gahusb
598adcbeb5
- update_purchase에서 numbers/is_real 타입 변환 추가 (런타임 에러 방지) - purchase_manager에서 evolve_after_check 호출하여 EMA 피드백 루프 활성화 - checker.py 중복 recalculate_weights 호출 제거 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
100 lines
3.1 KiB
Python
100 lines
3.1 KiB
Python
"""
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구매 이력 관리 + 결과 체크 모듈.
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- check_purchases_for_draw(): 특정 회차 구매 건들의 결과를 자동 체크
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- 체커의 _calc_rank 재사용
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- 결과 체크 후 strategy_performance 자동 갱신
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"""
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import logging
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from .db import (
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get_draw, get_purchases, update_purchase_results,
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upsert_strategy_performance,
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)
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from .checker import _calc_rank
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logger = logging.getLogger("lotto-backend")
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RANK_PRIZE = {1: 0, 2: 0, 3: 1_500_000, 4: 50_000, 5: 5_000}
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def check_purchases_for_draw(drw_no: int) -> int:
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"""
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특정 회차 결과로 해당 회차 구매 건들을 채점한다.
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Returns: 채점한 구매 건 수
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"""
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win_row = get_draw(drw_no)
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if not win_row:
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return 0
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win_nums = [win_row["n1"], win_row["n2"], win_row["n3"],
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win_row["n4"], win_row["n5"], win_row["n6"]]
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bonus = win_row["bonus"]
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unchecked = get_purchases(draw_no=drw_no, checked=False)
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strategy_agg = {}
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count = 0
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for purchase in unchecked:
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numbers_list = purchase["numbers"]
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if not numbers_list:
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continue
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results = []
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for nums in numbers_list:
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rank, correct, has_bonus = _calc_rank(nums, win_nums, bonus)
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prize = RANK_PRIZE.get(rank, 0)
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results.append({
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"numbers": nums,
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"rank": rank,
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"correct": correct,
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"has_bonus": has_bonus,
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"prize": prize,
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})
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total_prize = sum(r["prize"] for r in results)
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update_purchase_results(purchase["id"], results, total_prize)
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strat = purchase["source_strategy"]
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if strat not in strategy_agg:
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strategy_agg[strat] = {
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"sets_count": 0,
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"total_correct": 0,
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"max_correct": 0,
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"prize_total": 0,
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"scores": [],
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"_results": [],
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}
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agg = strategy_agg[strat]
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agg["_results"].extend(results)
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for r in results:
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agg["sets_count"] += 1
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agg["total_correct"] += r["correct"]
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agg["max_correct"] = max(agg["max_correct"], r["correct"])
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agg["prize_total"] += r["prize"]
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agg["scores"].append(r["correct"] / 6.0)
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count += 1
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for strat, agg in strategy_agg.items():
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avg_score = sum(agg["scores"]) / len(agg["scores"]) if agg["scores"] else 0.0
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upsert_strategy_performance(
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strategy=strat,
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draw_no=drw_no,
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sets_count=agg["sets_count"],
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total_correct=agg["total_correct"],
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max_correct=agg["max_correct"],
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prize_total=agg["prize_total"],
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avg_score=round(avg_score, 4),
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)
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# EMA 피드백 루프: 전략 가중치 진화
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try:
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from .strategy_evolver import evolve_after_check
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evolve_after_check(strat, drw_no, agg["_results"])
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except Exception:
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logger.debug(f"[purchase_manager] evolve_after_check 건너뜀: {strat}")
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logger.info(f"[purchase_manager] {drw_no}회차 구매 {count}건 체크 완료")
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return count
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