150 lines
5.8 KiB
Python
150 lines
5.8 KiB
Python
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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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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Mock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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# 创建岗位群到面试题的映射
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industry_questions = {}
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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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interview_content = item.get('面试题内容', '')
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if industry and interview_content and industry not in industry_questions:
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questions = parse_interview_questions(interview_content)
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if questions:
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# 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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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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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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industry_questions[industry] = questions_array
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# 映射岗位群名称到ID
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industry_mapping = {
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'健康管理': 'health_1',
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'健康检查': 'health_2',
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'康复治疗': 'health_3',
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'慢性病管理': 'health_4',
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'轻医美': 'health_5',
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'心理健康': 'health_6',
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'社群运营': 'health_7',
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'药品供应链管理': 'health_8',
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'药品生产': 'health_9',
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'药品质量检测': 'health_10',
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'药物研发': 'health_11'
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}
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# 为每个岗位群添加questions字段
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updates = 0
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for orig_name, industry_id in industry_mapping.items():
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if orig_name in industry_questions:
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questions = industry_questions[orig_name]
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# 生成questions的JSON字符串
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questions_json = json.dumps(questions, ensure_ascii=False, indent=2)
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# 查找对应的岗位群并添加questions字段
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# 使用更精确的模式：在positions数组结束后添加questions
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pattern = rf'("id":\s*"{industry_id}"[^{{]*?"positions":\s*\[[^\]]*?\])\s*(\}})'
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# 添加questions字段
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replacement = rf'\1,\n "questions": {questions_json}\n \2'
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new_content, count = re.subn(pattern, replacement, content, flags=re.DOTALL)
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if count > 0:
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content = new_content
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updates += 1
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print(f"✓ 为 {orig_name} ({industry_id}) 添加了 {len(questions)} 个问题分类")
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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(content)
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print(f"\n完成！更新了 {updates} 个岗位群的面试题")
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if __name__ == "__main__":
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main()
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