194 lines
7.2 KiB
Python
194 lines
7.2 KiB
Python
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#!/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("正在读取所有岗位的完整面试题内容（包含答案）...")
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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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# 提取所有岗位的面试题（包含答案）
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all_questions_with_answers = {}
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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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questions_with_answers = []
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lines = interview_content.split('\n')
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current_question = None
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current_answer = ''
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collecting_answer = False
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for line in lines:
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line_stripped = line.strip()
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# 检测问题行
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if line_stripped and line_stripped[0].isdigit() and '. 问题' in line_stripped:
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# 保存上一个问题
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if current_question:
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questions_with_answers.append({
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'question': current_question,
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'answer': current_answer.strip() if current_answer.strip() else "请根据您的实际经验和项目情况，结合专业知识进行回答。"
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})
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# 提取新问题
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parts = line_stripped.split('问题：', 1)
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if len(parts) > 1:
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current_question = parts[1].strip()
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else:
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parts = line_stripped.split('问题:', 1)
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if len(parts) > 1:
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current_question = parts[1].strip()
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else:
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current_question = line_stripped
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current_answer = ''
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collecting_answer = False
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# 检测答案开始
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elif '参考回答：' in line or '参考答案：' in line or '答案：' in line:
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collecting_answer = True
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# 如果答案在同一行
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if '：' in line:
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answer_part = line.split('：', 1)[1].strip()
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if answer_part:
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current_answer = answer_part
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# 收集答案内容
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elif collecting_answer and line.strip():
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# 检查是否是新问题或新章节
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if (line_stripped and line_stripped[0].isdigit() and '. 问题' in line_stripped) or line_stripped.startswith('#'):
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collecting_answer = False
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else:
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if current_answer:
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current_answer += ' '
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current_answer += line.strip()
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# 保存最后一个问题
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if current_question:
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questions_with_answers.append({
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'question': current_question,
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'answer': current_answer.strip() if current_answer.strip() else "请根据您的实际经验和项目情况，结合专业知识进行回答。"
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})
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all_questions_with_answers[position_name] = questions_with_answers
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if questions_with_answers:
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print(f" {position_name}: {len(questions_with_answers)} 个问题（含答案）")
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print(f"\n共解析 {len(all_questions_with_answers)} 个岗位的面试题")
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# 创建备份
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backup_file = f"{mock_file}.backup_full_answers_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
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with open(mock_file, 'r', encoding='utf-8') as f:
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original_content = f.read()
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with open(backup_file, 'w', encoding='utf-8') as f:
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f.write(original_content)
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print(f"\n已创建备份：{backup_file}")
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# 生成UI设计师的完整面试题数据
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if "UI设计师" in all_questions_with_answers:
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ui_questions = all_questions_with_answers["UI设计师"]
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# 构建单卡片格式的面试题
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new_questions = [
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{
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"id": "group_q1",
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"question": "# UI设计面试题",
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"subQuestions": []
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}
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]
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for idx, qa in enumerate(ui_questions, 1):
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# 清理答案文本，保持可读性
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answer_text = qa['answer']
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# 限制答案长度，避免太长
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if len(answer_text) > 500:
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answer_text = answer_text[:500] + "..."
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new_questions[0]["subQuestions"].append({
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"id": f"q1_{idx}",
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"question": qa['question'],
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"answer": answer_text
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})
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# 生成JSON字符串
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questions_json = json.dumps(new_questions, ensure_ascii=False, indent=6)
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# 保存UI设计的更新数据
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with open('ui_questions_with_answers.json', 'w', encoding='utf-8') as f:
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f.write(questions_json)
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print(f"\nUI设计师的面试题已准备就绪")
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print(f"包含 {len(ui_questions)} 个问题，每个都有完整答案")
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print("数据已保存到 ui_questions_with_answers.json")
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# 显示前两个问题作为示例
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print("\n示例（前2个问题）：")
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for i in range(min(2, len(ui_questions))):
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print(f"\n问题 {i+1}: {ui_questions[i]['question']}")
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answer_preview = ui_questions[i]['answer'][:150] + "..." if len(ui_questions[i]['answer']) > 150 else ui_questions[i]['answer']
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print(f"答案: {answer_preview}")
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# 为其他产业也生成完整数据
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industry_map = {
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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",
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"后期特效": "特效设计师",
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"剪辑": "剪辑师",
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"品牌设计": "品牌视觉内容策划",
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"平面设计": "平面设计师",
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"三维设计": "3D建模师",
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"摄影/摄像": "摄影师",
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"室内设计": "室内设计师",
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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",
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"音频处理": "音效设计师",
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"影视节目策划": "导演",
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"直播": "直播助理"
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}
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all_updates = []
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for industry_name, position_name in industry_map.items():
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if position_name in all_questions_with_answers:
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questions = all_questions_with_answers[position_name]
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if questions:
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# 构建单卡片格式
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industry_questions = [
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{
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"id": "group_q1",
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"question": f"# {industry_name}面试题",
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"subQuestions": []
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}
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]
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for idx, qa in enumerate(questions, 1):
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answer_text = qa['answer']
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if len(answer_text) > 500:
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answer_text = answer_text[:500] + "..."
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industry_questions[0]["subQuestions"].append({
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"id": f"q1_{idx}",
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"question": qa['question'],
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"answer": answer_text
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})
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all_updates.append({
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'industry': industry_name,
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'questions': industry_questions,
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'count': len(questions)
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})
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# 保存所有更新数据
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with open('all_industries_with_answers.json', 'w', encoding='utf-8') as f:
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json.dump(all_updates, f, ensure_ascii=False, indent=2)
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print(f"\n所有 {len(all_updates)} 个产业的完整面试题数据已准备就绪")
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print("数据已保存到 all_industries_with_answers.json")
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