#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import json
import random
from datetime import datetime, timedelta

def expand_logistics_jobs():
    """扩展交通物流岗位数据，增加更多岗位"""

    # 读取现有的岗位数据
    with open('src/data/companyJobsNew.json', 'r', encoding='utf-8') as f:
        existing_jobs = json.load(f)

    # 额外的交通物流岗位列表
    additional_positions = [
        "供应链分析师", "仓库主管", "货运代理", "物流规划师", "报关员",
        "调度员", "配送主管", "冷链物流专员", "跨境电商物流专员", "智慧物流工程师",
        "运输经理", "物流成本分析师", "供应链优化专员", "货运司机", "仓储主管",
        "物流信息系统管理员", "国际物流专员", "快递网点经理", "物流客服主管", "供应链培训师"
    ]

    # 公司列表
    logistics_companies = [
        "顺丰控股", "京东物流", "中通快递", "圆通速递", "申通快递",
        "德邦物流", "百世物流", "韵达速递", "中外运", "招商局物流",
        "菜鸟网络", "苏宁物流", "邮政速递", "极兔速递", "跨越速运"
    ]

    # 工作地点
    locations = ["上海", "北京", "深圳", "广州", "杭州", "南京", "苏州", "成都", "武汉", "西安", "天津", "重庆"]

    # 标签库
    all_tags = ["物流管理", "供应链", "仓储", "运输", "智能设备", "数据分析", "销售", "技术支持", "客户服务", "项目管理", "成本控制", "国际物流"]

    def generate_job_description(position):
        """生成职位描述"""
        base_desc = "负责"
        if "分析" in position:
            return base_desc + "物流数据分析和优化工作，提供决策支持，提升物流运营效率。"
        elif "主管" in position or "经理" in position:
            return base_desc + "团队管理和业务运营，确保物流服务质量和效率。"
        elif "专员" in position:
            return base_desc + "相关业务的执行和协调工作，保障物流流程顺畅运行。"
        elif "工程师" in position:
            return base_desc + "物流技术系统的开发、维护和优化工作。"
        else:
            return base_desc + "物流相关业务的日常运营和管理工作。"

    def get_salary_range(position):
        """根据岗位生成薪资范围"""
        if "经理" in position or "主管" in position:
            return random.choice(["15K-25K", "18K-28K", "20K-35K"])
        elif "工程师" in position or "分析师" in position:
            return random.choice(["12K-20K", "15K-25K", "18K-30K"])
        elif "专员" in position:
            return random.choice(["8K-12K", "10K-15K", "12K-18K"])
        else:
            return random.choice(["6K-10K", "8K-12K", "10K-14K"])

    # 生成额外的岗位数据
    new_jobs = []

    # 生成未来3个月内的截止日期
    base_date = datetime(2025, 1, 1)

    for i, position in enumerate(additional_positions):
        # 随机生成截止日期（1-90天后）
        days_offset = random.randint(30, 120)
        deadline = base_date + timedelta(days=days_offset)
        deadline_str = deadline.strftime("%Y/%-m/%-d")

        job_data = {
            "内推岗位名称": position,
            "岗位相关标签": "专业相关岗位",
            "岗位标签": random.choice(["就业", "实习"]),
            "薪资": get_salary_range(position),
            "工作地点": random.choice(locations),
            "学历要求": random.choice(["本科", "大专及以上", "本科及以上", "硕士及以上"]),
            "招聘人数": str(random.randint(1, 10)),
            "截止时间": deadline_str,
            "职位标签": random.sample(all_tags, random.randint(3, 5)),
            "福利标签": ["五险一金", "带薪年假", "节日福利", "员工旅游", "培训机会", "弹性工作"],
            "职位描述": generate_job_description(position),
            "任职要求": f"1. {random.choice(['物流管理', '交通运输', '供应链管理', '工业工程', '信息管理'])}等相关专业；\n2. 具备良好的沟通协调能力和团队合作精神；\n3. 熟悉物流行业运作流程；\n4. 有相关实习或工作经验者优先。",
            "公司介绍": f"{random.choice(logistics_companies)}是国内领先的物流企业，致力于为客户提供高效、智能、可靠的物流解决方案，业务覆盖全国。"
        }

        new_jobs.append(job_data)

    # 合并现有岗位和新岗位
    all_jobs = existing_jobs + new_jobs

    # 写入更新后的岗位数据
    with open('src/data/companyJobsNew.json', 'w', encoding='utf-8') as f:
        json.dump(all_jobs, f, ensure_ascii=False, indent=2)

    print(f"已扩展岗位数据:")
    print(f"- 原有岗位: {len(existing_jobs)} 个")
    print(f"- 新增岗位: {len(new_jobs)} 个")
    print(f"- 总计岗位: {len(all_jobs)} 个")

    # 显示新增的前5个岗位
    print("\n新增岗位示例:")
    for i, job in enumerate(new_jobs[:5], 1):
        print(f"{i}. {job['内推岗位名称']}: {job['薪资']} - {job['工作地点']} ({job['岗位标签']})")

if __name__ == "__main__":
    expand_logistics_jobs()