# models.py
from datetime import datetime, timezone, time
from typing import Optional, Any
import enum

from sqlalchemy import (
    String, Integer, BigInteger, Text, Boolean, DateTime, Time,
    Float, JSON, ForeignKey, Enum, UniqueConstraint, Index
)
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship


# ==========================================
# 0. 全局基类、枚举定义与动态类型
# ==========================================

class Base(DeclarativeBase):
    """
    SQLAlchemy 2.0 声明式基类
    所有的表模型都必须继承这个基类。
    """
    pass


# 让代码在 SQLite 环境下自动降级为 Integer 以保证自增正常工作，
# 而在生产环境部署到 PostgreSQL 或 MySQL 时，依然会使用容量更大的 BigInteger。
BigIntType = BigInteger().with_variant(Integer, "sqlite")


class SourceType(str, enum.Enum):
    """信息源的抓取方式"""
    HOT_TREND = "HOT_TREND"  # 热搜榜单类
    RSS_FEED = "RSS_FEED"  # 传统RSS订阅
    API = "API"  # 接口抓取类


class TargetType(str, enum.Enum):
    """
    多态目标类型 (Polymorphic Target)
    用于标记一条评论或一个标签到底是挂载在哪个实体下的。
    """
    EVENT = "EVENT"  # 挂载在单个热搜事件下
    TREND = "TREND"  # 挂载在宏观趋势下
    ARTICLE = "ARTICLE"  # 挂载在具体新闻文章下


class TaskStatus(str, enum.Enum):
    """后台任务状态"""
    SUCCESS = "SUCCESS"
    ERROR = "ERROR"


class GenderType(str, enum.Enum):
    """用户性别枚举"""
    MALE = "MALE"
    FEMALE = "FEMALE"
    OTHER = "OTHER"
    UNKNOWN = "UNKNOWN"


def utcnow():
    """
    获取带UTC时区的当前时间 (最佳实践)
    服务器内部和数据库统一存储 UTC 时间，只在前端展示时转为用户本地时区，避免时区错乱。
    """
    return datetime.now(timezone.utc)


# ==========================================
# 模块一：信息源管理
# ==========================================
class InfoSource(Base):
    """
    抓取源配置表
    充当爬虫的“任务清单”，后台可以随时开关特定的信息源，而不需要重启代码。
    """
    __tablename__ = "info_sources"

    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
    source_name: Mapped[str] = mapped_column(String(100), comment="信息源名称")
    source_type: Mapped[SourceType] = mapped_column(Enum(SourceType))
    home_url: Mapped[Optional[str]] = mapped_column(String(255))
    is_enabled: Mapped[bool] = mapped_column(Boolean, default=True)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


# ==========================================
# 模块二：AI 语义聚类中枢 (大事件池)
# ==========================================
class UnifiedEvent(Base):
    """
    AI 统一事件表
    核心业务逻辑：比如微博热搜叫“苹果发布会”，知乎热搜叫“iPhone 16 测评”，
    它们在子表(TrendingEvent)是两条记录，但通过 AI 语义向量对比后，
    会将它们统一挂载到这个表的一个 UnifiedEvent ID 下，实现跨平台事件聚合。
    """
    __tablename__ = "unified_events"

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    unified_title: Mapped[str] = mapped_column(String(255), comment="AI统一标题")
    ai_comprehensive_summary: Mapped[Optional[str]] = mapped_column(Text, comment="AI全局深度总结")

    center_embedding: Mapped[Optional[str]] = mapped_column(Text, comment="中心向量")  # 用于高维空间相似度计算
    hot_score: Mapped[int] = mapped_column(Integer, default=0, comment="聚合热度得分")

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


# ==========================================
# 模块三：内容存储库 (热搜 & 新闻子节点)
# ==========================================
class TrendingEvent(Base):
    """
    各平台热搜数据明细表
    """
    __tablename__ = "trending_events"
    __table_args__ = (
        # 联合唯一索引：同一个来源(比如微博)的同一条外部ID(MD5)只能存在一条记录，防重插核心保障
        UniqueConstraint("source_id", "external_id", name="idx_unique_external_trend"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    source_id: Mapped[int] = mapped_column(ForeignKey("info_sources.id"))
    unified_event_id: Mapped[Optional[int]] = mapped_column(ForeignKey("unified_events.id"))

    external_id: Mapped[str] = mapped_column(String(32), comment="32位MD5哈希指纹防重")
    title_embedding: Mapped[Optional[str]] = mapped_column(Text)

    icon_url: Mapped[Optional[str]] = mapped_column(String(500))
    current_headline: Mapped[str] = mapped_column(String(255))
    event_url: Mapped[Optional[str]] = mapped_column(String(500))
    app_link: Mapped[Optional[str]] = mapped_column(String(500))
    current_ranking: Mapped[Optional[int]] = mapped_column(Integer)
    brief_snippet: Mapped[Optional[str]] = mapped_column(Text)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


class NewsArticle(Base):
    """新闻文章明细表 (与 TrendingEvent 类似，但侧重长文本阅读)"""
    __tablename__ = "news_articles"
    __table_args__ = (
        UniqueConstraint("source_id", "external_id", name="idx_unique_external_article"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    source_id: Mapped[int] = mapped_column(ForeignKey("info_sources.id"))
    unified_event_id: Mapped[Optional[int]] = mapped_column(ForeignKey("unified_events.id"))

    external_id: Mapped[str] = mapped_column(String(32))
    title_embedding: Mapped[Optional[str]] = mapped_column(Text)

    cover_image_url: Mapped[Optional[str]] = mapped_column(String(500))
    article_title: Mapped[str] = mapped_column(String(255))
    article_url: Mapped[Optional[str]] = mapped_column(String(500))
    author_name: Mapped[Optional[str]] = mapped_column(String(100))
    original_summary: Mapped[Optional[str]] = mapped_column(Text)
    publish_time: Mapped[Optional[datetime]] = mapped_column(DateTime(timezone=True))

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


# ==========================================
# 模块四：热度与轨迹追踪
# ==========================================
class HeadlineRevision(Base):
    """
    标题修订历史表
    用于记录平台方暗戳戳修改热搜词条的行为（例如公关介入改标题）。
    """
    __tablename__ = "headline_revisions"

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    event_id: Mapped[int] = mapped_column(ForeignKey("trending_events.id"))
    previous_headline: Mapped[str] = mapped_column(String(255))
    revised_headline: Mapped[str] = mapped_column(String(255))

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


class RankingLog(Base):
    """
    热搜排名时间序列化日志
    每一次抓取都会生成一条记录，可以用于前端绘制热搜“排名起伏折线图”。
    """
    __tablename__ = "ranking_logs"
    __table_args__ = (
        # 针对时间序列查询优化的复合索引，加速类似 "查询某事件在过去24小时内的排名变化" 的操作
        Index("idx_event_time", "event_id", "observed_at"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    event_id: Mapped[int] = mapped_column(ForeignKey("trending_events.id"))
    ranking_position: Mapped[int] = mapped_column(Integer)
    observed_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


# ==========================================
# 模块五：多态话题与多态评论
# ==========================================
# 【设计模式】：多态设计
# 通过 target_type (存表名/类型) + target_id (存主键ID) 的组合，
# 让这两个表既能挂载在"单一热搜"下，也能挂载在"新闻文章"下，甚至挂在"统一大事件"下，避免了建立无数个外键的冗余。

class ExtractedTopic(Base):
    """AI 提取的核心话题标签表"""
    __tablename__ = "extracted_topics"
    __table_args__ = (
        Index("idx_topic_keyword", "topic_keyword"),
        # 多态查询索引，加速 target_type + target_id 的组合查询
        Index("idx_polymorphic_topics", "target_type", "target_id"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    target_type: Mapped[TargetType] = mapped_column(Enum(TargetType))
    target_id: Mapped[int] = mapped_column(BigIntType)
    topic_keyword: Mapped[str] = mapped_column(String(100))
    relevance_score: Mapped[Optional[float]] = mapped_column(Float)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


class DiscussionComment(Base):
    """全平台统一评论表"""
    __tablename__ = "discussion_comments"
    __table_args__ = (
        Index("idx_polymorphic_comments", "target_type", "target_id"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    target_type: Mapped[TargetType] = mapped_column(Enum(TargetType))
    target_id: Mapped[int] = mapped_column(BigIntType)

    commenter_name: Mapped[Optional[str]] = mapped_column(String(100))
    comment_content: Mapped[str] = mapped_column(Text)
    likes_count: Mapped[int] = mapped_column(Integer, default=0)
    external_comment_id: Mapped[Optional[str]] = mapped_column(String(32))
    comment_time: Mapped[Optional[datetime]] = mapped_column(DateTime(timezone=True))

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


# ==========================================
# 模块六：用户画像与多渠道高可用推送系统
# ==========================================
class AppUser(Base):
    """系统核心用户表"""
    __tablename__ = "app_users"

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    email: Mapped[str] = mapped_column(String(150), unique=True, index=True)
    password_hash: Mapped[Optional[str]] = mapped_column(String(255))

    nickname: Mapped[Optional[str]] = mapped_column(String(100))
    avatar_url: Mapped[Optional[str]] = mapped_column(String(500))
    gender: Mapped[GenderType] = mapped_column(Enum(GenderType), default=GenderType.UNKNOWN)

    # 预留的 JSON 字段，可以存放未来灵活变化的用户配置，避免频繁修改表结构
    metadata_: Mapped[Optional[Any]] = mapped_column("metadata", JSON, comment="自定义扩展偏好")

    timezone: Mapped[str] = mapped_column(String(50), default="Asia/Shanghai")
    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


class UserPushEndpoint(Base):
    """
    多渠道推送端点配置表
    一个用户可能绑定了邮箱(EMAIL)和微信(WECHAT)，支持配置降级重试(priority_level)。
    """
    __tablename__ = "user_push_endpoints"
    __table_args__ = (
        UniqueConstraint("user_id", "channel_type", name="idx_unique_user_channel"),
    )

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("app_users.id"))
    channel_type: Mapped[str] = mapped_column(String(50), comment="如 EMAIL, WECHAT")
    channel_account: Mapped[str] = mapped_column(String(255))
    is_active: Mapped[bool] = mapped_column(Boolean, default=True)
    priority_level: Mapped[int] = mapped_column(Integer, default=1, comment="1最高，降级重试")

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)
    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow, onupdate=utcnow)


class UserTopicPreference(Base):
    """用户订阅的兴趣标签库"""
    __tablename__ = "user_topic_preferences"
    __table_args__ = (
        UniqueConstraint("user_id", "interested_keyword", name="idx_unique_preference"),
    )

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("app_users.id"))
    interested_keyword: Mapped[str] = mapped_column(String(100))

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


class UserDeliverySchedule(Base):
    """用户勿扰/定时推送时间表"""
    __tablename__ = "user_delivery_schedules"
    __table_args__ = (
        UniqueConstraint("user_id", "delivery_time", name="idx_unique_schedule"),
    )

    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("app_users.id"))
    delivery_time: Mapped[time] = mapped_column(Time, comment="如 08:30:00")
    is_active: Mapped[bool] = mapped_column(Boolean, default=True)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


class DeliveryHistory(Base):
    """
    推送历史防刷表
    核心用途：一旦给某个用户推送过某条新闻/事件，就记录在这里。
    下次再触发推荐时，检查这个表，防止给同一个用户反复发送相同的内容。
    """
    __tablename__ = "delivery_history"
    __table_args__ = (
        UniqueConstraint("user_id", "target_type", "target_id", name="idx_prevent_duplicate_push"),
    )

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("app_users.id"))
    target_type: Mapped[TargetType] = mapped_column(Enum(TargetType))
    target_id: Mapped[int] = mapped_column(BigIntType)
    status: Mapped[TaskStatus] = mapped_column(Enum(TaskStatus))

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)


# ==========================================
# 模块七：系统任务监控
# ==========================================
class DataSyncTask(Base):
    """
    数据同步健康度监控表
    这就是爬虫脚本每次运行都要写入记录的地方，用于后台 Dashboard 监控爬虫健康状态和错误堆栈。
    """
    __tablename__ = "data_sync_tasks"

    id: Mapped[int] = mapped_column(BigIntType, primary_key=True, autoincrement=True)
    source_id: Mapped[int] = mapped_column(ForeignKey("info_sources.id"))
    items_fetched: Mapped[int] = mapped_column(Integer, default=0)
    task_status: Mapped[TaskStatus] = mapped_column(Enum(TaskStatus))
    error_trace: Mapped[Optional[str]] = mapped_column(Text)

    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=utcnow)