ALL-teach_sys/frontend_视觉设计/fix_interview_questions.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import json
import re

def parse_interview_content(content):
    """解析面试题内容，提取问题和答案"""
    questions = []
    
    # 按照 "问题：" 分割内容
    parts = re.split(r'\n\s*\d+\.\s*问题[：:]\s*', content)
    
    for i, part in enumerate(parts):
        if i == 0:  # 跳过第一个部分（通常是标题）
            continue
            
        lines = part.strip().split('\n')
        if not lines:
            continue
            
        # 第一行是问题
        question_text = lines[0].strip()
        
        # 查找答案部分
        answer_lines = []
        in_answer = False
        
        for line in lines[1:]:
            line = line.strip()
            if line.startswith('参考回答') or line.startswith('答案'):
                in_answer = True
                continue
            elif line.startswith('问题') or (line and line[0].isdigit() and '问题' in line):
                break
            elif in_answer and line:
                answer_lines.append(line)
        
        answer_text = '\\n'.join(answer_lines).strip()
        
        if question_text and answer_text:
            questions.append({
                "id": f"q_{i}",
                "question": question_text,
                "answer": answer_text,
                "difficulty": "中等",
                "tags": ["专业技能", "实践经验"]
            })
    
    return questions

def create_new_mock_data():
    """重新创建完整的mock数据"""
    # 读取视觉设计原始数据
    with open('网页未导入数据/视觉设计产业/视觉设计岗位简历.json', 'r', encoding='utf-8') as f:
        visual_data = json.load(f)
    
    # 按岗位群分组
    position_groups = {}
    interview_groups = {}
    
    for position in visual_data:
        group_name = position['简历岗位群']
        
        # 收集岗位数据
        if group_name not in position_groups:
            position_groups[group_name] = []
        position_groups[group_name].append(position)
        
        # 收集面试题数据
        if group_name not in interview_groups:
            interview_detail = position.get('面试题内容', '')
            if interview_detail:
                questions = parse_interview_content(interview_detail)
                interview_groups[group_name] = questions
    
    # 创建industries数据
    industries = []
    
    for group_id, (group_name, positions) in enumerate(position_groups.items()):
        # 创建positions数据
        industry_positions = []
        for pos_id, position in enumerate(positions):
            level = position.get('岗位等级标签', '普通岗')
            pos_obj = {
                "id": f"visual_design_{group_id + 1}_{pos_id + 1}",
                "title": position['岗位名称'],
                "level": level,
                "avatar": position.get('简历头像url', '').split(',')[0],
                "department": group_name,
                "type": "全职",
                "experience": "1-3年",
                "education": "大专",
                "salary": "6-12K",
                "location": "苏州",
                "updateTime": "2024-01-20",
                "description": f"负责{position['岗位名称']}相关工作",
                "requirements": [
                    f"具备{group_name}专业技能",
                    "熟悉相关设计软件",
                    "具备良好的沟通协作能力",
                    "有创新意识和学习能力"
                ]
            }
            industry_positions.append(pos_obj)
        
        # 创建面试题数据
        interview_questions = interview_groups.get(group_name, [])
        if not interview_questions:
            # 默认面试题
            interview_questions = [
                {
                    "id": f"q_default_1",
                    "question": f"{group_name}岗位的核心职责是什么？",
                    "answer": f"负责{group_name}相关工作，包括设计规划、创意实现、项目协作等，确保项目质量和进度。",
                    "difficulty": "基础",
                    "tags": ["专业认知", "岗位职责"]
                }
            ]
        
        questions_data = {
            "id": f"group_q{group_id + 1}",
            "question": f"# 一、专业能力与行业认知",
            "subQuestions": interview_questions
        }
        
        # 创建industry对象
        industry = {
            "id": f"visual_design_{group_id + 1}",
            "name": group_name,
            "positions": industry_positions,
            "questions": [questions_data]
        }
        
        industries.append(industry)
    
    return industries

def create_resume_templates():
    """创建简历模板数据"""
    with open('网页未导入数据/视觉设计产业/视觉设计岗位简历.json', 'r', encoding='utf-8') as f:
        visual_data = json.load(f)
    
    templates = {}
    position_groups = {}
    
    # 按岗位群分组
    for position in visual_data:
        group_name = position['简历岗位群']
        if group_name not in position_groups:
            position_groups[group_name] = []
        position_groups[group_name].append(position)
    
    # 为每个岗位群创建模板
    for group_name, positions in position_groups.items():
        templates[group_name] = []
        
        for position in positions:
            template = {
                "id": f"resume_{len(templates[group_name]) + 1}",
                "position": position['岗位名称'],
                "level": position.get('岗位等级标签', '普通岗'),
                "industry": group_name,
                "studentInfo": {
                    "name": "张小同",
                    "gender": "女",
                    "age": 22,
                    "education": "大专",
                    "major": "数字媒体艺术设计",
                    "avatar": position.get('简历头像url', '').split(',')[0]
                },
                "content": {
                    "original": position.get('简历内容', ''),
                    "modified": position.get('简历内容', '')
                },
                "interviewQuestions": position.get('面试题内容', '')
            }
            
            templates[group_name].append(template)
    
    return templates

def main():
    print("🚀 重新生成完整的面试题数据...")
    
    # 创建备份
    import shutil
    from datetime import datetime
    
    backup_name = f"src/mocks/resumeInterviewMock.js.backup_fix_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
    shutil.copy('src/mocks/resumeInterviewMock.js', backup_name)
    print(f"📦 已创建备份: {backup_name}")
    
    # 重新创建数据
    industries = create_new_mock_data()
    resume_templates = create_resume_templates()
    
    # 创建完整的mock数据
    my_resume = {
        "name": "张小同",
        "studentId": "2024001",
        "major": "数字媒体艺术设计",
        "education": "大专",
        "avatar": "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/butler_position_avatar/default_student.jpeg"
    }
    
    # 生成新的JS文件内容
    js_content = f"""// 简历与面试题Mock数据

// 岗位群列表
const industries = {json.dumps(industries, ensure_ascii=False, indent=2)};

// 简历模板数据
const resumeTemplates = {json.dumps(resume_templates, ensure_ascii=False, indent=2)};

// 我的简历数据
const myResume = {json.dumps(my_resume, ensure_ascii=False, indent=2)};

// 获取页面数据
export const getMockPageData = () => {{
  return {{
    industries,
    resumeTemplates,
    myResume
  }};
}};

// 导出各个数据模块
export {{ industries, resumeTemplates, myResume }};
"""
    
    # 写入文件
    with open('src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
        f.write(js_content)
    
    print("✅ 已重新生成 resumeInterviewMock.js")
    print(f"\\n📊 数据统计:")
    print(f"   - 岗位群数量: {len(industries)}")
    print(f"   - 岗位总数: {sum(len(industry['positions']) for industry in industries)}")
    
    # 显示每个岗位群的面试题数量
    for industry in industries:
        group_name = industry['name']
        question_count = len(industry['questions'][0]['subQuestions'])
        print(f"   - {group_name}: {question_count} 道面试题")

if __name__ == "__main__":
    main()