"""数据中台统一穿透查询 API（P1.2.5）。

作为各引擎与审计场景访问知识图谱的共同入口，对上层屏蔽底层是关系表还是图库。
对应需求 R2。
"""

from __future__ import annotations

import uuid

from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session

from app.api.schemas import (
    EntityOut,
    PenetrateRequest,
    PenetrateResponse,
    RelatedEntityOut,
)
from app.datahub.graph_repo import find_related_entities
from app.datahub.models import Entity
from app.db import get_session

router = APIRouter(prefix="/datahub", tags=["datahub"])


@router.get("/entities/{entity_id}", response_model=EntityOut)
def get_entity(entity_id: uuid.UUID, session: Session = Depends(get_session)) -> Entity:
    entity = session.get(Entity, entity_id)
    if entity is None:
        raise HTTPException(status_code=404, detail="实体不存在")
    return entity


@router.post("/penetrate", response_model=PenetrateResponse)
def penetrate(
    req: PenetrateRequest, session: Session = Depends(get_session)
) -> PenetrateResponse:
    """多跳穿透：返回与起点实体连通的关联实体（用于实控人/关联方/马甲识别）。"""
    start = session.get(Entity, req.start_entity_id)
    if start is None:
        raise HTTPException(status_code=404, detail="起点实体不存在")

    related_raw = find_related_entities(session, req.start_entity_id, max_depth=req.max_depth)

    # 批量取出关联实体详情，组装可解释结果
    id_to_depth = {rid: depth for rid, depth in related_raw}
    entities = (
        session.query(Entity).filter(Entity.id.in_(list(id_to_depth.keys()))).all()
        if id_to_depth
        else []
    )
    related = [
        RelatedEntityOut(entity=EntityOut.model_validate(e), depth=id_to_depth[e.id])
        for e in entities
    ]
    related.sort(key=lambda r: r.depth)

    return PenetrateResponse(
        start_entity_id=req.start_entity_id,
        max_depth=req.max_depth,
        related_count=len(related),
        related=related,
    )