49 lines
1.7 KiB
Python
49 lines
1.7 KiB
Python
"""채점 서비스 — 결과 입력 시 해당 경기 유저 픽 전수 채점 + 유저별 누적.
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관리자 setResult 와 워커가 공용으로 사용. scoring.grade_prediction 적용
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(scoring.json 배점) 후 services.points 로 user_points 누적 갱신.
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"""
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from __future__ import annotations
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import logging
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from ..domain import now_utc
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from ..models import Match, UserPrediction
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from ..scoring import grade_prediction, outcome_of
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from .points import accumulate_user_points
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log = logging.getLogger("triplepick.grading")
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async def apply_result(db: AsyncSession, match: Match, score_a: int, score_b: int) -> int:
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"""결과 기록 + 해당 경기 픽 전수 채점 + 유저별 포인트 누적. 채점된 픽 수 반환."""
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match.result_score_a = score_a
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match.result_score_b = score_b
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match.result_outcome = outcome_of(score_a, score_b)
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match.status = "finished"
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match.finished_at = now_utc()
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picks = (
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await db.execute(
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select(UserPrediction).where(UserPrediction.match_id == match.match_id)
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)
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).scalars().all()
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baseball = match.league in ("kbo", "mlb")
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for p in picks:
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key, value = grade_prediction(
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p.score_a, p.score_b, score_a, score_b, baseball=baseball
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)
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p.points = value
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p.scored_at = now_utc()
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# 채점된 픽의 유저(이메일)별 누적 포인트 갱신 — 같은 트랜잭션
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await accumulate_user_points(db, {p.email for p in picks})
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await db.commit()
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log.info("graded %d picks for %s (%d-%d)", len(picks), match.match_id, score_a, score_b)
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return len(picks)
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