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>
236 lines
9.8 KiB
Python
236 lines
9.8 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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def parse_interview_questions(content):
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"""解析面试题内容为结构化数据"""
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questions = []
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# 分割成不同的问题类别
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sections = re.split(r'\n# ([一二三四五六七八九十]+、[^#\n]+)', content)
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question_id = 1
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for i in range(1, len(sections), 2):
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if i >= len(sections):
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break
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section_title = sections[i].strip()
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section_content = sections[i + 1] if i + 1 < len(sections) else ""
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# 提取每个问题
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question_blocks = re.split(r'\n\d+\.\s+', section_content)
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for j, block in enumerate(question_blocks[1:], 1): # 跳过第一个空块
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lines = block.strip().split('\n')
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if not lines:
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continue
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question_text = lines[0].strip()
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# 查找答案
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answer_text = ""
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for k, line in enumerate(lines):
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if '示例答案' in line or '答案' in line:
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# 获取答案内容
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answer_lines = []
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for answer_line in lines[k+1:]:
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answer_line = answer_line.strip()
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if answer_line and not answer_line.startswith('示例答案'):
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if re.match(r'^\d+\.', answer_line):
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break
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answer_lines.append(answer_line)
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answer_text = ' '.join(answer_lines)
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break
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if question_text and answer_text:
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questions.append({
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"id": f"q{question_id}",
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"question": question_text,
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"answer": answer_text
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})
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question_id += 1
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return questions
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def main():
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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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# 读取现有的Mock数据
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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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mock_content = f.read()
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# 收集所有岗位群的数据
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all_industries = {}
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for item in health_data:
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industry = item.get('简历岗位群', '')
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position_name = item.get('岗位名称', '')
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avatar_url = item.get('简历头像url', '')
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level_tag = item.get('岗位等级标签', '')
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interview_content = item.get('面试题内容', '')
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if industry:
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if industry not in all_industries:
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all_industries[industry] = {
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'positions': [],
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'questions': None
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}
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# 添加岗位信息
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all_industries[industry]['positions'].append({
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'name': position_name,
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'avatar': avatar_url,
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'level': level_tag
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})
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# 添加面试题（只添加一次）
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if interview_content and not all_industries[industry]['questions']:
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questions = parse_interview_questions(interview_content)
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if questions:
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# 将问题按类别分组
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category_questions = {}
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current_category = "综合面试题"
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for q in questions:
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# 检查是否是新的分类
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if '岗位理解' in q['question']:
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current_category = "岗位理解类问题"
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elif '实践经验' in q['question'] or '案例' in q['question']:
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current_category = "实践经验类问题"
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elif '客户服务' in q['question'] or '客户' in q['question']:
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current_category = "客户服务类问题"
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elif '市场' in q['question'] or '趋势' in q['question']:
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current_category = "市场与未来趋势类问题"
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elif '技术' in q['question'] or '专业' in q['question']:
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current_category = "专业技术类问题"
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elif '团队' in q['question'] or '协作' in q['question']:
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current_category = "团队协作类问题"
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if current_category not in category_questions:
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category_questions[current_category] = []
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category_questions[current_category].append(q)
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# 构建questions数组
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questions_array = []
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cat_id = 1
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for category, cat_questions in category_questions.items():
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questions_array.append({
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"id": f"group_q{cat_id}",
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"question": category,
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"subQuestions": cat_questions
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})
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cat_id += 1
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all_industries[industry]['questions'] = questions_array
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# 需要添加的新岗位群（不在现有Mock中的）
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new_industries = ['社群运营', '药品供应链管理', '药品生产', '药品质量检测', '药物研发']
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# 生成新的岗位群数据
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new_industry_blocks = []
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industry_id = 7 # 从health_7开始
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for industry_name in new_industries:
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if industry_name in all_industries:
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industry_data = all_industries[industry_name]
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# 构建positions数组
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positions_data = []
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for idx, pos in enumerate(industry_data['positions'], 1):
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level_mapping = {
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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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'管理培训生岗': '管理培训生岗',
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'管理岗': '管理岗'
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}
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position_obj = {
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"id": f"health_{industry_id}_{idx}",
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"title": pos['name'],
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"level": level_mapping.get(pos['level'], '普通岗'),
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"avatar": pos['avatar'],
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"department": industry_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": "5-10K",
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"location": "北京",
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"updateTime": "2024-01-20",
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"description": f"负责{pos['name']}相关工作",
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"requirements": [
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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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positions_data.append(position_obj)
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# 构建industry对象
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industry_obj = {
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"id": f"health_{industry_id}",
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"name": industry_name,
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"positions": positions_data
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}
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# 添加questions（如果有的话）
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if industry_data['questions']:
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industry_obj["questions"] = industry_data['questions']
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else:
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# 使用默认的面试题结构
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industry_obj["questions"] = [
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{
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"id": "group_q1",
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"question": f"{industry_name}专业认知",
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"subQuestions": [
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{
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"id": "q1",
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"question": f"你如何理解{industry_name}的核心价值？",
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"answer": f"{industry_name}的核心价值在于通过专业技能和知识，为企业和客户创造价值，推动行业发展。"
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},
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{
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"id": "q2",
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"question": f"{industry_name}中最重要的能力是什么？",
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"answer": "专业技能、沟通能力、团队协作和持续学习能力都是非常重要的。"
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},
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{
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"id": "q3",
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"question": f"你为什么选择{industry_name}这个方向？",
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"answer": "我对这个领域充满热情，相信能够在这里发挥我的专业优势，为行业发展做出贡献。"
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}
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]
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}
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]
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new_industry_blocks.append(industry_obj)
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industry_id += 1
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# 将新的岗位群添加到Mock文件中
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# 找到industries数组的结束位置
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industries_end_pattern = r'(const industries = \[[^\]]*)\]'
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# 生成新的岗位群JavaScript代码
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new_blocks_js = ""
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for block in new_industry_blocks:
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new_blocks_js += ",\n " + json.dumps(block, ensure_ascii=False, indent=2).replace('\n', '\n ')
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# 替换
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replacement = rf'\1{new_blocks_js}\n]'
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new_content = re.sub(industries_end_pattern, replacement, mock_content, flags=re.DOTALL)
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# 写回文件
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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(f"成功添加了 {len(new_industry_blocks)} 个新岗位群：")
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for block in new_industry_blocks:
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print(f" - {block['name']} (ID: {block['id']}): {len(block['positions'])} 个岗位")
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# 统计总数
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print(f"\n现在总共有 11 个岗位群")
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if __name__ == "__main__":
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main() |