ALL-teach_sys/frontend_视觉设计/direct_update_questions.py

#!/usr/bin/env python3
import json
import os
from datetime import datetime

# 读取视觉设计岗位简历.json文件
json_file = '网页未导入数据/视觉设计产业/视觉设计岗位简历.json'
mock_file = 'src/mocks/resumeInterviewMock.js'

print("正在读取完整的面试题数据...")
with open(json_file, 'r', encoding='utf-8') as f:
    positions_data = json.load(f)

# 解析所有岗位的面试题
all_questions = {}
for position in positions_data:
    position_name = position.get("岗位名称", "")
    interview_content = position.get("面试题内容", "")
    if position_name and interview_content:
        questions = []
        lines = interview_content.split('\n')
        current_section = "专业能力类"  # 默认分类

        for line in lines:
            line = line.strip()
            # 识别大分类
            if line.startswith('# '):
                section_text = line[2:].strip()
                if '专业' in section_text or '能力' in section_text:
                    current_section = "专业能力类"
                elif '行为' in section_text or '经历' in section_text:
                    current_section = "行为经历类"
                elif '情景' in section_text or '应变' in section_text:
                    current_section = "情景应变类"
                else:
                    current_section = section_text

            # 识别问题
            elif line and line[0].isdigit() and '. 问题' in line:
                parts = line.split('问题：', 1)
                if len(parts) > 1:
                    question_text = parts[1].strip()
                else:
                    parts = line.split('问题:', 1)
                    if len(parts) > 1:
                        question_text = parts[1].strip()
                    else:
                        continue

                questions.append({
                    "question": question_text,
                    "section": current_section
                })

        all_questions[position_name] = questions
        if questions:
            print(f"解析 {position_name}：{len(questions)} 个问题")

# 创建备份
backup_file = f"{mock_file}.backup_direct_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
with open(mock_file, 'r', encoding='utf-8') as f:
    original_content = f.read()
with open(backup_file, 'w', encoding='utf-8') as f:
    f.write(original_content)
print(f"\n已创建备份：{backup_file}")

# 定义产业和岗位的映射
industry_map = {
    "UI设计": "UI设计师",
    "包装设计": "包装设计师",
    "插画设计": "插画师",
    "灯光": "影视灯光",
    "动画设计": "动画师",
    "后期特效": "特效设计师",
    "剪辑": "剪辑师",
    "品牌设计": "品牌视觉内容策划",
    "平面设计": "平面设计师",
    "三维设计": "3D建模师",
    "摄影/摄像": "摄影师",
    "室内设计": "室内设计师",
    "调色": "调色师",
    "新媒体运营": "新媒体运营专员",
    "音频处理": "音效设计师",
    "影视节目策划": "导演",
    "直播": "直播助理"
}

# 更新面试题
print("\n开始更新面试题...")
content = original_content
update_count = 0

for industry_name, position_name in industry_map.items():
    if position_name not in all_questions:
        print(f"✗ 未找到 {position_name} 的面试题数据")
        continue

    questions = all_questions[position_name]
    if not questions:
        continue

    # 按分类组织问题
    sections = {}
    for q in questions:
        section = q['section']
        if section not in sections:
            sections[section] = []
        sections[section].append(q['question'])

    # 构建新的questions数组
    new_questions = []
    group_id = 1
    for section_name, section_questions in sections.items():
        if section_questions:
            group = {
                "id": f"group_q{group_id}",
                "question": f"# {section_name}",
                "subQuestions": []
            }
            for idx, q_text in enumerate(section_questions, 1):
                group["subQuestions"].append({
                    "id": f"q{group_id}_{idx}",
                    "question": q_text,
                    "answer": "请根据您的实际经验和项目情况，结合专业知识进行回答。"
                })
            new_questions.append(group)
            group_id += 1

    # 生成JSON字符串
    questions_json = json.dumps(new_questions, ensure_ascii=False, indent=6)

    # 查找并替换
    # 搜索产业名称
    search_str = f'"name": "{industry_name}"'
    if search_str in content:
        # 找到产业位置
        start_idx = content.find(search_str)

        # 找到对应的questions字段
        questions_start = content.find('"questions":', start_idx)
        if questions_start > 0 and questions_start < start_idx + 2000:  # 确保在同一产业内
            # 找到questions数组的开始 [
            array_start = content.find('[', questions_start)
            if array_start > 0:
                # 找到对应的结束 ]
                bracket_count = 1
                idx = array_start + 1
                while idx < len(content) and bracket_count > 0:
                    if content[idx] == '[':
                        bracket_count += 1
                    elif content[idx] == ']':
                        bracket_count -= 1
                    idx += 1

                if bracket_count == 0:
                    # 替换questions内容
                    content = content[:array_start] + questions_json + content[idx-1:]
                    update_count += 1
                    print(f"✓ 已更新 {industry_name} ({len(questions)} 个问题)")

# 写回文件
if update_count > 0:
    print(f"\n正在写入文件...")
    with open(mock_file, 'w', encoding='utf-8') as f:
        f.write(content)

    # 验证语法
    print("验证文件语法...")
    result = os.popen(f'node -c {mock_file} 2>&1').read()
    if result:
        print(f"❌ 语法错误：{result}")
        # 恢复备份
        with open(backup_file, 'r', encoding='utf-8') as f:
            content = f.read()
        with open(mock_file, 'w', encoding='utf-8') as f:
            f.write(content)
        print("已恢复备份")
    else:
        print("✓ 语法验证通过")
        print(f"\n成功更新 {update_count} 个产业的面试题！")
else:
    print("\n未更新任何产业")