135 lines
4.8 KiB
Python
135 lines
4.8 KiB
Python
"""관리자 API — Bearer 토큰 인증. 경기/AI예측 upsert + 결과 입력(채점)."""
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from __future__ import annotations
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from fastapi import APIRouter, Depends, Header, HTTPException
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from sqlalchemy import func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from ..config import settings
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from ..database import get_db
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from ..domain import now_utc
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from ..models import AIPrediction, CrowdStats, Match, PageVisit, UserPrediction
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from ..schemas import AdminAIPredictionIn, AdminSetResultIn, DailyVisitOut, GenericOk
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from ..services.grading import apply_result
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router = APIRouter(prefix="/api/admin", tags=["admin"])
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def require_admin(authorization: str = Header(default="")) -> None:
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token = authorization.removeprefix("Bearer ").strip()
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if not token or token != settings.admin_api_token:
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raise HTTPException(status_code=401, detail="UNAUTHORIZED")
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@router.post("/ai-predictions", response_model=GenericOk, dependencies=[Depends(require_admin)])
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async def upsert_ai_prediction(
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body: AdminAIPredictionIn, db: AsyncSession = Depends(get_db)
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) -> GenericOk:
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match = (
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await db.execute(select(Match).where(Match.match_id == body.matchId))
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).scalars().first()
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if not match:
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raise HTTPException(status_code=404, detail="MATCH_NOT_FOUND")
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pred = (
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await db.execute(
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select(AIPrediction).where(
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AIPrediction.match_id == body.matchId, AIPrediction.model == body.model
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)
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)
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).scalars().first()
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if pred is None:
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pred = AIPrediction(match_id=body.matchId, model=body.model)
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db.add(pred)
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pred.outcome = body.outcome
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pred.score_a = body.scoreA
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pred.score_b = body.scoreB
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pred.confidence_pct = body.confidencePct
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pred.reason_ko = body.reasonKo
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pred.reason_en = body.reasonEn
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pred.generated_at = now_utc()
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pred.source = "admin"
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await db.commit()
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return GenericOk(ok=True, detail="upserted")
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@router.post("/result", response_model=GenericOk, dependencies=[Depends(require_admin)])
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async def set_result(
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body: AdminSetResultIn, db: AsyncSession = Depends(get_db)
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) -> GenericOk:
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match = (
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await db.execute(select(Match).where(Match.match_id == body.matchId))
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).scalars().first()
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if not match:
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raise HTTPException(status_code=404, detail="MATCH_NOT_FOUND")
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graded = await apply_result(db, match, body.scoreA, body.scoreB)
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# 결과 메일은 워커가 result_email_delay_minutes 경과 후 발송(@finished_at 기준).
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return GenericOk(
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ok=True,
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detail="result set & graded",
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extra={"gradedPicks": graded, "emailsSentBy": "worker"},
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)
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@router.get(
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"/visits", response_model=list[DailyVisitOut], dependencies=[Depends(require_admin)]
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)
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async def daily_visits(db: AsyncSession = Depends(get_db)) -> list[DailyVisitOut]:
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"""일별 순수 방문자 수 (최신순)."""
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rows = (
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await db.execute(
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select(PageVisit.visit_date, func.count())
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.group_by(PageVisit.visit_date)
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.order_by(PageVisit.visit_date.desc())
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)
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).all()
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return [DailyVisitOut(date=d.isoformat(), uniqueVisitors=c) for d, c in rows]
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@router.post(
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"/recount-crowd", response_model=GenericOk, dependencies=[Depends(require_admin)]
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)
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async def recount_crowd(db: AsyncSession = Depends(get_db)) -> GenericOk:
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"""crowd_stats 를 user_predictions(진실 원천)에서 재집계.
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과거 같은 outcome 재제출로 팀 컬럼만 부풀려진(=합 100% 초과) 행을 복구한다.
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"""
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# 경기별 outcome 분포 집계
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rows = (
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await db.execute(
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select(
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UserPrediction.match_id,
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UserPrediction.outcome,
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func.count(),
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).group_by(UserPrediction.match_id, UserPrediction.outcome)
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)
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).all()
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tally: dict[str, dict[str, int]] = {}
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for match_id, outcome, c in rows:
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t = tally.setdefault(
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match_id, {"total": 0, "team_a_win": 0, "draw": 0, "team_b_win": 0}
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)
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col = {"TEAM_A_WIN": "team_a_win", "DRAW": "draw", "TEAM_B_WIN": "team_b_win"}[outcome]
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t[col] += c
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t["total"] += c
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stats = (await db.execute(select(CrowdStats))).scalars().all()
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fixed = 0
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for s in stats:
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t = tally.get(s.match_id, {"total": 0, "team_a_win": 0, "draw": 0, "team_b_win": 0})
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if (
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s.total != t["total"]
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or s.team_a_win != t["team_a_win"]
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or s.draw != t["draw"]
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or s.team_b_win != t["team_b_win"]
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):
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s.total = t["total"]
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s.team_a_win = t["team_a_win"]
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s.draw = t["draw"]
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s.team_b_win = t["team_b_win"]
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fixed += 1
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await db.commit()
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return GenericOk(ok=True, detail="crowd recounted", extra={"matchesFixed": fixed})
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