freedakgmail
65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
"""数据中台统一穿透查询 API（P1.2.5）。
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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。
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对应需求 R2。
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"""
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from __future__ import annotations
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import uuid
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from fastapi import APIRouter, Depends, HTTPException
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from sqlalchemy.orm import Session
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from app.api.schemas import (
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EntityOut,
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PenetrateRequest,
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PenetrateResponse,
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RelatedEntityOut,
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)
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from app.datahub.graph_repo import find_related_entities
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from app.datahub.models import Entity
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from app.db import get_session
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router = APIRouter(prefix="/datahub", tags=["datahub"])
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@router.get("/entities/{entity_id}", response_model=EntityOut)
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def get_entity(entity_id: uuid.UUID, session: Session = Depends(get_session)) -> Entity:
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entity = session.get(Entity, entity_id)
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if entity is None:
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raise HTTPException(status_code=404, detail="实体不存在")
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return entity
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@router.post("/penetrate", response_model=PenetrateResponse)
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def penetrate(
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req: PenetrateRequest, session: Session = Depends(get_session)
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) -> PenetrateResponse:
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"""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）。"""
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start = session.get(Entity, req.start_entity_id)
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if start is None:
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raise HTTPException(status_code=404, detail="起点实体不存在")
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related_raw = find_related_entities(session, req.start_entity_id, max_depth=req.max_depth)
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# 批量取出关联实体详情，组装可解释结果
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id_to_depth = {rid: depth for rid, depth in related_raw}
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entities = (
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session.query(Entity).filter(Entity.id.in_(list(id_to_depth.keys()))).all()
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if id_to_depth
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else []
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)
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related = [
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RelatedEntityOut(entity=EntityOut.model_validate(e), depth=id_to_depth[e.id])
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for e in entities
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]
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related.sort(key=lambda r: r.depth)
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return PenetrateResponse(
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start_entity_id=req.start_entity_id,
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max_depth=req.max_depth,
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related_count=len(related),
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related=related,
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)
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