"""三层去重模块的数据模型。"""

from __future__ import annotations

from datetime import datetime
from enum import StrEnum
from typing import Literal, Self

from pydantic import BaseModel, Field, model_validator


class DedupLayer(StrEnum):
    """命中去重的层。"""

    URL = "url"          # L1: 完全相同 URL
    CONTENT = "content"  # L2: 标准化后 content 完全一致
    SIMHASH = "simhash"  # L3: SimHash 汉明距离 <= 阈值


class Fingerprint(BaseModel):
    """单篇文章的指纹记录,持久化到 SQLite。

    source_ids: 同一内容组(去重后视为同一篇新闻)的全部来源列表,
                第一位是主源(即本指纹的 source_id);重复文章命中时由
                Deduper.ingest 自动合并,实现「一条唯一新闻记录多个源」。
    """

    url_hash: str = Field(..., description="主键,与 Article.url_hash 一致")
    content_hash: str = Field(..., description="标准化 content 的 SHA1[:16]")
    simhash: int = Field(..., description="64 位 SimHash 整数(无符号)")
    source_id: str
    url: str
    title: str
    publish_date: str | None = Field(default=None, description="YYYY-MM-DD,用于时间窗口")
    ingested_at: datetime = Field(default_factory=datetime.now)
    source_ids: list[str] = Field(
        default_factory=list,
        description="同内容组全部来源(去重合并),始终包含 source_id 且其居首",
    )

    @model_validator(mode="after")
    def _ensure_source_ids(self) -> Self:
        """保证 source_ids 非空、去重且以主源 source_id 开头。"""
        seen: list[str] = []
        for s in [self.source_id, *self.source_ids]:
            if s and s not in seen:
                seen.append(s)
        self.source_ids = seen
        return self


class DedupResult(BaseModel):
    """对单篇文章的判重结果。"""

    url_hash: str
    is_duplicate: bool
    matched_layer: DedupLayer | None = None
    matched_url_hash: str | None = None
    matched_url: str | None = None
    matched_title: str | None = None
    matched_source_id: str | None = Field(
        default=None, description="匹配指纹的主源 source_id"
    )
    all_source_ids: list[str] = Field(
        default_factory=list,
        description="该内容组(唯一新闻)的全部来源;含匹配指纹自身的来源",
    )
    hamming_distance: int | None = Field(
        default=None, description="仅 SimHash 层有值"
    )

    def short_summary(self) -> str:
        if not self.is_duplicate:
            return f"[UNIQUE] {self.url_hash}"
        layer = self.matched_layer.value if self.matched_layer else "?"
        extra = f" hd={self.hamming_distance}" if self.hamming_distance is not None else ""
        return f"[DUP/{layer}] {self.url_hash} ~ {self.matched_url_hash}{extra}"


class DedupStats(BaseModel):
    """指纹库统计。"""

    total: int = 0
    by_source: dict[str, int] = Field(default_factory=dict)
    earliest: str | None = None
    latest: str | None = None


# 类型别名,便于在批处理日志中归类
DedupVerdict = Literal["unique", "duplicate"]