Files
ALL-teach_sys/frontend_能源/replace_industries_data.py
KQL cd2e307402 初始化12个产业教务系统项目
主要内容:
- 包含12个产业的完整教务系统前端代码
- 智能启动脚本 (start-industry.sh)
- 可视化产业导航页面 (index.html)
- 项目文档 (README.md)

优化内容:
- 删除所有node_modules和.yoyo文件夹,从7.5GB减少到2.7GB
- 添加.gitignore文件避免上传不必要的文件
- 自动依赖管理和智能启动系统

产业列表:
1. 文旅产业 (5150)
2. 智能制造 (5151)
3. 智能开发 (5152)
4. 财经商贸 (5153)
5. 视觉设计 (5154)
6. 交通物流 (5155)
7. 大健康 (5156)
8. 土木水利 (5157)
9. 食品产业 (5158)
10. 化工产业 (5159)
11. 能源产业 (5160)
12. 环保产业 (5161)

🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
2025-09-24 14:14:14 +08:00

123 lines
3.8 KiB
Python

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import datetime
import shutil
import json
from collections import defaultdict
def generate_industries_with_avatars():
"""
生成带有岗位头像的industries数据
"""
# 读取能源岗位简历数据
with open("网页未导入数据/能源产业/能源岗位简历.json", 'r', encoding='utf-8') as f:
energy_jobs = json.load(f)
# 读取岗位等级数据(包含头像)
with open("src/data/joblevel.json", 'r', encoding='utf-8') as f:
joblevel_data = json.load(f)
# 创建岗位名称到头像的映射
position_avatars = {}
for level_key, level_data in joblevel_data["data"].items():
for position in level_data["list"]:
position_avatars[position["position_name"]] = position.get("img", "")
# 按岗位群分组
job_groups = defaultdict(list)
for job in energy_jobs:
group_name = job.get("简历岗位群", "")
if group_name:
job_groups[group_name].append(job)
# 生成industries数据结构
industries = []
group_id = 1
for group_name, jobs in job_groups.items():
industry = {
"id": f"energy_{group_id}",
"name": group_name,
"positions": [],
"questions": [
{
"id": f"group_q{group_id}",
"question": f"# {group_name}面试题",
"subQuestions": []
}
]
}
# 添加该岗位群下的所有岗位
pos_id = 1
for job in jobs:
position_name = job["岗位名称"]
avatar_url = position_avatars.get(position_name, "")
position = {
"id": f"energy_{group_id}_{pos_id}",
"title": position_name,
"level": job.get("岗位等级标签", "基础岗"),
"avatar": avatar_url,
"department": group_name,
"type": "全职",
"experience": "1-3年",
"education": "大专",
"salary": "8-15K",
"location": "北京",
"updateTime": "2024-01-20",
"description": f"负责{position_name}相关工作",
"requirements": []
}
industry["positions"].append(position)
pos_id += 1
industries.append(industry)
group_id += 1
return industries
def replace_industries_in_mock():
"""
替换mock文件中的industries数据
"""
mock_file = "src/mocks/resumeInterviewMock.js"
# 备份文件
backup_path = f"{mock_file}.backup_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}"
shutil.copy(mock_file, backup_path)
print(f"✅ 已备份文件到:{backup_path}")
# 生成新的industries数据
industries = generate_industries_with_avatars()
# 读取原文件内容
with open(mock_file, 'r', encoding='utf-8') as f:
content = f.read()
# 查找industries数组的起始和结束位置
import re
# 生成新的industries字符串
industries_str = json.dumps(industries, ensure_ascii=False, indent=2)
# 替换industries数组
pattern = r'const industries = \[[\s\S]*?\n\];'
replacement = f'const industries = {industries_str};'
new_content = re.sub(pattern, replacement, content, count=1)
# 写入文件
with open(mock_file, 'w', encoding='utf-8') as f:
f.write(new_content)
# 输出统计信息
print(f"✅ 成功替换industries数据")
print(f"📊 共 {len(industries)} 个岗位群")
for i, industry in enumerate(industries, 1):
print(f" {i}. {industry['name']} ({len(industry['positions'])}个岗位)")
if __name__ == "__main__":
replace_industries_in_mock()