105 lines
4.2 KiB
Python
105 lines
4.2 KiB
Python
"""成就判定核心，被异步任务和管理命令共用。
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判定刻意做成"一次查询取全部候选 + 内存比对"，与 problemset 里逐条查询的
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旧写法相反：一次判题只多 3~4 条 SQL。
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"""
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import logging
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from django.db import transaction
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from django.db.models import F
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from achievement.metrics import META_METRICS, METRIC_REGISTRY, build_ctx
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from achievement.models import Achievement, Operator, UserAchievement, UserStat
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logger = logging.getLogger(__name__)
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def get_or_create_stat(user):
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stat, _ = UserStat.objects.get_or_create(user=user)
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return stat
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def evaluate(user, metrics, only_metrics=None):
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"""返回该用户应解锁但尚未解锁的成就列表。"""
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unlocked_ids = set(UserAchievement.objects.filter(user=user).values_list("achievement_id", flat=True))
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qs = Achievement.objects.filter(visible=True).exclude(id__in=unlocked_ids)
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if only_metrics is not None:
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qs = qs.filter(metric__in=only_metrics)
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hits = []
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for achievement in qs:
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value = metrics.get(achievement.metric)
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# 指标从未产生有效值时 key 不存在，直接跳过：
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# 否则 min_ac_code_chars 这类极小值指标会对新用户恒成立
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if value is None:
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continue
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if achievement.operator == Operator.GTE and value >= achievement.threshold:
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hits.append(achievement)
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elif achievement.operator == Operator.LTE and value <= achievement.threshold:
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hits.append(achievement)
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return hits
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def unlock(user, achievements, backfilled=False, notified=False):
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"""写入解锁记录并累加 unlock_count，返回实际新建的记录。
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刻意逐条 get_or_create 而不是 bulk_create：unique_user_achievement 约束负责
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并发竞态，was_created 是"这一条确实是我新建的"的唯一可信判据。用
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bulk_create(ignore_conflicts=True) 则无法区分新建与已存在，并发判题时会把
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unlock_count 重复累加（获得率永久偏高），并对同一个奖杯重复推送通知。
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循环次数是"本次新解锁的成就数"，常态为 0，因此常态零查询。
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"""
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created = []
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for achievement in achievements:
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record, was_created = UserAchievement.objects.get_or_create(
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user=user,
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achievement=achievement,
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defaults={"backfilled": backfilled, "notified": notified},
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)
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if was_created:
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Achievement.objects.filter(id=achievement.id).update(unlock_count=F("unlock_count") + 1)
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created.append(record)
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return created
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def run_for_submission(user, submission):
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"""判题后的完整流程：更新指标 → 第一轮判定 → 元指标第二轮判定。"""
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ctx = build_ctx(user.id, submission)
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if ctx["skip"]:
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# 比赛提交不计入成就
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return []
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with transaction.atomic():
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stat = UserStat.objects.select_for_update().get_or_create(user=user)[0]
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for key, m in METRIC_REGISTRY.items():
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if key in META_METRICS:
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continue
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m.on_submission(stat.metrics, submission, ctx)
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stat.save(update_fields=["metrics", "update_time"])
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first = unlock(user, evaluate(user, stat.metrics))
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if not first:
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return []
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# 第二轮：只重算元指标、只判定依赖元指标的成就，不再有第三轮
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meta_values = {key: METRIC_REGISTRY[key].recompute(user) for key in META_METRICS}
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# 必须重新取锁并重新读一次 stat：上面那个 stat 对象的 metrics 是解锁前的快照，
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# 直接 save 会把整份字典写回，覆盖掉并发判题在这期间已提交的增量
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# （同一用户两次提交并发判题时会让提交数/AC 数静默倒退，且无定期重算兜底）。
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# 这里只合并元指标那几个 key。
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with transaction.atomic():
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stat = UserStat.objects.select_for_update().get(user=user)
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for key, value in meta_values.items():
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if value is None:
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stat.metrics.pop(key, None)
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else:
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stat.metrics[key] = value
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stat.save(update_fields=["metrics", "update_time"])
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second = unlock(user, evaluate(user, stat.metrics, only_metrics=META_METRICS))
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return first + second
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