108 lines
4.1 KiB
Python
108 lines
4.1 KiB
Python
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#!/usr/bin/env python3
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import json
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import re
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# 读取化工岗位简历数据
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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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chemical_data = json.load(f)
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# 统计和收集所有岗位群的面试题
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job_group_questions = {}
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total_questions = 0
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positions_per_group = {}
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# 遍历所有岗位
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for position_data in chemical_data:
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position_name = position_data.get('positionName', '')
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job_group = position_data.get('jobGroup', '')
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# 初始化岗位群数据
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if job_group not in job_group_questions:
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job_group_questions[job_group] = []
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positions_per_group[job_group] = []
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positions_per_group[job_group].append(position_name)
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# 提取该岗位的面试题
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if 'interviewQuestions' in position_data:
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interview_content = position_data['interviewQuestions']
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# 解析面试题内容
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questions = []
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# 按换行分割，每两行构成一个问答对
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lines = [line.strip() for line in interview_content.split('\n') if line.strip()]
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for i in range(0, len(lines), 2):
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if i + 1 < len(lines):
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question = lines[i]
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answer = lines[i + 1]
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# 清理问题和答案文本
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question = re.sub(r'^问题\d+[:：]\s*', '', question)
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question = re.sub(r'^问[:：]\s*', '', question)
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question = re.sub(r'^\d+[、.]\s*', '', question)
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answer = re.sub(r'^答案[:：]\s*', '', answer)
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answer = re.sub(r'^答[:：]\s*', '', answer)
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answer = re.sub(r'^解答[:：]\s*', '', answer)
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if question and answer:
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questions.append({
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"question": question.strip(),
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"answer": answer.strip()
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})
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elif i < len(lines):
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# 如果只有一行，作为问题，答案使用通用答案
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question = lines[i]
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question = re.sub(r'^问题\d+[:：]\s*', '', question)
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question = re.sub(r'^\d+[、.]\s*', '', question)
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if question.strip():
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questions.append({
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"question": question.strip(),
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"answer": f"这是{position_name}岗位的重要考察点，需要根据个人经验和专业知识进行回答。"
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})
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# 添加到岗位群的问题列表
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for q in questions:
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# 检查是否已存在完全相同的问题
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is_duplicate = False
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for existing in job_group_questions[job_group]:
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if existing['question'] == q['question']:
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is_duplicate = True
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break
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if not is_duplicate and q['question'] and q['answer']:
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job_group_questions[job_group].append(q)
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total_questions += 1
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# 输出统计信息
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print(f"\n===== 化工岗位面试题统计 =====")
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print(f"总岗位数: {len(chemical_data)}")
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print(f"总岗位群数: {len(job_group_questions)}")
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print(f"总面试题数: {total_questions}")
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print(f"\n各岗位群面试题数量：")
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for job_group, questions in sorted(job_group_questions.items()):
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positions = positions_per_group[job_group]
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if len(positions) > 3:
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positions_str = ', '.join(positions[:3]) + f' 等{len(positions)}个岗位'
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else:
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positions_str = ', '.join(positions)
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print(f" {job_group}: {len(questions)} 题 (包含: {positions_str})")
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# 输出前几个岗位群的面试题示例
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print(f"\n===== 面试题示例 =====")
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for job_group in list(job_group_questions.keys())[:2]:
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print(f"\n【{job_group}】的前3道面试题：")
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for i, q in enumerate(job_group_questions[job_group][:3], 1):
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print(f" {i}. 问：{q['question'][:50]}...")
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print(f" 答：{q['answer'][:50]}...")
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# 保存面试题数据到JSON文件
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with open('all_interview_questions.json', 'w', encoding='utf-8') as f:
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json.dump(job_group_questions, f, ensure_ascii=False, indent=2)
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print(f"\n✅ 已保存所有面试题到 all_interview_questions.json")
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print(f"\n下一步：生成更新脚本...")
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