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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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import json
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import os
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import re
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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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def load_visual_design_data():
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"""加载视觉设计岗位简历数据"""
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with open('网页未导入数据/视觉设计产业/视觉设计岗位简历.json', 'r', encoding='utf-8') as f:
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return json.load(f)
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print("正在读取完整的面试题数据...")
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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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def extract_first_5_questions(content):
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"""从面试题内容中提取前5个问题和答案"""
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questions = []
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# 创建岗位名称到面试题的映射
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interview_questions_map = {}
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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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# 解析markdown格式的面试题
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questions = []
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lines = interview_content.split('\n')
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current_section = ""
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current_question = None
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# 提取所有问题
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pattern = r'(\d+)\.\s*问题[：:]?\s*(.*?)(?:\n\s*)?(?:参考回答[：:]?)(.*?)(?=\d+\.\s*问题|$)'
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matches = re.findall(pattern, content, re.DOTALL)
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for line in lines:
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line = line.strip()
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if line.startswith('# '):
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# 新的大分类
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current_section = line[2:].strip()
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elif line and line[0].isdigit() and '. 问题' in line:
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# 保存上一个问题
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if current_question:
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questions.append(current_question)
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for i, match in enumerate(matches[:5], 1): # 只取前5个
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q_num = match[0]
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question_text = match[1].strip()
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answer_text = match[2].strip()
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# 提取问题文本
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parts = line.split('问题：', 1)
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if len(parts) > 1:
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question_text = parts[1].strip()
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else:
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parts = line.split('问题:', 1)
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if len(parts) > 1:
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question_text = parts[1].strip()
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else:
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question_text = line
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questions.append({
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"num": i,
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"question": question_text,
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"answer": answer_text
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})
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current_question = {
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"question": question_text,
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"answer": "",
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"section": current_section
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}
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elif line.startswith('答案：') or line.startswith('答案:'):
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if current_question:
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answer = line.replace('答案：', '').replace('答案:', '').strip()
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current_question["answer"] = answer
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elif current_question and line and not line.startswith('#') and not (line[0].isdigit() and '. 问题' in line):
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# 继续添加到答案中（多行答案）
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if current_question["answer"] and not line.startswith('---'):
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current_question["answer"] += " " + line
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return questions
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# 添加最后一个问题
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if current_question:
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questions.append(current_question)
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def main():
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print("=== 简单更新面试题内容 ===\n")
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interview_questions_map[position_name] = questions
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if questions:
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print(f"解析 {position_name} 的面试题，共 {len(questions)} 个问题")
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# 创建备份
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timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
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backup_name = f'src/mocks/resumeInterviewMock.js.backup_{timestamp}_simple'
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print(f"\n总共找到 {len(interview_questions_map)} 个岗位的面试题")
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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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# 读取resumeInterviewMock.js文件
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print("\n正在读取 resumeInterviewMock.js...")
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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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with open(backup_name, 'w', encoding='utf-8') as f:
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f.write(mock_content)
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print(f"✓ 已创建备份: {backup_name}\n")
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# 创建备份
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backup_file = f"{mock_file}.backup_simple_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
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with open(backup_file, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f"已创建备份文件: {backup_file}")
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# 加载视觉设计数据
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visual_data = load_visual_design_data()
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# 为每个产业创建面试题数据
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def create_industry_questions(position_name, questions):
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"""为特定岗位创建面试题数组"""
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# 按section分组
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sections = {}
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for q in questions:
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section = q.get('section', '通用问题')
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if section not in sections:
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sections[section] = []
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sections[section].append(q)
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# 岗位映射
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position_map = {
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"UI设计师": "UI设计",
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"包装设计师": "包装设计",
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"插画师": "插画设计",
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"影视灯光": "灯光",
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"动画师": "动画设计",
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"平面设计师": "平面设计",
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"品牌视觉内容策划": "品牌设计",
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"CG总监助理": "三维设计",
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"特效设计师": "后期特效",
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"剪辑师": "剪辑",
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"调色师": "调色",
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"录音师": "音频处理",
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"直播专员": "直播",
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"新媒体运营专员": "新媒体运营",
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"文案策划": "影视节目策划",
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"室内设计师": "室内设计"
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}
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# 创建questions数组
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result = []
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updated_count = 0
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for section_name, section_questions in sections.items():
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if section_questions:
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# 创建分组
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group = {
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"id": f"group_q{len(result)+1}",
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"question": f"# {section_name}" if section_name else "# 面试题",
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"subQuestions": []
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}
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# 对每个岗位进行更新
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for item in visual_data:
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position_name = item.get('岗位名称')
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interview_content = item.get('面试题内容')
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for idx, q in enumerate(section_questions):
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sub_q = {
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"id": f"q{len(result)+1}_{idx+1}",
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"question": q["question"],
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"answer": q["answer"] if q["answer"] else "请根据实际情况回答。"
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}
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group["subQuestions"].append(sub_q)
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if not position_name or not interview_content:
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continue
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if group["subQuestions"]: # 只添加有内容的分组
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result.append(group)
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if position_name not in position_map:
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continue
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return result
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industry_name = position_map[position_name]
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questions = extract_first_5_questions(interview_content)
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# 定义产业和岗位的映射关系
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industry_positions_map = {
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"UI设计": ["UI设计师"],
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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", "角色原画师", "分镜设计师"],
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"后期特效": ["特效设计师", "3D特效师", "特效合成师", "CG总监助理"],
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"剪辑": ["剪辑师", "影视剪辑", "短视频剪辑师"],
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"品牌设计": ["品牌视觉内容策划", "LOGO设计师", "品牌视觉传播策划管培生"],
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"平面设计": ["平面设计师", "AIGC设计师", "AI绘画师"],
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"三维设计": ["3D建模师", "渲染合成师", "材质灯光师", "游戏场景地编", "游戏场景生态设计师助理", "潮玩设计师"],
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"摄影/摄像": ["摄影师", "影视摄像", "摄影美术指导助理"],
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"室内设计": ["室内设计师", "美术总监助理"],
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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", "自媒体运营专员"],
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"音频处理": ["音效设计师", "音频编辑师", "混音师", "录音师"],
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"影视节目策划": ["导演", "文案策划"],
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"直播": ["社群运营", "直播助理", "直播运营", "直播专员"]
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}
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if not questions:
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continue
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# 手动为每个产业更新questions
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print("\n开始更新面试题数据...")
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update_count = 0
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print(f"处理 {industry_name} ({position_name}):")
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# 读取文件行
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lines = content.split('\n')
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new_lines = []
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i = 0
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# 逐个替换前5个问题的内容
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for q in questions:
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q_id = f"q1_{q['num']}"
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while i < len(lines):
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line = lines[i]
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new_lines.append(line)
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# 转义特殊字符
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question_escaped = q['question'].replace('\\', '\\\\').replace('"', '\\"')
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answer_escaped = q['answer'].replace('\\', '\\\\').replace('"', '\\"')
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# 检查是否是产业名称行
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for industry_name, position_names in industry_positions_map.items():
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if f'"name": "{industry_name}"' in line:
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# 找到产业，查找其questions字段
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j = i + 1
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while j < len(lines) and '"questions":' not in lines[j]:
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new_lines.append(lines[j])
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j += 1
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# 查找并替换该问题
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pattern = rf'("id":\s*"{q_id}".*?"question":\s*)"[^"]*"(.*?"answer":\s*)"[^"]*"'
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replacement = rf'\1"{question_escaped}"\2"{answer_escaped}"'
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if j < len(lines) and '"questions":' in lines[j]:
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# 找到questions行
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new_lines.append(lines[j]) # 添加 "questions": [
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new_content = re.sub(pattern, replacement, mock_content, count=1, flags=re.DOTALL)
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# 跳过旧的questions内容直到找到对应的结束 ]
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bracket_count = 1
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j += 1
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while j < len(lines) and bracket_count > 0:
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if '[' in lines[j]:
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bracket_count += lines[j].count('[') - lines[j].count(']')
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elif ']' in lines[j]:
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bracket_count -= lines[j].count(']')
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j += 1
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if new_content != mock_content:
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mock_content = new_content
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print(f" ✓ 更新问题 {q_id}")
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else:
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print(f" ✗ 未能更新问题 {q_id}")
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# 现在j指向 ] 的下一行
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# 插入新的面试题数据
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for position_name in position_names:
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if position_name in interview_questions_map:
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questions = interview_questions_map[position_name]
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if questions:
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questions_data = create_industry_questions(position_name, questions)
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# 生成JSON字符串（带缩进）
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questions_str = json.dumps(questions_data, ensure_ascii=False, indent=6)[1:-1] # 去掉外层的[]
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# 添加正确缩进
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indented_questions = '\n'.join([' ' + line for line in questions_str.split('\n')])
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new_lines.append(indented_questions)
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new_lines.append(' ]')
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update_count += 1
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print(f"✓ 已更新 {industry_name} 产业的面试题（{len(questions)} 个问题）")
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# 更新i到j的位置，跳过旧的questions内容
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i = j - 1
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break
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else:
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# 如果没有找到对应的面试题，保持原样
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continue
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break
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i += 1
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updated_count += 1
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# 如果没有更新任何产业，使用原内容
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if update_count == 0:
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print("未能更新任何产业，保持原文件不变")
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else:
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# 写回文件
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print(f"\n正在写入更新后的内容...")
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new_content = '\n'.join(new_lines)
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with open(mock_file, 'w', encoding='utf-8') as f:
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f.write(new_content)
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# 保存文件
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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(f"\n更新完成!")
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print(f"成功更新: {update_count} 个产业的面试题")
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print(f"\n✅ 更新完成！处理了{updated_count}个岗位")
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# 验证语法
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print("\n验证文件语法...")
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result = os.popen(f'node -c {mock_file} 2>&1').read()
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if result:
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print(f"❌ 语法错误: {result}")
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# 恢复备份
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print("正在恢复备份...")
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with open(backup_file, 'r', encoding='utf-8') as f:
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content = f.read()
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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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print("已恢复备份文件")
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else:
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print("✓ 语法验证通过")
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print("\n面试题更新成功！现在每个产业都有完整的面试题数据。")
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import subprocess
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try:
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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("✅ 文件语法验证通过")
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else:
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print(f"❌ 语法错误:\n{result.stderr}")
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print("\n恢复备份...")
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with open(backup_name, 'r', encoding='utf-8') as f:
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backup_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(backup_content)
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print("已恢复备份")
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except Exception as e:
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print(f"⚠️ 无法验证语法: {str(e)}")
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if __name__ == '__main__':
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main()
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