a7242f0c69
- 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>
162 lines
5.9 KiB
Python
162 lines
5.9 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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print("开始替换为大健康产业数据...")
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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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# 按岗位群分组
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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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position_groups[group_name].append(item)
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# 创建岗位群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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# 生成industries数组
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industries = []
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for idx, (group_name, items) in enumerate(position_groups.items(), 1):
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group_id = group_id_map.get(group_name, f'health_{idx}')
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# 创建岗位群对象
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industry = {
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'id': group_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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# 处理该岗位群的所有岗位
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position_idx = 1
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questions_added = False
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for item in items:
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# 添加岗位
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position = {
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'id': f"{group_id}_{position_idx}",
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'title': item['岗位名称'],
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'level': item['岗位等级标签'],
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'department': group_name,
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'type': '全职',
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'experience': '1-3年',
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'education': '大专',
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'salary': '6-10K',
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'location': '北京',
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'updateTime': '2024-01-20',
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'description': f"{item['岗位名称']}职位描述",
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'requirements': [
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f"熟悉{group_name}相关工作",
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"具有良好的沟通能力",
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"有相关工作经验优先"
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]
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}
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industry['positions'].append(position)
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position_idx += 1
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# 添加面试题（只添加一次）
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if not questions_added and item.get('面试题内容'):
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# 解析面试题内容
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content = item['面试题内容']
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# 提取大类问题
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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]+、|$)', content, re.DOTALL)
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if sections:
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for section_idx, (section_title, section_content) in enumerate(sections, 1):
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# 提取具体问题
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questions = re.findall(r'(\d+\.\s*[^\\n]+)\\n\\s*示例答案[：:]\\n(.*?)(?=\\d+\.|$)', section_content, re.DOTALL)
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if questions:
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subQuestions = []
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for q_idx, (question_text, answer_text) in enumerate(questions, 1):
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subQuestions.append({
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'id': f'q{q_idx}',
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'question': question_text.strip(),
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'answer': answer_text.strip()
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})
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if subQuestions:
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industry['questions'].append({
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'id': f"{group_id}_q{section_idx}",
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'question': section_title.strip(),
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'subQuestions': subQuestions[:3] # 只取前3个问题
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})
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questions_added = True
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# 如果没有面试题，添加默认的
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if not industry['questions']:
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industry['questions'].append({
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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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industries.append(industry)
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# 生成resumeTemplates对象
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resumeTemplates = {}
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for group_name, items in position_groups.items():
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templates = []
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for item in items:
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template = {
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'position': item['岗位名称'],
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'level': item['岗位等级标签'],
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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'] # 使用相同内容作为modified版本
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}
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}
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templates.append(template)
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resumeTemplates[group_name] = templates
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# 保存转换后的数据
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output = {
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'industries': industries,
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'resumeTemplates': resumeTemplates
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}
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/health_mock_data.json', 'w', encoding='utf-8') as f:
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json.dump(output, f, ensure_ascii=False, indent=2)
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print(f"\n✓ 数据转换完成!")
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print(f" - 生成了 {len(industries)} 个岗位群")
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print(f" - 总计 {sum(len(ind['positions']) for ind in industries)} 个岗位")
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print(f" - 数据已保存到 health_mock_data.json")
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print("\n下一步：将生成的数据替换到 resumeInterviewMock.js 中") |