feat(lotto): 채점 보조 함수 — 일치 수·패턴 요약·델타

lotto/app/jobs/grading_helpers.py

@@ -0,0 +1,93 @@
+"""채점 보조 — 일치 수 계산, 패턴 요약, 패턴 갭."""
+from typing import List, Dict, Any
+
+LOW_HIGH_CUT = 22  # curator_helpers.py 와 동일
+
+
+def score_picks_against_draw(picks: List[Dict[str, Any]],
+                              win_nums: List[int],
+                              bonus: int) -> Dict[str, Any]:
+    """4계층 중 한 그룹(예: core_picks 5세트) vs 추첨 결과 채점.
+
+    picks 는 [{numbers, risk_tag, reason}] 리스트.
+    """
+    if not picks:
+        return {"avg_match": None, "best_match": 0, "five_plus_prizes": 0, "best_tier": None}
+
+    win_set = set(win_nums)
+    matches = []
+    for p in picks:
+        nums = p.get("numbers") or []
+        m = len(set(nums) & win_set)
+        matches.append((m, p.get("risk_tag")))
+
+    avg = sum(m for m, _ in matches) / len(matches)
+    best_match, best_tier = max(matches, key=lambda x: x[0])
+    five_plus = sum(1 for m, _ in matches if m >= 3)  # 5등 이상
+
+    # tier별 평균 → 가장 잘 맞은 risk_tag
+    tier_scores: Dict[str, List[int]] = {}
+    for m, t in matches:
+        if t:
+            tier_scores.setdefault(t, []).append(m)
+    if tier_scores:
+        best_tier = max(tier_scores.items(),
+                        key=lambda kv: sum(kv[1]) / len(kv[1]))[0]
+
+    return {
+        "avg_match": round(avg, 2),
+        "best_match": best_match,
+        "five_plus_prizes": five_plus,
+        "best_tier": best_tier,
+    }
+
+
+def summarize_pattern(nums: List[int]) -> Dict[str, int]:
+    """한 세트의 패턴 요약 — 저/고, 홀/짝, 합계."""
+    nums = sorted(nums)
+    odd = sum(1 for n in nums if n % 2 == 1)
+    low = sum(1 for n in nums if n <= LOW_HIGH_CUT)
+    return {
+        "odd_count": odd,
+        "even_count": 6 - odd,
+        "low_count": low,
+        "high_count": 6 - low,
+        "sum": sum(nums),
+    }
+
+
+def aggregate_pattern_summaries(summaries: List[Dict[str, int]]) -> Dict[str, float]:
+    """여러 세트의 패턴 요약 → 평균(low_avg, odd_avg, sum_avg)."""
+    if not summaries:
+        return {"low_avg": None, "odd_avg": None, "sum_avg": None}
+    n = len(summaries)
+    return {
+        "low_avg": round(sum(s["low_count"] for s in summaries) / n, 2),
+        "odd_avg": round(sum(s["odd_count"] for s in summaries) / n, 2),
+        "sum_avg": round(sum(s["sum"] for s in summaries) / n, 1),
+    }
+
+
+def compute_pattern_delta(user_summary: Dict[str, float],
+                          draw_summary: Dict[str, float]) -> str:
+    """사용자 평균 vs 추첨 패턴의 가장 큰 격차 1~2개를 한 줄로."""
+    if not user_summary or user_summary.get("low_avg") is None:
+        return ""
+    deltas = []
+    if user_summary.get("low_avg") is not None and draw_summary.get("low_avg") is not None:
+        d = round(user_summary["low_avg"] - draw_summary["low_avg"], 2)
+        if abs(d) >= 0.5:
+            sign = "+" if d > 0 else ""
+            deltas.append(("저번호", d, f"저번호 편향 {sign}{d}"))
+    if user_summary.get("sum_avg") is not None and draw_summary.get("sum_avg") is not None:
+        d = round(user_summary["sum_avg"] - draw_summary["sum_avg"], 1)
+        if abs(d) >= 10:
+            sign = "+" if d > 0 else ""
+            deltas.append(("합계", d, f"합계 {sign}{d}"))
+    if user_summary.get("odd_avg") is not None and draw_summary.get("odd_avg") is not None:
+        d = round(user_summary["odd_avg"] - draw_summary["odd_avg"], 2)
+        if abs(d) >= 0.5:
+            sign = "+" if d > 0 else ""
+            deltas.append(("홀짝", d, f"홀짝 {sign}{d}"))
+    deltas.sort(key=lambda x: -abs(x[1]))
+    return " / ".join(d[2] for d in deltas[:2])