from contextlib import asynccontextmanager

from tortoise import Tortoise
from app.job.job import scheduler
from fastapi import FastAPI
from app.config.tortoise_config import getTortoiseConfig
import logging

logger = logging.getLogger(__name__)


async def init():
    # 初始化链接
    logger.info("开始初始化数据库")
    await Tortoise.init(config=getTortoiseConfig().model_dump())
    # 生成数据库表数据
    logger.info("开始生成数据库表")
    await Tortoise.generate_schemas()


async def close():
    await Tortoise.close_connections()


# 使用asynccontextmanager装饰器定义一个异步上下文管理器函数lifespan
@asynccontextmanager
async def lifespan(app: FastAPI):
    # 开始apscheduler
    scheduler.start()
    logging.info("apscheduler启动完成")
    await init()
    logging.info("初始化数据库完成")
    # 获取程序开始执行的时间
    start_time = time.time()
    param = SpiderParams(
        startDate="2024-12-20",
        endDate="2024-12-21",
        target_type=[
            TypeEnum.ANIME,
            TypeEnum.EPISODES,
            TypeEnum.MOVIE,
            TypeEnum.VARIETY,
        ],
        url="http://guduodata.com",
    )
    print(param.get_time_range())
    asyncio.run(scrawl_and_save(param))
    print(f"程序执行耗时时间：{(time.time() - start_time) / 1000}")
    yield
    # 在异步上下文管理器中，"退出上下文"时清理机器学习模型，释放资源
    scheduler.shutdown()
    logging.info("apscheduler关闭完成")
    await close()
    logging.info("关闭数据库完成")