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>
226 lines
9.0 KiB
Python
226 lines
9.0 KiB
Python
#!/usr/bin/env python3
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import json
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import os
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from datetime import datetime
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# 读取视觉设计岗位简历.json文件
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json_file = '网页未导入数据/视觉设计产业/视觉设计岗位简历.json'
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mock_file = 'src/mocks/resumeInterviewMock.js'
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print("正在读取完整的面试题数据...")
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with open(json_file, 'r', encoding='utf-8') as f:
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positions_data = json.load(f)
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# 创建岗位名称到面试题的映射
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interview_questions_map = {}
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for position in positions_data:
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position_name = position.get("岗位名称", "")
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interview_content = position.get("面试题内容", "")
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if position_name and interview_content:
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# 解析markdown格式的面试题
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questions = []
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lines = interview_content.split('\n')
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current_section = ""
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current_question = None
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for line in lines:
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line = line.strip()
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if line.startswith('# '):
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# 新的大分类
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current_section = line[2:].strip()
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elif line and line[0].isdigit() and '. 问题' in line:
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# 保存上一个问题
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if current_question:
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questions.append(current_question)
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# 提取问题文本
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parts = line.split('问题：', 1)
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if len(parts) > 1:
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question_text = parts[1].strip()
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else:
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parts = line.split('问题:', 1)
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if len(parts) > 1:
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question_text = parts[1].strip()
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else:
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question_text = line
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current_question = {
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"question": question_text,
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"answer": "",
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"section": current_section
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}
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elif line.startswith('答案：') or line.startswith('答案:'):
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if current_question:
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answer = line.replace('答案：', '').replace('答案:', '').strip()
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current_question["answer"] = answer
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elif current_question and line and not line.startswith('#') and not (line[0].isdigit() and '. 问题' in line):
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# 继续添加到答案中（多行答案）
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if current_question["answer"] and not line.startswith('---'):
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current_question["answer"] += " " + line
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# 添加最后一个问题
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if current_question:
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questions.append(current_question)
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interview_questions_map[position_name] = questions
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if questions:
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print(f"解析 {position_name} 的面试题，共 {len(questions)} 个问题")
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print(f"\n总共找到 {len(interview_questions_map)} 个岗位的面试题")
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# 读取resumeInterviewMock.js文件
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print("\n正在读取 resumeInterviewMock.js...")
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with open(mock_file, 'r', encoding='utf-8') as f:
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content = f.read()
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# 创建备份
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backup_file = f"{mock_file}.backup_simple_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
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with open(backup_file, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f"已创建备份文件: {backup_file}")
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# 为每个产业创建面试题数据
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def create_industry_questions(position_name, questions):
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"""为特定岗位创建面试题数组"""
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# 按section分组
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sections = {}
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for q in questions:
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section = q.get('section', '通用问题')
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if section not in sections:
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sections[section] = []
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sections[section].append(q)
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# 创建questions数组
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result = []
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for section_name, section_questions in sections.items():
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if section_questions:
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# 创建分组
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group = {
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"id": f"group_q{len(result)+1}",
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"question": f"# {section_name}" if section_name else "# 面试题",
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"subQuestions": []
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}
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for idx, q in enumerate(section_questions):
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sub_q = {
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"id": f"q{len(result)+1}_{idx+1}",
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"question": q["question"],
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"answer": q["answer"] if q["answer"] else "请根据实际情况回答。"
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}
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group["subQuestions"].append(sub_q)
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if group["subQuestions"]: # 只添加有内容的分组
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result.append(group)
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return result
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# 定义产业和岗位的映射关系
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industry_positions_map = {
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"UI设计": ["UI设计师"],
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"包装设计": ["包装设计师"],
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"插画设计": ["插画师"],
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"灯光": ["影视灯光"],
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"动画设计": ["动画师", "角色原画师", "分镜设计师"],
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"后期特效": ["特效设计师", "3D特效师", "特效合成师", "CG总监助理"],
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"剪辑": ["剪辑师", "影视剪辑", "短视频剪辑师"],
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"品牌设计": ["品牌视觉内容策划", "LOGO设计师", "品牌视觉传播策划管培生"],
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"平面设计": ["平面设计师", "AIGC设计师", "AI绘画师"],
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"三维设计": ["3D建模师", "渲染合成师", "材质灯光师", "游戏场景地编", "游戏场景生态设计师助理", "潮玩设计师"],
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"摄影/摄像": ["摄影师", "影视摄像", "摄影美术指导助理"],
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"室内设计": ["室内设计师", "美术总监助理"],
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"调色": ["调色师"],
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"新媒体运营": ["新媒体运营专员", "自媒体运营专员"],
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"音频处理": ["音效设计师", "音频编辑师", "混音师", "录音师"],
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"影视节目策划": ["导演", "文案策划"],
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"直播": ["社群运营", "直播助理", "直播运营", "直播专员"]
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}
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# 手动为每个产业更新questions
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print("\n开始更新面试题数据...")
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update_count = 0
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# 读取文件行
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lines = content.split('\n')
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new_lines = []
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i = 0
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while i < len(lines):
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line = lines[i]
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new_lines.append(line)
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# 检查是否是产业名称行
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for industry_name, position_names in industry_positions_map.items():
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if f'"name": "{industry_name}"' in line:
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# 找到产业，查找其questions字段
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j = i + 1
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while j < len(lines) and '"questions":' not in lines[j]:
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new_lines.append(lines[j])
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j += 1
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if j < len(lines) and '"questions":' in lines[j]:
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# 找到questions行
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new_lines.append(lines[j]) # 添加 "questions": [
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# 跳过旧的questions内容直到找到对应的结束 ]
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bracket_count = 1
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j += 1
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while j < len(lines) and bracket_count > 0:
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if '[' in lines[j]:
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bracket_count += lines[j].count('[') - lines[j].count(']')
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elif ']' in lines[j]:
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bracket_count -= lines[j].count(']')
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j += 1
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# 现在j指向 ] 的下一行
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# 插入新的面试题数据
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for position_name in position_names:
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if position_name in interview_questions_map:
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questions = interview_questions_map[position_name]
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if questions:
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questions_data = create_industry_questions(position_name, questions)
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# 生成JSON字符串（带缩进）
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questions_str = json.dumps(questions_data, ensure_ascii=False, indent=6)[1:-1] # 去掉外层的[]
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# 添加正确缩进
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indented_questions = '\n'.join([' ' + line for line in questions_str.split('\n')])
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new_lines.append(indented_questions)
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new_lines.append(' ]')
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update_count += 1
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print(f"✓ 已更新 {industry_name} 产业的面试题（{len(questions)} 个问题）")
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# 更新i到j的位置，跳过旧的questions内容
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i = j - 1
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break
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else:
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# 如果没有找到对应的面试题，保持原样
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continue
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break
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i += 1
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# 如果没有更新任何产业，使用原内容
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if update_count == 0:
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print("未能更新任何产业，保持原文件不变")
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else:
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# 写回文件
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print(f"\n正在写入更新后的内容...")
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new_content = '\n'.join(new_lines)
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with open(mock_file, 'w', encoding='utf-8') as f:
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f.write(new_content)
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print(f"\n更新完成!")
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print(f"成功更新: {update_count} 个产业的面试题")
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# 验证语法
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print("\n验证文件语法...")
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result = os.popen(f'node -c {mock_file} 2>&1').read()
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if result:
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print(f"❌ 语法错误: {result}")
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# 恢复备份
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print("正在恢复备份...")
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with open(backup_file, 'r', encoding='utf-8') as f:
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content = f.read()
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with open(mock_file, 'w', encoding='utf-8') as f:
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f.write(content)
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print("已恢复备份文件")
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else:
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print("✓ 语法验证通过")
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print("\n面试题更新成功！现在每个产业都有完整的面试题数据。") |