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>
70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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生成缺失的面试题数据
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"""
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import json
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import re
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# 读取面试题数据
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with open('interview_questions_data.json', 'r', encoding='utf-8') as f:
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interview_data = json.load(f)
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# 需要添加的岗位群
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empty_job_groups = [
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"房地产经纪",
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"工程采购",
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"工程造价与资料管理",
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"建筑安装工程",
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"建筑工程检测",
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"建筑工程设计",
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"建筑施工与施工管理"
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]
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for job_group in empty_job_groups:
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if job_group not in interview_data:
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print(f"警告: 未找到 {job_group}")
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continue
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questions = interview_data[job_group]
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if not questions:
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print(f"警告: {job_group} 没有数据")
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continue
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# 限制题目数量
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max_questions = min(8, len(questions))
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selected_questions = []
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for q in questions[:max_questions]:
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# 清理问题文本
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clean_q = q.copy()
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clean_q["question"] = re.sub(r'^(选择题|填空题)[：:]', '', q["question"]).strip()
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# 修复选择题答案
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if q["answer"] and len(q["answer"]) == 1 and q["answer"] in 'ABCD':
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# 根据问题内容推断答案
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if "不是" in q["question"] or "不属于" in q["question"]:
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if job_group == "房地产经纪":
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clean_q["answer"] = "提供建筑施工监理服务"
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elif job_group == "工程采购":
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clean_q["answer"] = "提高采购人员个人收入"
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else:
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clean_q["answer"] = "请参考题目选项中与职责不符的选项"
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else:
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clean_q["answer"] = "请参考题目选项中的正确答案"
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else:
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clean_q["answer"] = q["answer"]
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selected_questions.append(clean_q)
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# 构建questions对象
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questions_obj = [{
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"id": f"group_{job_group}_q1",
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"question": f"{job_group}面试题",
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"subQuestions": selected_questions
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}]
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# 输出JSON
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print(f"\n// {job_group}")
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print(f'"questions": {json.dumps(questions_obj, ensure_ascii=False, indent=4)}') |