更新12个教务系统并优化项目大小
主要更新： - 更新所有12个产业的教务系统数据和功能 - 删除所有 node_modules 文件夹（节省3.7GB） - 删除所有 .yoyo 缓存文件夹（节省1.2GB） - 删除所有 dist 构建文件（节省55MB） 项目优化： - 项目大小从 8.1GB 减少到 3.2GB（节省60%空间） - 保留完整的源代码和配置文件 - .gitignore 已配置，防止再次提交大文件 启动脚本： - start-industry.sh/bat/ps1 脚本会自动检测并安装依赖 - 首次启动时自动运行 npm install - 支持单个或批量启动产业系统 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
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KQL
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frontend_智能制造/update_all_interviews_direct.py
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frontend_智能制造/update_all_interviews_direct.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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直接更新所有岗位群的面试题
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使用更精确的文本处理方法
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"""
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import json
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import re
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from datetime import datetime
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print("=== 直接更新所有岗位群面试题 ===\n")
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# 1. 读取源数据
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print("1. 读取智能制造岗位简历.json...")
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with open('网页未导入数据/智能制造产业/智能制造岗位简历.json', 'r', encoding='utf-8') as f:
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source_data = json.load(f)
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# 2. 解析所有面试题（只保留唯一的岗位群）
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print("2. 解析面试题数据...")
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interview_questions_map = {}
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for item in source_data:
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job_group = 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 not job_group or not interview_content or job_group in interview_questions_map:
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continue # 跳过已处理的岗位群
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# 收集所有问题
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all_questions = []
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lines = interview_content.split('\n')
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i = 0
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while i < len(lines):
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line = lines[i].strip()
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# 匹配问题编号
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question_match = re.match(r'^(\d+)[\.、]\s*(.+)', line)
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if question_match:
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question_text = question_match.group(2).strip()
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# 查找答案
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answer = ""
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i += 1
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while i < len(lines):
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next_line = lines[i].strip()
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if re.match(r'^\d+[\.、]\s*', next_line) or next_line.startswith('#'):
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i -= 1
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break
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if next_line and (next_line.startswith('答案') or next_line.startswith('示例答案')):
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answer = re.sub(r'^(答案|示例答案)[：:]?\s*', '', next_line).strip()
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if not answer:
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i += 1
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if i < len(lines):
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answer = lines[i].strip()
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break
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elif next_line and not answer:
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answer = next_line
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break
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i += 1
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if not answer:
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answer = "请根据实际情况回答"
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all_questions.append({
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'question': question_text,
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'answer': answer
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})
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i += 1
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if all_questions:
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interview_questions_map[job_group] = all_questions
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print(f" - {job_group}: {len(all_questions)} 道题")
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print(f"\n共解析 {len(interview_questions_map)} 个岗位群")
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# 3. 读取当前mock文件
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print("\n3. 读取当前mock文件...")
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with open('src/mocks/resumeInterviewMock.js', 'r', encoding='utf-8') as f:
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mock_content = f.read()
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# 4. 备份
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backup_time = datetime.now().strftime('%Y%m%d_%H%M%S')
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backup_file = f'src/mocks/resumeInterviewMock.js.backup_direct_{backup_time}'
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print(f"4. 创建备份: {backup_file}")
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with open(backup_file, 'w', encoding='utf-8') as f:
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f.write(mock_content)
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# 5. 逐个岗位群更新
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print("\n5. 开始更新各岗位群...")
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updated_count = 0
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for job_group, questions in interview_questions_map.items():
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print(f"\n处理 {job_group}...")
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# 构建新的questions数组
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sub_questions_list = []
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for idx, q in enumerate(questions, 1):
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question_text = q['question'].replace('\\', '\\\\').replace('"', '\\"')
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answer_text = q['answer'].replace('\\', '\\\\').replace('"', '\\"').replace('\n', ' ')
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sub_questions_list.append(f'''{{
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"id": "q1_{idx}",
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"question": "{question_text}",
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"answer": "{answer_text}"
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}}''')
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# 构建完整的questions结构
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new_questions_str = f'''[
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{{
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"id": "group_q1",
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"question": "# {job_group}岗位面试题",
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"subQuestions": [
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{','.join(sub_questions_list)}
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]
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}}
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]'''
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# 使用更精确的查找和替换
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# 先找到岗位群的位置
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job_group_pattern = f'"name": "{job_group}"'
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job_group_pos = mock_content.find(job_group_pattern)
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if job_group_pos == -1:
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print(f" ⚠️ 未找到 {job_group}")
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continue
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# 从该位置开始查找 questions 字段
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search_start = job_group_pos
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questions_start = mock_content.find('"questions":', search_start)
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if questions_start == -1 or questions_start - job_group_pos > 5000: # 限制搜索范围
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print(f" ⚠️ 未找到 {job_group} 的questions字段")
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continue
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# 找到 questions 数组的开始 [
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array_start = mock_content.find('[', questions_start)
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if array_start == -1:
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print(f" ⚠️ 未找到 {job_group} 的questions数组开始")
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continue
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# 找到对应的结束 ]
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bracket_count = 1
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pos = array_start + 1
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array_end = -1
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while pos < len(mock_content) and bracket_count > 0:
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if mock_content[pos] == '[':
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bracket_count += 1
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elif mock_content[pos] == ']':
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bracket_count -= 1
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if bracket_count == 0:
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array_end = pos
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break
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pos += 1
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if array_end == -1:
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print(f" ⚠️ 未找到 {job_group} 的questions数组结束")
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continue
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# 替换questions数组
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before = mock_content[:array_start]
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after = mock_content[array_end + 1:]
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mock_content = before + new_questions_str + after
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print(f" ✅ {job_group} 已更新为 {len(questions)} 道题")
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updated_count += 1
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# 6. 保存文件
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print(f"\n6. 保存更新后的文件...")
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print(f" 共更新 {updated_count} 个岗位群")
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with open('src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
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f.write(mock_content)
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# 7. 验证语法
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print("\n7. 验证语法...")
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import subprocess
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result = subprocess.run(['node', '-c', 'src/mocks/resumeInterviewMock.js'],
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capture_output=True, text=True)
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if result.returncode == 0:
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print("✅ 语法检查通过！")
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print(f"\n=== 更新完成 ===")
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print(f"成功更新 {updated_count}/{len(interview_questions_map)} 个岗位群")
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# 统计最终结果
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print("\n=== 最终统计 ===")
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with open('src/mocks/resumeInterviewMock.js', 'r', encoding='utf-8') as f:
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final_content = f.read()
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for group in interview_questions_map.keys():
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# 查找该岗位群的questions
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group_pos = final_content.find(f'"name": "{group}"')
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if group_pos != -1:
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# 从该位置向后查找questions
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questions_pos = final_content.find('"questions":', group_pos)
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if questions_pos != -1 and questions_pos - group_pos < 5000:
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# 统计该区域的题目数量
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search_end = questions_pos + 10000 # 限制搜索范围
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section = final_content[questions_pos:min(search_end, len(final_content))]
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count = len(re.findall(r'"id": "q1_\d+"', section))
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expected = len(interview_questions_map[group])
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status = "✅" if count == expected else f"⚠️ ({count}/{expected})"
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print(f" {status} {group}: {count} 道题")
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else:
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print(f" ❌ {group}: 未找到questions")
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else:
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print(f" ❌ {group}: 未找到岗位群")
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else:
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print("❌ 语法错误：")
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print(result.stderr)
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print("\n正在恢复备份...")
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with open(backup_file, 'r', encoding='utf-8') as f:
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mock_content = f.read()
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with open('src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
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f.write(mock_content)
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print("已恢复到备份版本")
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