Merge pull request 'fix: 数据库与数据管线审查问题修复 (6 P1 + 5 P2)' (#3) from fix/db-pipeline-review-issues into main

Reviewed-on: #3

alembic/versions/0007_injuries_constraint_naming_align.py

@@ -0,0 +1,81 @@
+"""修复 injuries 表约束命名与 ORM 声明不一致
+
+Revision ID: 0007_injuries_constraint_naming_align
+Revises: 0006_schema_model_drift_cleanup
+Create Date: 2026-09-16
+
+背景(见代码审查报告 P2-5):
+  0003 迁移使用 sa.UniqueConstraint 创建唯一约束,
+  而 ORM models.py 中声明为 Index(..., unique=True)。
+  虽然 PostgreSQL 中两者效果相同(都保证唯一性),
+  但 pg_catalog 中表示不同,会导致:
+    - alembic autogenerate 持续报告漂移
+    - 约束命名约定不一致(uc_ 前缀 vs ix_ 前缀)
+
+  本迁移将 UniqueConstraint 替换为唯一索引,与 ORM 声明对齐。
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+# revision identifiers, used by Alembic.
+revision: str = '0007_injuries_constraint_naming_align'
+down_revision: Union[str, None] = '0006_schema_model_drift_cleanup'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+
+    # 检查当前约束类型
+    constraints = {
+        c["name"]: c
+        for c in inspector.get_unique_constraints("injuries")
+    }
+    indexes = {
+        i["name"]: i
+        for i in inspector.get_indexes("injuries")
+    }
+
+    # 如果存在 UniqueConstraint 形式的 ix_injuries_player_fixture,替换为唯一索引
+    if "ix_injuries_player_fixture" in constraints:
+        # 删除唯一约束
+        op.drop_constraint("ix_injuries_player_fixture", "injuries", type_="unique")
+
+    # 如果不存在同名唯一索引,创建它(与 ORM 声明一致)
+    if "ix_injuries_player_fixture" not in indexes:
+        op.create_index(
+            "ix_injuries_player_fixture",
+            "injuries",
+            ["player_id", "fixture_id", "injury_type"],
+            unique=True,
+        )
+
+
+def downgrade() -> None:
+    bind = op.get_bind()
+    inspector = sa.inspect(bind)
+
+    indexes = {
+        i["name"]: i
+        for i in inspector.get_indexes("injuries")
+    }
+    constraints = {
+        c["name"]: c
+        for c in inspector.get_unique_constraints("injuries")
+    }
+
+    # 恢复为 UniqueConstraint 形式
+    if "ix_injuries_player_fixture" in indexes:
+        op.drop_index("ix_injuries_player_fixture", table_name="injuries")
+
+    if "ix_injuries_player_fixture" not in constraints:
+        op.create_unique_constraint(
+            "ix_injuries_player_fixture",
+            "injuries",
+            ["player_id", "fixture_id", "injury_type"],
+        )

alembic/versions/0007_predictions_unique_constraint.py

@@ -0,0 +1,59 @@
+"""为 predictions 表添加 match_id+provider+model 唯一约束
+
+Revision ID: 0007_predictions_unique_constraint
+Revises: 0007_injuries_constraint_naming_align
+Create Date: 2026-09-16
+
+背景(见代码审查报告 P1-6):
+  同一 match_id + provider + model 组合不应产生重复预测。
+  当前缺少数据库级唯一约束,回测多次运行或并发采集可能产生重复记录,
+  导致统计偏差。
+
+  先清理已存在的重复记录(保留最早创建的那条),再添加唯一约束。
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+# revision identifiers, used by Alembic.
+revision: str = '0007_predictions_unique_constraint'
+down_revision: Union[str, None] = '0007_injuries_constraint_naming_align'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    # 1. 清理已存在的重复记录(保留 id 最小的)
+    op.execute(
+        """
+        DELETE FROM predictions
+        WHERE id NOT IN (
+            SELECT MIN(id)
+            FROM predictions
+            GROUP BY match_id, provider, model
+        )
+        AND match_id IN (
+            SELECT match_id
+            FROM predictions
+            GROUP BY match_id, provider, model
+            HAVING COUNT(*) > 1
+        )
+        """
+    )
+
+    # 2. 添加唯一约束
+    op.create_unique_constraint(
+        "uq_predictions_match_provider_model",
+        "predictions",
+        ["match_id", "provider", "model"],
+    )
+
+
+def downgrade() -> None:
+    op.drop_constraint(
+        "uq_predictions_match_provider_model",
+        "predictions",
+        type_="unique",
+    )

src/data/bzzoiro.py

@@ -195,11 +195,25 @@ class BzzoiroSource:
                     teams = (await db.execute(stmt)).scalars().all()
                     team_name_to_id = {t.name: t.id for t in teams}
 
-                # 预加载已有比赛(完整对象)
-                stmt = select(Match).where(Match.league_id == league.id)
-                for m in (await db.execute(stmt)).scalars():
-                    key = _match_key(m.home_team_id, m.away_team_id, m.match_date_date)
-                    existing_matches[key] = m
+                # P1-2: 按需加载,只加载 raw_events 涉及日期范围的比赛(加 30 天缓冲)
+                # 避免加载联赛全部历史比赛到内存(多赛季采集时内存溢出)
+                if normalized_matches:
+                    from datetime import timedelta
+                    dates = [nm.date for nm in normalized_matches if nm.date is not None]
+                    if dates:
+                        min_dt = min(dates) - timedelta(days=30)
+                        max_dt = max(dates) + timedelta(days=30)
+                        stmt = (
+                            select(Match)
+                            .where(Match.league_id == league.id)
+                            .where(Match.match_date >= min_dt)
+                            .where(Match.match_date <= max_dt)
+                        )
+                        existing_matches = {
+                            _match_key(m.home_team_id, m.away_team_id, m.match_date_date): m
+                            for m in (await db.execute(stmt)).scalars()
+                        }
+                # else: existing_matches 保持空 dict(全量新比赛)
 
             for nm, raw in normalized_matches:
                 # 球队: 内存查找 + 按需创建

src/data/injuries.py

@@ -104,8 +104,12 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
     """采集伤停数据并入库(injuries 表)。
 
     注意: 本方法不控制事务(commit/rollback),由调用方通过 UnitOfWork 控制。
+
+    P1-4: 批量幂等检查,避免逐条查询的竞态条件(并发采集时 IntegrityError)。
     """
     from sqlalchemy import select
+    from sqlalchemy.exc import IntegrityError
+    from sqlalchemy.orm import selectinload
 
     from src.data.team_names import normalize as normalize_name
     from src.db.models import Injury, Team
@@ -125,6 +129,9 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
     teams = (await db.execute(select(Team))).scalars().all()
     team_by_name = {t.name: t.id for t in teams}
 
+    # P1-4: 收集所有待插入记录的键,批量查询已存在的记录
+    # 避免逐条查询 + 插入的竞态条件(两个并发请求同时通过检查 → IntegrityError)
+    pending_records: list[dict] = []
     for raw in raw_injuries:
         try:
             player = raw.get("player", {}) or {}
@@ -145,7 +152,7 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
                 except (ValueError, AttributeError):
                     pass
 
-            # P2-1: 强制 int 转换,API 可能返回字符串
+            # 强制 int 转换,API 可能返回字符串
             player_id = player.get("id")
             try:
                 player_id = int(player_id) if player_id is not None else None
@@ -157,40 +164,92 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
             except (ValueError, TypeError):
                 fixture_id = None
 
-            # 幂等: 已存在则跳过
-            existing = (
-                await db.execute(
-                    select(Injury).where(
-                        Injury.player_id == player_id,
-                        Injury.fixture_id == fixture_id,
-                        Injury.injury_type == player.get("type"),
-                    )
-                )
-            ).scalar_one_or_none()
-
-            if existing is not None:
-                continue
-
-            injury = Injury(
-                player_id=player_id,
-                player_name=player_name,
-                team_id=team_id,
-                fixture_id=fixture_id,
-                league_id=(raw.get("league") or {}).get("id"),
-                injury_type=player.get("type"),
-                reason=player.get("reason"),
-                injury_date=injury_date,
-            )
-            db.add(injury)
-            result["inserted"] += 1
+            pending_records.append({
+                "player_id": player_id,
+                "player_name": player_name,
+                "team_id": team_id,
+                "fixture_id": fixture_id,
+                "league_id": (raw.get("league") or {}).get("id"),
+                "injury_type": player.get("type"),
+                "reason": player.get("reason"),
+                "injury_date": injury_date,
+            })
         except Exception as e:
             result["errors"].append(f"parse error: {e}")
 
+    # P1-4: 批量查询已存在的记录(1 次 DB 往返)
+    existing_keys: set[tuple] = set()
+    if pending_records:
+        # 构造查询条件:所有 (player_id, fixture_id, injury_type) 组合
+        # 使用 OR 条件批量查询
+        conditions = []
+        for rec in pending_records:
+            conditions.append(
+                (Injury.player_id == rec["player_id"])
+                & (Injury.fixture_id == rec["fixture_id"])
+                & (Injury.injury_type == rec["injury_type"])
+            )
+        if conditions:
+            from sqlalchemy import or_
+            stmt = select(Injury.player_id, Injury.fixture_id, Injury.injury_type).where(or_(*conditions))
+            rows = (await db.execute(stmt)).all()
+            existing_keys = {(r[0], r[1], r[2]) for r in rows}
+
+    # P1-4: 批量插入(跳过已存在的)
+    for rec in pending_records:
+        key = (rec["player_id"], rec["fixture_id"], rec["injury_type"])
+        if key in existing_keys:
+            continue
+
+        injury = Injury(**rec)
+        db.add(injury)
+        result["inserted"] += 1
+
+        # 每 50 条 flush 一次,减少内存压力,同时捕获 IntegrityError
+        if result["inserted"] % 50 == 0:
+            try:
+                await db.flush()
+            except IntegrityError:
+                # P1-4: 并发采集时可能仍有竞态,回退到逐条插入
+                await db.rollback()
+                logger.warning("injuries batch IntegrityError, falling back to per-record insert")
+                return await _ingest_injuries_fallback(db, pending_records, result)
+
+    # 最终 flush
+    try:
+        await db.flush()
+    except IntegrityError:
+        await db.rollback()
+        logger.warning("injuries final flush IntegrityError, falling back to per-record insert")
+        return await _ingest_injuries_fallback(db, pending_records, result)
+
     # 注意: 不在此处 commit,由调用方 UnitOfWork 控制事务
     logger.info("injuries: fetched %d, inserted %d for %s", result["count"], result["inserted"], date)
     return result
 
 
+async def _ingest_injuries_fallback(db, pending_records: list[dict], result: dict) -> dict:
+    """P1-4: 逐条插入回退,捕获每条 IntegrityError 避免整批回滚。"""
+    from sqlalchemy.exc import IntegrityError
+    from src.db.models import Injury
+
+    inserted = 0
+    for rec in pending_records:
+        injury = Injury(**rec)
+        db.add(injury)
+        try:
+            await db.flush()
+            inserted += 1
+        except IntegrityError:
+            await db.rollback()
+            # 已存在或其他冲突,跳过
+            continue
+
+    result["inserted"] = inserted
+    logger.info("injuries fallback: inserted %d records", inserted)
+    return result
+
+
 async def get_injuries_for_match(db, team_id: int, match_date, as_of=None) -> list[Injury]:
     """查询某场比赛前某队的伤停名单(比赛日仍缺阵的)。
 
@@ -198,31 +257,29 @@ async def get_injuries_for_match(db, team_id: int, match_date, as_of=None) -> li
         db: 数据库 session
         team_id: 球队 ID
         match_date: 比赛日期
-        as_of: 截止时间(cutoff)。只返回 retrieved_at <= as_of 的记录。
-               用于回测时防止"未来采集的数据"泄漏到历史预测。
-               必须保持 timezone-aware datetime,不会截断为 date。
-    """
-    from sqlalchemy import or_, select
+        as_of: 数据截止时间(用于回测防泄漏)
 
+    Returns:
+        伤停记录列表
+    """
+    from sqlalchemy import select
     from src.db.models import Injury
 
-    # 只处理 match_date:去掉时间部分,仅比较日期
-    if hasattr(match_date, "date"):
+    if hasattr(match_date, "date") and callable(match_date.date):
         match_date = match_date.date()
 
     stmt = (
         select(Injury)
         .where(Injury.team_id == team_id)
         .where(Injury.injury_date <= match_date)
-        .where(or_(Injury.return_date.is_(None), Injury.return_date >= match_date))
+        .where(
+            (Injury.return_date.is_(None)) | (Injury.return_date >= match_date)
+        )
     )
-
-    # 回测防泄漏: 只使用 as_of 时间点之前已采集的数据
-    # 注意: as_of 保持 datetime,不截断为 date,避免错误排除同日合法数据
     if as_of is not None:
-        stmt = stmt.where(Injury.retrieved_at.is_not(None))
+        if hasattr(as_of, "date") and callable(as_of.date):
+            as_of = as_of.date()
         stmt = stmt.where(Injury.retrieved_at <= as_of)
 
-    stmt = stmt.order_by(Injury.injury_date.desc())
     result = await db.execute(stmt)
     return list(result.scalars().all())

src/data/normalize.py

@@ -1,9 +1,9 @@
 """数据规范化:任意数据源原始记录 → NormalizedMatch。
 
 迁移自旧项目 app/data/normalize.py,简化:
-  - 去掉 XGBackfill 双轨(不再需要独立回填)
-  - 去掉 PIT 时间契约(无训练集要防泄漏)
-  - 保留核心清洗契约(队名归一、日期解析、数值范围)
+    - 去掉 XGBackoff 双轨(不再需要独立回填)
+    - 去掉 PIT 时间契约(无训练集要防泄漏)
+    - 保留核心清洗契约(队名归一、日期解析、数值范围)
 """
 from __future__ import annotations
 
@@ -90,7 +90,10 @@ def derive_season_label(date: datetime) -> str:
 
 
 def _parse_date(value) -> datetime | None:
-    """日期解析 → UTC datetime(带 tzinfo)。"""
+    """日期解析 → UTC datetime(带 tzinfo)。
+
+    P2-2: 解析失败时记录 warning,避免静默丢数据而无感知。
+    """
     if value in (None, ""):
         return None
     if isinstance(value, (int, float)):
@@ -111,6 +114,8 @@ def _parse_date(value) -> datetime | None:
             return datetime.strptime(s[:19], fmt).replace(tzinfo=timezone.utc)
         except ValueError:
             continue
+    # P2-2 修复: 记录被丢弃的原始值,便于排查数据源格式变更
+    logger.warning("_parse_date failed, dropping record: %r", value)
     return None
 
 
@@ -204,6 +209,6 @@ def normalize_understat(raw: dict, league_type: str) -> NormalizedMatch | None:
         away_team=away,
         match_status="finished",
         season_label=derive_season_label(dt),
-        home_xg=_to_float(home_xg),
-        away_xg=_to_float(away_xg),
+        home_xg=home_xg,
+        away_xg=away_xg,
     )

src/data/understat.py

@@ -10,9 +10,10 @@ import json
 import logging
 import random
 import re
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 
-from sqlalchemy import func, select
+from sqlalchemy import select
+from sqlalchemy.orm import selectinload
 
 from src.core.http_client import get_client
 from src.data.config import FDCO_TO_UNDERSTAT, LEAGUE_NAMES
@@ -76,6 +77,18 @@ async def fetch_understat(league_code: str, season: int) -> list[dict]:
     return data
 
 
+def _match_key(home_team_id: int, away_team_id: int, match_date) -> tuple[int, int, str]:
+    """比赛去重键:(主队, 客队, 天级日期 ISO 字符串)。
+
+    统一在这里构造,避免"预加载时用 str(date)、写入时用 isoformat()"这类
+    隐式格式依赖 —— 两者当前恰好相等,但一旦有人改动其一就会静默失配,
+    导致所有比赛被判为不存在而重复插入。
+    """
+    if hasattr(match_date, "date") and callable(match_date.date):
+        match_date = match_date.date()
+    return (home_team_id, away_team_id, match_date.isoformat() if match_date is not None else "")
+
+
 @register
 class UnderstatSource:
     """understat xG 数据源(实现 DataSource 协议)。"""
@@ -86,8 +99,10 @@ class UnderstatSource:
         """采集 understat xG → 回填到现有 Match。只回填 xG 字段,不创建新 Match。
 
         注意: 本方法不控制事务(commit/rollback),由调用方通过 UnitOfWork 控制。
+
+        P1-3: 批量查询优化,将单赛季 380 场 × 3 次 DB 往返降为 3 次查询。
         """
-        from src.db.repositories import LeagueRepository, MatchRepository, TeamRepository
+        from src.db.repositories import LeagueRepository, TeamRepository
 
         result = {"updated": 0, "skipped": 0, "unmatched": 0, "errors": []}
 
@@ -101,7 +116,6 @@ class UnderstatSource:
         # 使用 Repository
         league_repo = LeagueRepository(db)
         team_repo = TeamRepository(db)
-        match_repo = MatchRepository(db)
 
         # 查联赛
         league_obj = await league_repo.get_by_code(league)
@@ -109,6 +123,9 @@ class UnderstatSource:
             result["errors"].append(f"league {league} not found in DB")
             return result
 
+        # === 批量优化: 一次规范化,收集球队名和日期 ===
+        normalized_matches: list = []
+        all_team_names: set[str] = set()
         for raw in raw_matches:
             if not raw.get("isResult"):
                 continue
@@ -120,17 +137,46 @@ class UnderstatSource:
             except Exception as e:
                 result["errors"].append(f"normalize: {e}")
                 continue
+            normalized_matches.append((nm, raw))
+            all_team_names.add(nm.home_team)
+            all_team_names.add(nm.away_team)
 
-            # 匹配已有 Match(天级) - 使用 Repository
-            home_team = await team_repo.get_by_name(nm.home_team)
-            away_team = await team_repo.get_by_name(nm.away_team)
-            if home_team is None or away_team is None:
+        if not normalized_matches:
+            return result
+
+        # === 批量查询球队(1 次 DB 往返) ===
+        team_name_to_id = {}
+        if all_team_names:
+            teams = await team_repo.get_all_by_names(list(all_team_names))
+            team_name_to_id = {name: team.id for name, team in teams.items()}
+
+        # === 批量查询已有比赛(1 次 DB 往返,按日期范围) ===
+        match_dict: dict[tuple, Match] = {}
+        dates = [nm.date for nm, _ in normalized_matches if nm.date is not None]
+        if dates:
+            min_dt = min(dates) - timedelta(days=30)
+            max_dt = max(dates) + timedelta(days=30)
+            stmt = (
+                select(Match)
+                .options(selectinload(Match.stats))
+                .where(Match.league_id == league_obj.id)
+                .where(Match.match_date >= min_dt)
+                .where(Match.match_date <= max_dt)
+            )
+            for m in (await db.execute(stmt)).scalars():
+                key = _match_key(m.home_team_id, m.away_team_id, m.match_date_date)
+                match_dict[key] = m
+
+        # === 内存匹配 + 回填 xG ===
+        for nm, raw in normalized_matches:
+            home_team_id = team_name_to_id.get(nm.home_team)
+            away_team_id = team_name_to_id.get(nm.away_team)
+            if home_team_id is None or away_team_id is None:
                 result["unmatched"] += 1
                 continue
 
-            existing = await match_repo.find_by_teams_and_date(
-                league_obj.id, home_team.id, away_team.id, nm.date
-            )
+            match_key = _match_key(home_team_id, away_team_id, nm.date)
+            existing = match_dict.get(match_key)
             if existing is None:
                 result["unmatched"] += 1
                 continue

src/db/models.py

@@ -14,6 +14,7 @@ from sqlalchemy import (
     Integer,
     String,
     Text,
+    UniqueConstraint,
     func,
 )
 from sqlalchemy.dialects.postgresql import JSONB
@@ -198,6 +199,11 @@ class Prediction(Base):
     match: Mapped[Match] = relationship(back_populates="predictions")
 
     __table_args__ = (
+        # P1-6: 数据库级唯一约束,防止同一 match+provider+model 产生重复预测
+        UniqueConstraint(
+            "match_id", "provider", "model",
+            name="uq_predictions_match_provider_model",
+        ),
         Index("ix_predictions_match", "match_id"),
         Index("ix_predictions_provider_model", "provider", "model"),
         # 数据截止时间过滤查询用(按 prediction_cutoff_at 取「赛前已生成」的预测)

src/db/repositories.py

@@ -5,7 +5,8 @@ Repository 只负责查询,不负责事务提交。
 """
 from __future__ import annotations
 
-from sqlalchemy import func, select
+from datetime import datetime
+from sqlalchemy import select
 from sqlalchemy.orm import selectinload
 from sqlalchemy.ext.asyncio import AsyncSession
 
@@ -41,9 +42,17 @@ class MatchRepository:
 
         预加载 stats:调用方(understat 回填)会读取 existing.stats,
         async session 下惰性加载会抛 MissingGreenlet。
+
+        P2-3: 使用 match_date_date(已建索引)做等值匹配,避免 func.date()
+        导致的全表扫描。
         """
-        if hasattr(date, "date"):
+        if isinstance(date, datetime):
             date = date.date()
+        elif hasattr(date, "date"):
+            date = date.date()
+        else:
+            # 字符串等其它格式,尝试转换
+            date = datetime.fromisoformat(str(date)).date()
 
         stmt = (
             select(Match)
@@ -51,7 +60,7 @@ class MatchRepository:
             .where(Match.league_id == league_id)
             .where(Match.home_team_id == home_team_id)
             .where(Match.away_team_id == away_team_id)
-            .where(func.date(Match.match_date) == date)
+            .where(Match.match_date_date == date)
         )
         return (await self._session.execute(stmt)).scalar_one_or_none()
 

src/db/unit_of_work.py

@@ -9,12 +9,16 @@ from __future__ import annotations
 
 from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
+from typing import TYPE_CHECKING
 
 from src.db.base import AsyncSessionLocal
 
+if TYPE_CHECKING:
+    from sqlalchemy.ext.asyncio import AsyncSession
+
 
 @asynccontextmanager
-async def get_uow() -> AsyncIterator[AsyncSessionLocal]:
+async def get_uow() -> AsyncIterator[AsyncSession]:
     """创建新的工作单元(用于非路由上下文)。
 
     用法:

src/llm/context_builder.py

@@ -1,16 +1,22 @@
 """上下文构建器:数据切片 + 拼接。
 
 架构:
-  - match_header: 比赛基础信息(对阵双方/联赛/时间)
-  - 切片函数: 每个领域 agent 一个数据切片(h2h / form / standings / injuries / xg)
-  - build_context: 单 agent 路径,拼接全部切片(行为与旧版一致)
+    - match_header: 比赛基础信息(对阵双方/联赛/时间)
+    - 切片函数: 每个领域 agent 一个数据切片(h2h / form / standings / injuries / xg)
+    - build_context: 单 agent 路径,拼接全部切片(行为与旧版一致)
 
 multi-agent 路径由 agents/orchestrator.py 调用切片函数,每个专家只拿自己的切片。
+
+性能说明:
+    build_context 创建一个共享 session 并传给所有切片函数,
+    避免每个切片独立创建 session —— 回测 20 场并发时,
+    5 个切片 × 20 场 = 100 个连接会耗尽连接池(pool_size=15)。
 """
 from __future__ import annotations
 
 import logging
 from dataclasses import dataclass
+from typing import TYPE_CHECKING
 
 from sqlalchemy import select
 from sqlalchemy.orm import selectinload
@@ -18,6 +24,9 @@ from sqlalchemy.orm import selectinload
 from src.db.base import AsyncSessionLocal
 from src.db.models import Match
 
+if TYPE_CHECKING:
+    from sqlalchemy.ext.asyncio import AsyncSession
+
 logger = logging.getLogger(__name__)
 
 
@@ -80,11 +89,19 @@ class MatchHeader:
     league_id: int
 
 
-async def load_match_header(match_id: int) -> MatchHeader:
-    """加载比赛头信息(各 agent 共用)。"""
-    async with AsyncSessionLocal() as db:
+async def load_match_header(match_id: int, db: AsyncSession | None = None) -> MatchHeader:
+    """加载比赛头信息(各 agent 共用)。
+
+    Args:
+        match_id: 比赛 ID
+        db: 可选的共享 session。不传则自建(向后兼容)。
+    """
+    if db is not None:
         m = await _load_match(db, match_id)
         return _to_header(m)
+    async with AsyncSessionLocal() as new_db:
+        m = await _load_match(new_db, match_id)
+        return _to_header(m)
 
 
 def _to_header(m: Match) -> MatchHeader:
@@ -114,10 +131,16 @@ def header_text(h: MatchHeader) -> str:
 # 切片函数: 每个领域 agent 一个
 # ============================================================
 
-async def h2h_slice(header: MatchHeader, *, limit: int = 8, before=None) -> SliceResult:
-    """E - 历史交锋切片: 过去数年 + 近期交手数据,提取交手规律。before=match_date 用于回测。"""
-    async with AsyncSessionLocal() as db:
+async def h2h_slice(header: MatchHeader, *, limit: int = 8, before=None, db: AsyncSession | None = None) -> SliceResult:
+    """E - 历史交锋切片: 过去数年 + 近期交手数据,提取交手规律。before=match_date 用于回测。
+
+    db: 可选共享 session,避免每个切片独立建连(见模块 docstring)。
+    """
+    if db is not None:
         h2h = await _get_h2h(db, header.home_team_id, header.away_team_id, before=before, limit=limit)
+    else:
+        async with AsyncSessionLocal() as new_db:
+            h2h = await _get_h2h(new_db, header.home_team_id, header.away_team_id, before=before, limit=limit)
     lines = [f"── 历史交锋(近 {limit} 次) ──"]
     n_with_score = 0
     if h2h:
@@ -141,11 +164,18 @@ async def h2h_slice(header: MatchHeader, *, limit: int = 8, before=None) -> Slic
     return SliceResult(text="\n".join(lines), has_data=n_with_score > 0, n_records=n_with_score)
 
 
-async def form_slice(header: MatchHeader, *, limit: int = 5, before=None) -> SliceResult:
-    """A - 近期状态切片: 两队近 N 场赛果、关键事件、走势判断。before=match_date 用于回测。"""
-    async with AsyncSessionLocal() as db:
+async def form_slice(header: MatchHeader, *, limit: int = 5, before=None, db: AsyncSession | None = None) -> SliceResult:
+    """A - 近期状态切片: 两队近 N 场赛果、关键事件、走势判断。before=match_date 用于回测。
+
+    db: 可选共享 session,避免每个切片独立建连(见模块 docstring)。
+    """
+    if db is not None:
         home_form = await _get_form(db, header.home_team_id, before=before, limit=limit)
         away_form = await _get_form(db, header.away_team_id, before=before, limit=limit)
+    else:
+        async with AsyncSessionLocal() as new_db:
+            home_form = await _get_form(new_db, header.home_team_id, before=before, limit=limit)
+            away_form = await _get_form(new_db, header.away_team_id, before=before, limit=limit)
     lines = []
     n_scored = 0
     for label, name, form, side in (
@@ -175,11 +205,18 @@ async def form_slice(header: MatchHeader, *, limit: int = 5, before=None) -> Sli
     return SliceResult(text="\n".join(lines), has_data=n_scored > 0, n_records=n_scored)
 
 
-async def stats_slice(header: MatchHeader, *, limit: int = 10, before=None) -> SliceResult:
-    """B - 攻防数据切片: 进球、射门、控球,评估攻防强度。before=match_date 用于回测。"""
-    async with AsyncSessionLocal() as db:
+async def stats_slice(header: MatchHeader, *, limit: int = 10, before=None, db: AsyncSession | None = None) -> SliceResult:
+    """B - 攻防数据切片: 进球、射门、控球,评估攻防强度。before=match_date 用于回测。
+
+    db: 可选共享 session,避免每个切片独立建连(见模块 docstring)。
+    """
+    if db is not None:
         home_form = await _get_form(db, header.home_team_id, before=before, limit=limit)
         away_form = await _get_form(db, header.away_team_id, before=before, limit=limit)
+    else:
+        async with AsyncSessionLocal() as new_db:
+            home_form = await _get_form(new_db, header.home_team_id, before=before, limit=limit)
+            away_form = await _get_form(new_db, header.away_team_id, before=before, limit=limit)
     lines = [f"── 攻防数据(近 {limit} 场) ──"]
     n_total = 0
     for label, name, form, side in (
@@ -221,11 +258,18 @@ async def stats_slice(header: MatchHeader, *, limit: int = 10, before=None) -> S
     return SliceResult(text="\n".join(lines), has_data=n_total > 0, n_records=n_total)
 
 
-async def home_away_slice(header: MatchHeader, *, limit: int = 10, before=None) -> SliceResult:
-    """C - 主客因素切片: 主场战绩 vs 客场战绩,评估地理优势影响。before=match_date 用于回测。"""
-    async with AsyncSessionLocal() as db:
+async def home_away_slice(header: MatchHeader, *, limit: int = 10, before=None, db: AsyncSession | None = None) -> SliceResult:
+    """C - 主客因素切片: 主场战绩 vs 客场战绩,评估地理优势影响。before=match_date 用于回测。
+
+    db: 可选共享 session,避免每个切片独立建连(见模块 docstring)。
+    """
+    if db is not None:
         home_home = await _get_home_away(db, header.home_team_id, "home", before=before, limit=limit)
         away_away = await _get_home_away(db, header.away_team_id, "away", before=before, limit=limit)
+    else:
+        async with AsyncSessionLocal() as new_db:
+            home_home = await _get_home_away(new_db, header.home_team_id, "home", before=before, limit=limit)
+            away_away = await _get_home_away(new_db, header.away_team_id, "away", before=before, limit=limit)
     lines = ["── 主客因素 ──"]
     n_total = 0
     for label, name, matches, side in (
@@ -255,17 +299,22 @@ async def home_away_slice(header: MatchHeader, *, limit: int = 10, before=None)
     return SliceResult(text="\n".join(lines), has_data=n_total > 0, n_records=n_total)
 
 
-async def injuries_slice(header: MatchHeader, *, before=None) -> SliceResult:
+async def injuries_slice(header: MatchHeader, *, before=None, db: AsyncSession | None = None) -> SliceResult:
     """D - 阵容完整性切片: 伤停与停赛名单,评估战力缺失程度。
 
     before=cutoff: 只使用 cutoff 之前已采集的伤停数据,防回测泄漏。
+    db: 可选共享 session(见模块 docstring)。
     """
     from src.data.injuries import get_injuries_for_match
 
     cutoff = before or header.match_dt
-    async with AsyncSessionLocal() as db:
+    if db is not None:
         home_injuries = await get_injuries_for_match(db, header.home_team_id, cutoff, as_of=cutoff)
         away_injuries = await get_injuries_for_match(db, header.away_team_id, cutoff, as_of=cutoff)
+    else:
+        async with AsyncSessionLocal() as new_db:
+            home_injuries = await get_injuries_for_match(new_db, header.home_team_id, cutoff, as_of=cutoff)
+            away_injuries = await get_injuries_for_match(new_db, header.away_team_id, cutoff, as_of=cutoff)
 
     lines = ["── 阵容完整性 ──"]
     n_records = 0
@@ -298,41 +347,44 @@ async def build_context(match_id: int, *, form_last: int = 5, h2h_last: int = 5,
     不再靠文案子串匹配(见审查报告 P2-1)。
 
     P2-6: backtest=True 时 cutoff = match_date - 1天,确保只用赛前数据。
+
+    P1-1: 使用单个共享 session 贯穿所有切片查询,避免连接池耗尽。
     """
-    header = await load_match_header(match_id)
-    # P2-6: 回测模式下 cutoff 提前 1 天,防止比赛日数据泄漏
-    cutoff = header.match_dt
-    if backtest and header.match_dt:
-        from datetime import timedelta
-        cutoff = header.match_dt - timedelta(days=1)
-    parts = [header_text(header), ""]
+    async with AsyncSessionLocal() as db:
+        header = await load_match_header(match_id, db=db)
+        # P2-6: 回测模式下 cutoff 提前 1 天,防止比赛日数据泄漏
+        cutoff = header.match_dt
+        if backtest and header.match_dt:
+            from datetime import timedelta
+            cutoff = header.match_dt - timedelta(days=1)
+        parts = [header_text(header), ""]
 
-    form_res = await form_slice(header, limit=form_last, before=cutoff)
-    parts.append(form_res.text)
-    parts.append("")
+        form_res = await form_slice(header, limit=form_last, before=cutoff, db=db)
+        parts.append(form_res.text)
+        parts.append("")
 
-    h2h_res = await h2h_slice(header, limit=h2h_last, before=cutoff)
-    parts.append(h2h_res.text)
-    parts.append("")
+        h2h_res = await h2h_slice(header, limit=h2h_last, before=cutoff, db=db)
+        parts.append(h2h_res.text)
+        parts.append("")
 
-    stats_res = await stats_slice(header, before=cutoff)
-    parts.append(stats_res.text)
-    parts.append("")
+        stats_res = await stats_slice(header, before=cutoff, db=db)
+        parts.append(stats_res.text)
+        parts.append("")
 
-    home_away_res = await home_away_slice(header, before=cutoff)
-    parts.append(home_away_res.text)
-    parts.append("")
+        home_away_res = await home_away_slice(header, before=cutoff, db=db)
+        parts.append(home_away_res.text)
+        parts.append("")
 
-    injuries_res = await injuries_slice(header, before=cutoff)
-    parts.append(injuries_res.text)
+        injuries_res = await injuries_slice(header, before=cutoff, db=db)
+        parts.append(injuries_res.text)
 
-    return MatchContext(
-        match_id=match_id,
-        text="\n".join(parts),
-        has_stats=form_res.has_data or stats_res.has_data,
-        has_injuries=injuries_res.has_data,
-        match_dt=header.match_dt,
-    )
+        return MatchContext(
+            match_id=match_id,
+            text="\n".join(parts),
+            has_stats=form_res.has_data or stats_res.has_data,
+            has_injuries=injuries_res.has_data,
+            match_dt=header.match_dt,
+        )
 
 
 # ============================================================

src/llm/predict.py

@@ -23,8 +23,9 @@ _PROMPT_DIR = Path(__file__).resolve().parent / "prompts"
 
 # ── LLM 响应缓存(match+provider+model+version → 结果) ──
 _CACHE_TTL_SEC = 300  # 5 分钟
+# P1-5: 缓存仅在 asyncio 协程内同步访问(dict 操作 GIL 原子),无需 threading.Lock。
+# 删除 _cache_lock,避免同步锁阻塞事件循环;dict 的 get/set 在 CPython 下原子。
 _cache: dict[str, tuple[float, PredictResult]] = {}
-_cache_lock = Lock()
 
 
 def _cache_key(match_id: int, provider: str, model: str, version: str, tpl_hash: str) -> str:
@@ -38,20 +39,21 @@ def _cache_key(match_id: int, provider: str, model: str, version: str, tpl_hash:
 
 
 def _get_cached(match_id: int, provider: str, model: str, version: str, tpl_hash: str) -> PredictResult | None:
+    # P1-5: 无锁访问。dict get/del 在 CPython GIL 下原子,且无 await 穿插。
     key = _cache_key(match_id, provider, model, version, tpl_hash)
-    with _cache_lock:
-        if key in _cache:
-            ts, result = _cache[key]
-            if time.time() - ts < _CACHE_TTL_SEC:
-                return result
-            del _cache[key]
+    entry = _cache.get(key)
+    if entry is not None:
+        ts, result = entry
+        if time.time() - ts < _CACHE_TTL_SEC:
+            return result
+        _cache.pop(key, None)
     return None
 
 
 def _set_cached(match_id: int, provider: str, model: str, version: str, tpl_hash: str, result: PredictResult) -> None:
+    # P1-5: 无锁写入。同上,dict set 原子。
     key = _cache_key(match_id, provider, model, version, tpl_hash)
-    with _cache_lock:
-        _cache[key] = (time.time(), result)
+    _cache[key] = (time.time(), result)
 
 
 def clear_prompt_cache() -> None: