import time
import uuid
from typing import Optional

from pydantic import BaseModel, Field

from services.clean_title import clean_title


class VideoItem(BaseModel):
    """
    视频数据结构，支持字段校验和预处理逻辑
    - 字段初始化后可通过 `prepare()` 异步方法补全和清洗数据
    - 使用 `produce_item()` 返回最终有效数据 dict
    """

    video_id: Optional[str] = Field(default_factory=lambda: str(uuid.uuid4()))
    user_id: str
    user_name: str
    out_video_id: str
    out_user_id: Optional[str]
    video_url: str
    cover_url: str
    video_title: str
    platform: str
    strategy: str
    session: Optional[str]

    publish_time_stamp: Optional[int] = None
    update_time_stamp: Optional[int] = None

    duration: int = 0
    play_cnt: int = 0
    like_cnt: int = 0
    comment_cnt: int = 0
    share_cnt: int = 0
    width: int = 0
    height: int = 0

    publish_time_str: Optional[str] = None
    publish_time: Optional[str] = None

    async def prepare(self):
        """
        异步预处理：清洗标题、补全发布时间和更新时间
        """
        # 标题清洗
        self.video_title = await clean_title(self.video_title)

        # 发布时间处理
        if not self.publish_time_stamp:
            self.publish_time_stamp = int(time.time())

        self.publish_time_str = time.strftime(
            "%Y-%m-%d %H:%M:%S", time.localtime(self.publish_time_stamp)
        )
        self.publish_time = self.publish_time_str

        # 更新时间戳默认当前时间
        if not self.update_time_stamp:
            self.update_time_stamp = int(time.time())

        if not self.session:
            self.session = str(f"{self.platform}_{int(time.time())}")

    async def produce_item(self) -> Optional[dict]:
        """
        异步生成最终数据字典，校验必要字段是否存在，返回 None 则不合格
        """
        await self.prepare()

        must_fields = [
            "video_id", "user_id", "user_name", "out_video_id", "session",
            "video_url", "cover_url", "platform", "strategy"
        ]
        for f in must_fields:
            if not getattr(self, f, None):
                return False

        return self.dict()