157 lines
5.5 KiB
Python
157 lines
5.5 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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from datetime import datetime
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def create_backup(file_path):
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"""创建备份文件"""
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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backup_path = f"{file_path}.backup_direct_{timestamp}"
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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with open(backup_path, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f"已创建备份: {backup_path}")
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return backup_path
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def get_chemical_questions():
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"""获取化工行业的面试题数据"""
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# 加载化工数据
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with open('网页未导入数据/化工产业/化工岗位简历.json', 'r', encoding='utf-8') as f:
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data = json.load(f)
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# 创建岗位群到面试题的映射
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questions_map = {}
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for item in data:
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group = item.get('简历岗位群', '')
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if group and group not in questions_map:
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# 为每个岗位群创建示例面试题
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questions_map[group] = [
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{
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"id": "q1",
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"question": f"请介绍一下你对{group}岗位的理解",
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"answer": "需要掌握相关专业知识和技能，确保工作安全高效。"
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},
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{
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"id": "q2",
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"question": f"在{group}工作中，你认为最重要的是什么？",
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"answer": "安全第一，质量优先，持续改进。"
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},
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{
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"id": "q3",
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"question": "遇到紧急情况你会如何处理？",
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"answer": "立即启动应急预案，确保人员安全，及时上报并处理。"
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}
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]
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# 特定岗位群的专业问题
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if "化工安全" in questions_map:
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questions_map["化工安全"] = [
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{
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"id": "q1",
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"question": "发现储罐泄漏应如何处理？",
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"answer": "立即隔离危险区，启动应急预案，关闭泄漏源，通报相关部门。"
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},
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{
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"id": "q2",
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"question": "如何进行危险源辨识？",
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"answer": "通过HAZOP分析、JSA作业安全分析等方法系统识别风险。"
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},
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{
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"id": "q3",
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"question": "化工安全管理的核心是什么？",
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"answer": "预防为主，综合治理，从源头控制风险。"
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}
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]
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if "精细化工" in questions_map:
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questions_map["精细化工"] = [
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{
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"id": "q1",
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"question": "精细化工与传统化工的区别？",
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"answer": "精细化工产品附加值高、批量小、品种多、技术含量高。"
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},
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{
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"id": "q2",
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"question": "如何控制产品质量？",
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"answer": "严格控制原料质量、工艺参数、过程监控和产品检验。"
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}
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]
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return questions_map
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def update_mock_file():
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"""直接更新mock文件的subQuestions"""
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mock_file = 'src/mocks/resumeInterviewMock.js'
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# 创建备份
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backup_path = create_backup(mock_file)
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# 获取面试题数据
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questions_map = get_chemical_questions()
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# 读取文件内容
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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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# 对每个岗位群进行替换
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for group_name, questions in questions_map.items():
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# 查找该岗位群的questions部分
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# 模式：从 "name": "岗位群名" 到 "subQuestions": []
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import re
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pattern = rf'("name":\s*"{re.escape(group_name)}".*?"subQuestions":\s*)\[\]'
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# 构建替换内容
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questions_json = json.dumps(questions, ensure_ascii=False, indent=10)
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# 调整缩进
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lines = questions_json.split('\n')
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formatted_lines = []
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for line in lines[1:-1]: # 跳过首尾的[]
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formatted_lines.append(' ' + line)
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formatted_json = '[\n' + '\n'.join(formatted_lines) + '\n ]'
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# 执行替换
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replacement = rf'\1{formatted_json}'
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new_content = re.sub(pattern, replacement, content, count=1, flags=re.DOTALL)
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if new_content != content:
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content = new_content
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print(f"✓ 已更新 {group_name} 的面试题")
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else:
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print(f"⚠ 未找到 {group_name} 的空subQuestions")
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# 保存文件
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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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# 验证语法
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import subprocess
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result = subprocess.run(['node', '-c', mock_file], capture_output=True, text=True)
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if result.returncode == 0:
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print("\n✓ 语法检查通过")
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print(f"✓ 成功更新了 {len(questions_map)} 个岗位群的面试题")
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return True
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else:
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print("\n✗ 语法检查失败:")
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print(result.stderr[:500])
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# 恢复备份
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with open(backup_path, 'r', encoding='utf-8') as f:
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backup_content = f.read()
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with open(mock_file, 'w', encoding='utf-8') as f:
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f.write(backup_content)
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print("已恢复备份文件")
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return False
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def main():
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"""主函数"""
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print("开始直接更新面试题数据...\n")
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if update_mock_file():
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print("\n✅ 面试题更新成功完成！")
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else:
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print("\n❌ 面试题更新失败")
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if __name__ == "__main__":
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main()
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