨干岗',
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'普通岗': '普通岗'
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}
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return level_map.get(level_tag, '普通岗')
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def parse_resume_content(content):
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"""解析简历内容，提取关键信息"""
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# 提取项目经历
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project_match = re.search(r'项目名称：(.+?)\n', content)
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project_name = project_match.group(1) if project_match else "健康管理项目"
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# 提取岗位职责（取前3条）
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responsibilities = []
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resp_pattern = r'\d+\.\s*([^；\n]+[；。]?)'
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resp_matches = re.findall(resp_pattern, content)
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if resp_matches:
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responsibilities = [m.strip().rstrip('；。') for m in resp_matches[:3]]
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# 提取核心能力
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core_skills = []
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if '### （一）核心能力' in content:
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core_section = content.split('### （一）核心能力')[1].split('### （二）')[0]
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skill_matches = re.findall(r'\d+\.\s*([^。\n]+。?)', core_section)
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core_skills = [s.strip().rstrip('。') for s in skill_matches[:5]]
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# 提取个人评价
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summary = "我是一名大专毕业生，具备扎实的专业基础和实践经验。"
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if '# 三、个人评价' in content or '# 三、个人总结' in content:
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summary_section = content.split('# 三、')[1]
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summary_text = re.sub(r'\n+', ' ', summary_section).strip()
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if len(summary_text) > 50:
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summary = summary_text[:200] + "..."
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return {
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'project_name': project_name,
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'responsibilities': responsibilities,
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'core_skills': core_skills,
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'summary': summary
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}
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def create_industries_structure(resume_data, qa_data):
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"""创建industries数据结构"""
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# 按岗位群分组
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groups = defaultdict(list)
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for item in resume_data:
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group_name = item['简历岗位群']
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groups[group_name].append(item)
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industries = []
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industry_id = 1
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for group_name, positions_data in groups.items():
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industry = {
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"id": f"health_{industry_id}",
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"name": group_name,
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"positions": [],
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"questions": []
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}
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position_id = 1
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for pos in positions_data:
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# 解析简历内容获取更详细的信息
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parsed_info = parse_resume_content(pos['简历内容'])
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position = {
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"id": f"health_{industry_id}_{position_id}",
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"title": pos['岗位名称'],
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"level": map_level(pos['岗位等级标签']),
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"avatar": pos['简历头像url'],
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"department": group_name,
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"type": "全职",
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"experience": "1-3年" if pos['岗位等级标签'] == '基础岗' else "2-5年",
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"education": "大专",
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"salary": "5-10K" if pos['岗位等级标签'] == '基础岗' else "8-15K",
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"location": "北京",
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"updateTime": "2024-01-20",
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"description": f"负责{pos['岗位名称']}相关工作，包括{parsed_info['responsibilities'][0] if parsed_info['responsibilities'] else '日常工作'}",
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"requirements": parsed_info['responsibilities'][:4] if len(parsed_info['responsibilities']) >= 4 else [
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"具备相关专业知识和技能",
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"有良好的沟通能力和团队合作精神",
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"能够独立完成岗位职责",
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"有相关实习或工作经验优先"
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]
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}
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industry["positions"].append(position)
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position_id += 1
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# 添加基于岗位群的问题
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questions = []
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question_id = 1
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# 添加通用问题
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main_question = {
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"id": f"group_q{industry_id}",
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"question": f"# 一、{group_name}专业认知",
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"subQuestions": []
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}
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# 从大健康问答内容中提取相关问题
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for qa in qa_data[:3]: # 取前3个问答作为示例
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sub_q = {
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"id": f"q{industry_id}_{question_id}",
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"question": qa.get('问题_流程1', f"请介绍一下您对{group_name}的理解？"),
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"answer": qa.get('回答_流程2', f"在{group_name}领域，我通过系统学习和实践，掌握了相关专业知识和技能。")
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}
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main_question["subQuestions"].append(sub_q)
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question_id += 1
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industry["questions"].append(main_question)
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industries.append(industry)
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industry_id += 1
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return industries
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def create_resume_templates(resume_data):
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"""创建resumeTemplates数据结构"""
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templates = defaultdict(list)
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for item in resume_data:
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group_name = item['简历岗位群']
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parsed_info = parse_resume_content(item['简历内容'])
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template = {
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"position": item['岗位名称'],
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"level": map_level(item['岗位等级标签']),
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"avatar": item['简历头像url'],
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"content": {
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"original": item['简历内容'],
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"modified": item['简历内容'] # 使用相同内容
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},
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"studentInfo": {
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"project_experience": {
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"project_name": parsed_info['project_name'],
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"position": item['岗位名称'] + "助理",
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"time_period": "XXXXXX",
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"company": "XXXXXX",
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"description": " ；\n".join(parsed_info['responsibilities'][:10]) if parsed_info['responsibilities'] else f"参与{item['岗位名称']}相关工作"
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},
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"core_skills": parsed_info['core_skills'][:9] if parsed_info['core_skills'] else [
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f"熟悉{group_name}相关理论知识",
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"具备实践操作能力",
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"良好的沟通协调能力"
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],
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"compound_skills": [
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"医疗服务与健康管理常识：了解我国医疗体系的基本结构与服务流程",
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"患者安全意识：了解生命体征监测、基础护理技能",
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"医疗人工智能基础认知：了解AI在医疗健康领域的应用",
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"质量控制认知：了解ISO体系和质量管理基本要求",
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"药品营销能力：掌握客户需求识别和沟通技巧"
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],
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"personal_summary": parsed_info['summary']
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}
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}
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templates[group_name].append(template)
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return dict(templates)
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def save_as_js_module(industries, resume_templates):
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"""保存为JS模块格式"""
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# 转换为JSON字符串，确保正确转义
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industries_json = json.dumps(industries, ensure_ascii=False, indent=2)
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templates_json = json.dumps(resume_templates, ensure_ascii=False, indent=2)
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# 创建临时JS文件内容
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js_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_json};
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// 简历模板数据
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const resumeTemplates = {templates_json};
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// 导出函数
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export const getMockPageData = () => {{
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return {{
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industries,
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resumeTemplates
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}};
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}};
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export {{
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industries,
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resumeTemplates
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}};'''
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# 保存为临时文件
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with open('temp_mock_data.js', 'w', encoding='utf-8') as f:
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f.write(js_content)
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print("已生成临时文件 temp_mock_data.js")
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return True
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def main():
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print("开始转换大健康数据...")
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# 加载数据
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resume_data, qa_data = load_health_data()
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print(f"加载了 {len(resume_data)} 个岗位简历数据")
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print(f"加载了 {len(qa_data)} 个问答数据")
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# 创建数据结构
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industries = create_industries_structure(resume_data, qa_data)
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resume_templates = create_resume_templates(resume_data)
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# 输出统计
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print(f"\n转换完成：")
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print(f"- {len(industries)} 个岗位群")
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print(f"- {sum(len(ind['positions']) for ind in industries)} 个岗位")
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print(f"- {sum(len(templates) for templates in resume_templates.values())} 个简历模板")
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# 保存为JS模块
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save_as_js_module(industries, resume_templates)
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# 输出各岗位群信息
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print("\n岗位群详情：")
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for industry in industries:
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print(f" {industry['name']}: {len(industry['positions'])} 个岗位")
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print("\n请手动将 temp_mock_data.js 的内容合并到 resumeInterviewMock.js 中")
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if __name__ == "__main__":
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main() |