a7242f0c69
- 包含4个产业方向的前端项目：智能开发、智能制造、大健康、财经商贸 - 已清理node_modules、.yoyo等大文件，项目大小从2.6GB优化至631MB - 配置完善的.gitignore文件 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
251 lines
9.1 KiB
Python
251 lines
9.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import json
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import re
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def extract_all_questions_from_content(content):
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"""从内容中提取所有面试题"""
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all_questions = []
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# 删除"判断题："等前缀
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content = re.sub(r'判断题[：:]?\s*', '', content)
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# 先按大类分割（# 一、二、三等）
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category_pattern = r'# ([一二三四五六七八九十]+、[^\n]+)'
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categories = re.split(category_pattern, content)
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if len(categories) > 1:
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# 有分类的情况
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for i in range(1, len(categories), 2):
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if i+1 >= len(categories):
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break
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category_title = categories[i].strip()
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category_content = categories[i+1]
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# 从该分类中提取所有问题
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questions = extract_questions_from_text(category_content)
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if questions:
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all_questions.append({
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"category": category_title,
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"questions": questions
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})
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else:
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# 没有分类，直接提取所有问题
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questions = extract_questions_from_text(content)
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if questions:
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all_questions.append({
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"category": "综合面试题",
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"questions": questions
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})
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return all_questions
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def extract_questions_from_text(text):
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"""从文本中提取问题和答案"""
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questions = []
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question_id = 1
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# 分割文本为行
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lines = text.split('\n')
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current_question = None
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current_answer = []
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in_answer_section = False
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for i, line in enumerate(lines):
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line = line.strip()
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# 检查是否是问题行（数字开头）
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question_match = re.match(r'^(\d+)\.\s*(.+)$', line)
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if question_match:
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# 先保存上一个问题
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if current_question and current_answer:
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answer_text = ' '.join(current_answer).strip()
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# 清理答案文本
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answer_text = re.sub(r'^(示例)?答案[：:]?\s*', '', answer_text)
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answer_text = re.sub(r'\s+', ' ', answer_text)
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if answer_text:
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questions.append({
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"id": f"q{question_id}",
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"question": current_question,
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"answer": answer_text
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})
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question_id += 1
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# 开始新问题
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current_question = question_match.group(2).strip()
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current_answer = []
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in_answer_section = False
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# 检查是否进入答案部分
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elif line and ('示例答案' in line or '答案：' in line or '答案:' in line):
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in_answer_section = True
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# 答案可能在同一行
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answer_on_same_line = re.sub(r'^.*(示例)?答案[：:]?\s*', '', line).strip()
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if answer_on_same_line:
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current_answer.append(answer_on_same_line)
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# 收集答案内容
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elif in_answer_section and line:
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# 检查是否是下一个问题或分类
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if not re.match(r'^(\d+)\.', line) and not line.startswith('#'):
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current_answer.append(line)
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# 空行可能表示答案结束
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elif not line and in_answer_section:
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in_answer_section = False
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# 保存最后一个问题
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if current_question and current_answer:
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answer_text = ' '.join(current_answer).strip()
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answer_text = re.sub(r'^(示例)?答案[：:]?\s*', '', answer_text)
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answer_text = re.sub(r'\s+', ' ', answer_text)
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if answer_text:
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questions.append({
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"id": f"q{question_id}",
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"question": current_question,
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"answer": answer_text
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})
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# 如果没有找到答案，尝试另一种模式
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if not questions:
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# 使用正则表达式匹配问题和答案
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pattern = r'(\d+)\.\s*([^\n]+)\s*\n\s*(?:示例)?答案[：:]?\s*\n\s*([^\n]+(?:\n(?!\d+\.|#)[^\n]*)*)'
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matches = re.findall(pattern, text, re.MULTILINE)
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question_id = 1
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for match in matches:
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question_text = match[1].strip()
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answer_text = match[2].strip()
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answer_text = re.sub(r'\s+', ' ', answer_text)
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if question_text and answer_text:
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questions.append({
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"id": f"q{question_id}",
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"question": question_text,
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"answer": answer_text
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})
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question_id += 1
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return questions
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def main():
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# 读取大健康岗位简历数据
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/网页未导入数据/大健康产业/大健康岗位简历.json', 'r', encoding='utf-8') as f:
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health_data = json.load(f)
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# 读取Mock文件
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/src/mocks/resumeInterviewMock.js', 'r', encoding='utf-8') as f:
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content = f.read()
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# 收集每个岗位群的所有面试题
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industry_all_questions = {}
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for item in health_data:
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industry = item.get('简历岗位群', '')
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interview_content = item.get('面试题内容', '')
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if industry and interview_content:
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if industry not in industry_all_questions:
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industry_all_questions[industry] = []
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# 提取该岗位的所有问题
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categories = extract_all_questions_from_content(interview_content)
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# 合并到该岗位群的问题列表中
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for cat in categories:
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# 检查是否已有该分类
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existing_cat = None
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for existing in industry_all_questions[industry]:
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if existing['category'] == cat['category']:
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existing_cat = existing
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break
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if existing_cat:
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# 合并问题，避免重复
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existing_questions = {q['question'] for q in existing_cat['questions']}
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for q in cat['questions']:
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if q['question'] not in existing_questions:
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existing_cat['questions'].append(q)
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else:
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# 添加新分类
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industry_all_questions[industry].append(cat)
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# 转换为前端期望的格式并更新Mock文件
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industry_mapping = {
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'健康管理': 'health_1',
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'健康检查': 'health_2',
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'康复治疗': 'health_3',
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'慢性病管理': 'health_4',
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'轻医美': 'health_5',
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'心理健康': 'health_6',
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'社群运营': 'health_7',
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'药品供应链管理': 'health_8',
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'药品生产': 'health_9',
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'药品质量检测': 'health_10',
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'药物研发': 'health_11'
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}
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updates = 0
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for orig_name, industry_id in industry_mapping.items():
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if orig_name in industry_all_questions:
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categories = industry_all_questions[orig_name]
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# 转换为questions数组
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questions_array = []
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cat_id = 1
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total_questions = 0
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for cat in categories:
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if cat['questions']:
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# 重新编号问题ID
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renumbered_questions = []
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for i, q in enumerate(cat['questions'], 1):
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renumbered_questions.append({
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"id": f"q{total_questions + i}",
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"question": q['question'],
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"answer": q['answer']
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})
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total_questions += len(renumbered_questions)
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questions_array.append({
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"id": f"group_q{cat_id}",
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"question": cat['category'],
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"subQuestions": renumbered_questions
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})
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cat_id += 1
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if questions_array:
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print(f"✓ {orig_name} ({industry_id}): {len(questions_array)} 个分类，共 {total_questions} 个面试题")
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# 生成JSON字符串
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questions_json = json.dumps(questions_array, ensure_ascii=False, indent=2)
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# 删除旧的questions字段
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pattern1 = rf'("id":\s*"{industry_id}"[^{{]*?"positions":\s*\[[^\]]*?\]),\s*"questions":\s*\[[^\]]*?\](\s*\}})'
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replacement1 = rf'\1\2'
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content = re.sub(pattern1, replacement1, content, flags=re.DOTALL)
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# 添加新的questions字段
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pattern2 = rf'("id":\s*"{industry_id}"[^{{]*?"positions":\s*\[[^\]]*?\])(\s*\}})'
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replacement2 = rf'\1,\n "questions": {questions_json}\2'
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new_content, count = re.subn(pattern2, replacement2, content, flags=re.DOTALL)
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if count > 0:
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content = new_content
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updates += 1
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# 写回文件
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with open('/Users/apple/Documents/cursor/教务系统/frontend_大健康/src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
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f.write(content)
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print(f"\n✅ 完成！更新了 {updates} 个岗位群的完整面试题数据")
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if __name__ == "__main__":
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main() |