Author SHA1 Message Date
shangfangjian a0ce2e2a6a feat: 数据管线 P2 优化 — 血缘写入 + 质量监控 + 缓存清理 + 重试 worker
P2-1: DataLineage 血缘写入(bzzoiro/understat Bronze→Silver 全链路)
P2-2: DataQualityCheck 质量检查写入(行计数异常检测)
P2-3: RateLimitedClient 集成到 bzzoiro 采集
P2-4: injuries 缓存过期清理(启动时扫描删除 >1h 文件)
P2-5: IngestFailure 重试 worker(FastAPI startup 注册)

新增文件:
  - src/data/retry_worker.py (死信表重试 sweep)
2026-09-16 15:55:08 +08:00
shangfangjian 5de8ffb09d feat: 数据管线架构优化 — Bronze 层 + 死信队列 + 令牌桶 + 血缘追踪
P0: injuries 缓存原子写(tempfile+os.replace) + TTL 分级 + asyncio.Lock 并发安全
P1: 引入 Bronze 层 RawEvent 表(原始事件存档,不可变)
P1: IngestFailure 死信表(失败持久化,支持重试恢复)
P1: understat 改为 xG 覆盖更新模式 + xG 来源追踪字段
P1: 令牌桶限流器(TokenBucket)替换固定 sleep
P1: DataQualityCheck 数据质量监控表
P1: DataLineage 血缘追踪表
P2: 回测并发控制 Semaphore(3)

新增文件:
  - src/data/rate_limiter.py (令牌桶限流器)
  - alembic/versions/0008 (4 张新表迁移)
  - alembic/versions/0009 (MatchStats xG 字段迁移)
2026-09-16 14:12:42 +08:00
shangfangjian 2fd8a80ad9 revert: 移除手动创建的 experts 目录
Octop 为每个专家 Agent 自带存储后端,无需在项目代码中创建
2026-09-16 13:37:00 +08:00
shangfangjian 5676198392 chore: 添加专家工作区目录结构
为代码审查、数据工程、后端架构、安全工程四个角色
建立专属工作区,用于持久化审查报告、设计文档和知识积累
2026-09-16 13:34:42 +08:00
10 changed files with 1182 additions and 30 deletions
@@ -0,0 +1,121 @@
"""新增 Bronze 层 + 死信表 + 数据质量表 + 血缘表
Revision ID: 0008_raw_event_and_ingest_failure
Revises: 0007_predictions_unique_constraint
Create Date: 2026-09-17
架构审查报告 P1 实施:
- raw_events: Bronze 层,不可变原始采集记录
- ingest_failures: 采集失败死信表
- data_quality_checks: 数据质量检查结果记录
- data_lineage: ETL 全过程元数据血缘追踪
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import JSONB
# revision identifiers, used by Alembic.
revision: str = '0008_raw_event_and_ingest_failure'
down_revision: Union[str, None] = '0007_predictions_unique_constraint'
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ── raw_events: Bronze 层原始记录 ──
op.create_table(
"raw_events",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("source_system", sa.String(30), nullable=False),
sa.Column("source_record_id", sa.String(100), nullable=False),
sa.Column("raw_payload", JSONB(), nullable=False),
sa.Column("ingested_at", sa.DateTime(timezone=True), nullable=False),
sa.Column("ingest_batch_id", sa.String(64), nullable=True),
)
op.create_index("ix_raw_events_batch", "raw_events", ["ingest_batch_id"])
op.create_index("ix_raw_events_source_ingested", "raw_events", ["source_system", "ingested_at"])
op.create_unique_constraint("uq_raw_events_source_record", "raw_events", ["source_system", "source_record_id"])
# ── ingest_failures: 采集失败死信表 ──
op.create_table(
"ingest_failures",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("source_system", sa.String(30), nullable=False),
sa.Column("entity_type", sa.String(30), nullable=False),
sa.Column("source_record_id", sa.String(100), nullable=True),
sa.Column("error_type", sa.String(50), nullable=False),
sa.Column("error_detail", sa.Text(), nullable=True),
sa.Column("raw_payload", JSONB(), nullable=True),
sa.Column("retry_count", sa.Integer(), nullable=False, server_default="0"),
sa.Column("next_retry_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("status", sa.String(20), nullable=False, server_default="pending"),
sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
sa.Column("resolved_at", sa.DateTime(timezone=True), nullable=True),
)
op.create_index("ix_ingest_failures_status_next_retry", "ingest_failures", ["status", "next_retry_at"])
op.create_index("ix_ingest_failures_source", "ingest_failures", ["source_system", "entity_type"])
op.create_check_constraint("ck_ingest_failures_status", "ingest_failures",
"status IN ('pending', 'retrying', 'resolved', 'abandoned')")
op.create_check_constraint("ck_ingest_failures_retry_nonneg", "ingest_failures", "retry_count >= 0")
# ── data_quality_checks: 数据质量检查记录 ──
op.create_table(
"data_quality_checks",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("check_name", sa.String(100), nullable=False),
sa.Column("entity_type", sa.String(30), nullable=False),
sa.Column("entity_id", sa.String(50), nullable=True),
sa.Column("expected_value", sa.Text(), nullable=True),
sa.Column("actual_value", sa.Text(), nullable=True),
sa.Column("passed", sa.Boolean(), nullable=False),
sa.Column("severity", sa.String(10), nullable=False, server_default="warning"),
sa.Column("detail", sa.Text(), nullable=True),
sa.Column("checked_at", sa.DateTime(timezone=True), nullable=False),
)
op.create_index("ix_dqc_check_time", "data_quality_checks", ["check_name", "checked_at"])
op.create_index("ix_dqc_entity", "data_quality_checks", ["entity_type", "entity_id"])
op.create_index("ix_dqc_severity_passed", "data_quality_checks", ["severity", "passed"])
op.create_check_constraint("ck_dqc_severity", "data_quality_checks",
"severity IN ('info', 'warning', 'critical')")
# ── data_lineage: ETL 血缘追踪 ──
op.create_table(
"data_lineage",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("source_system", sa.String(30), nullable=False),
sa.Column("source_record_id", sa.String(100), nullable=False),
sa.Column("target_table", sa.String(50), nullable=False),
sa.Column("target_id", sa.Integer(), nullable=True),
sa.Column("transform_name", sa.String(100), nullable=False),
sa.Column("transform_detail", sa.Text(), nullable=True),
sa.Column("batch_id", sa.String(64), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), nullable=False),
)
op.create_index("ix_lineage_source", "data_lineage", ["source_system", "source_record_id"])
op.create_index("ix_lineage_target", "data_lineage", ["target_table", "target_id"])
op.create_index("ix_lineage_batch", "data_lineage", ["batch_id"])
def downgrade() -> None:
# 逆序删除
op.drop_index("ix_lineage_batch", table_name="data_lineage")
op.drop_index("ix_lineage_target", table_name="data_lineage")
op.drop_index("ix_lineage_source", table_name="data_lineage")
op.drop_table("data_lineage")
op.drop_index("ix_dqc_severity_passed", table_name="data_quality_checks")
op.drop_index("ix_dqc_entity", table_name="data_quality_checks")
op.drop_index("ix_dqc_check_time", table_name="data_quality_checks")
op.drop_table("data_quality_checks")
op.drop_index("ix_ingest_failures_source", table_name="ingest_failures")
op.drop_index("ix_ingest_failures_status_next_retry", table_name="ingest_failures")
op.drop_table("ingest_failures")
op.drop_constraint("uq_raw_events_source_record", table_name="raw_events", type_="unique")
op.drop_index("ix_raw_events_source_ingested", table_name="raw_events")
op.drop_index("ix_raw_events_batch", table_name="raw_events")
op.drop_table("raw_events")
@@ -0,0 +1,35 @@
"""MatchStats 新增 xG 追踪字段
Revision ID: 0009_match_stats_xg_fields
Revises: 0008_raw_event_and_ingest_failure
Create Date: 2026-09-17
架构审查报告 P1-4 实施:
understat 允许纠正旧 xG 值。新增字段追踪 xG 具体来源和更新时间,
实现全量覆盖模式:当 understat 数据更新时覆盖旧值而非跳过。
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = '0009_match_stats_xg_fields'
down_revision: Union[str, None] = '0008_raw_event_and_ingest_failure'
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
op.add_column("match_stats", sa.Column("xg_source", sa.String(30), nullable=True))
op.add_column("match_stats", sa.Column("xg_updated_at", sa.DateTime(timezone=True), nullable=True))
op.add_column("match_stats", sa.Column("xg_source_record_id", sa.String(100), nullable=True))
op.create_index("ix_match_stats_xg_source", "match_stats", ["xg_source", "xg_updated_at"])
def downgrade() -> None:
op.drop_index("ix_match_stats_xg_source", table_name="match_stats")
op.drop_column("match_stats", "xg_source_record_id")
op.drop_column("match_stats", "xg_updated_at")
op.drop_column("match_stats", "xg_source")
+3
View File
@@ -16,6 +16,9 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
from src.db.base import init_db
from src.core.http_client import close_client
await init_db() # 验证连接,不建表
# P2-5: 启动时执行一次 ingest failure 重试清理
from src.data.retry_worker import run_retry_worker
await run_retry_worker()
yield
await close_client()
+233 -6
View File
@@ -2,6 +2,12 @@
迁移自旧项目 app/data/sources/bzzoiro/,改成 async + 简化入库。
使用 Repository 模式进行数据访问,不直接控制事务。
改进(P1):
- Bronze 层集成:采集后先存 RawEvent,再规范化
- 死信表集成:采集/规范化失败写 IngestFailure
- 令牌桶限流:替换固定 REQUEST_INTERVAL sleep
- 数据血缘:记录 ETL 全过程
"""
from __future__ import annotations
@@ -9,6 +15,7 @@ import asyncio
import json as _json
import logging
import random
import uuid
from collections.abc import Iterable
from datetime import datetime, timezone
@@ -18,11 +25,26 @@ from src.core.config import settings
from src.core.http_client import get_client
from src.data.config import BZZOIRO_LEAGUE_IDS, LEAGUE_COUNTRIES, LEAGUE_NAMES, REQUEST_INTERVAL
from src.data.normalize import normalize_bzzoiro
from src.data.rate_limiter import RateLimitedClient, TokenBucket
from src.data.sources import register
from src.db.models import League, Match, MatchStats, Team
from src.db.models import DataLineage, DataQualityCheck, IngestFailure, League, Match, MatchStats, RawEvent, Team
logger = logging.getLogger(__name__)
# 令牌桶限流器:替代固定 sleep,rate 根据 REQUEST_INTERVAL 计算
_bzzoiro_limiter = TokenBucket(rate=1.0 / REQUEST_INTERVAL, capacity=3)
# P2-3: RateLimitedClient 包装,在 HTTP 调用层面透明限流
_bzzoiro_rl_client: RateLimitedClient | None = None
def _get_bzzoiro_rl_client() -> RateLimitedClient:
"""惰性初始化 RateLimitedClient(避免模块导入时创建 client)。"""
global _bzzoiro_rl_client
if _bzzoiro_rl_client is None:
client = get_client()
_bzzoiro_rl_client = RateLimitedClient(client, _bzzoiro_limiter)
return _bzzoiro_rl_client
def _to_date(value):
"""把 datetime / date / str 统一成 `date`。"""
@@ -60,8 +82,9 @@ async def _fetch_json_async(path: str, params: dict | None = None, max_retries:
last_exc: Exception | None = None
for attempt in range(max_retries):
try:
client = get_client()
resp = await client.get(url, headers=headers, params=params, timeout=30)
# P2-3: 使用 RateLimitedClient 包装 HTTP 调用,透明限流
rl_client = _get_bzzoiro_rl_client()
resp = await rl_client.get(url, headers=headers, params=params, timeout=30)
resp.raise_for_status()
return resp.json()
except Exception as e:
@@ -124,10 +147,141 @@ async def fetch_bzzoiro_events(
break
if len(batch) < limit:
break
await asyncio.sleep(REQUEST_INTERVAL)
# 令牌桶已在 _fetch_json_async 内部处理,这里不再需要固定 sleep
return rows
async def _write_bronze_events(db, raw_events: list[dict], batch_id: str) -> None:
"""将原始事件写入 Bronze 层(RawEvent 表)。
P2-1: 写入血缘记录,追踪 Bronze 层摄取过程。
"""
for raw in raw_events:
try:
source_record_id = str(raw.get("id", ""))
if not source_record_id:
# P1-fix: 不再静默跳过,记录到死信表
logger.warning("bzzoiro raw event missing id: %s", str(raw)[:200])
await _write_ingest_failure(
db, "bzzoiro", "match", "",
"normalize_error", "raw event missing id", raw,
)
continue
bronze = RawEvent(
source_system="bzzoiro",
source_record_id=source_record_id,
raw_payload=raw,
ingest_batch_id=batch_id,
)
db.add(bronze)
except Exception as e:
logger.warning("bzzoiro raw_event write failed: %s", e)
try:
await db.flush()
except Exception as e:
logger.warning("bzzoiro raw_events flush failed: %s", e)
# P2-1: 写入 Bronze 层血缘记录
for raw in raw_events:
source_record_id = str(raw.get("id", ""))
if not source_record_id:
continue
await _write_data_lineage(
db,
source_system="bzzoiro",
source_record_id=source_record_id,
target_table="raw_events",
transform_name="bronze_ingest",
batch_id=batch_id,
)
async def _write_ingest_failure(
db,
source_system: str,
entity_type: str,
source_record_id: str,
error_type: str,
error_detail: str,
raw_payload: dict | None,
) -> None:
"""写入采集失败到死信表(IngestFailure)。"""
try:
from datetime import timedelta
failure = IngestFailure(
source_system=source_system,
entity_type=entity_type,
source_record_id=source_record_id,
error_type=error_type,
error_detail=error_detail[:2000] if error_detail else None,
raw_payload=raw_payload,
status="pending",
next_retry_at=datetime.now(timezone.utc) + timedelta(minutes=5),
)
db.add(failure)
await db.flush()
except Exception:
logger.warning("bzzoiro ingest_failure write failed", exc_info=True)
async def _write_data_lineage(
db,
*,
source_system: str,
source_record_id: str,
target_table: str,
target_id: int | None = None,
transform_name: str,
transform_detail: str | None = None,
batch_id: str | None = None,
) -> None:
"""写入数据血缘记录(DataLineage 表)。"""
try:
lineage = DataLineage(
source_system=source_system,
source_record_id=source_record_id,
target_table=target_table,
target_id=target_id,
transform_name=transform_name,
transform_detail=transform_detail,
batch_id=batch_id,
)
db.add(lineage)
await db.flush()
except Exception:
logger.warning("bzzoiro data_lineage write failed", exc_info=True)
async def _write_data_quality_check(
db,
*,
check_name: str,
entity_type: str,
entity_id: str | None = None,
expected_value: str | None = None,
actual_value: str | None = None,
passed: bool,
severity: str = "warning",
detail: str | None = None,
) -> None:
"""写入数据质量检查结果(DataQualityCheck 表)。"""
try:
check = DataQualityCheck(
check_name=check_name,
entity_type=entity_type,
entity_id=entity_id,
expected_value=expected_value,
actual_value=actual_value,
passed=passed,
severity=severity,
detail=detail,
)
db.add(check)
await db.flush()
except Exception:
logger.warning("bzzoiro data_quality_check write failed", exc_info=True)
@register
class BzzoiroSource:
"""bzzoiro 数据源(实现 DataSource 协议)。"""
@@ -148,6 +302,7 @@ class BzzoiroSource:
注意: 本方法不控制事务(commit/rollback),由调用方通过 UnitOfWork 控制。
"""
result: dict = {"leagues": {}, "total_inserted": 0, "total_updated": 0, "errors": []}
batch_id = uuid.uuid4().hex[:16]
for code in leagues:
league_r: dict = {"inserted": 0, "updated": 0, "errors": []}
@@ -156,9 +311,17 @@ class BzzoiroSource:
except Exception as e:
logger.exception("bzzoiro fetch failed for %s", code)
league_r["errors"].append(f"fetch failed: {e}")
# 写死信表
await _write_ingest_failure(
db, "bzzoiro", "match", f"fetch_{code}_{batch_id}",
"fetch_error", str(e), {"league": code, "date_from": date_from, "date_to": date_to},
)
result["leagues"][code] = league_r
continue
# === Bronze 层:先存 RawEvent ===
await _write_bronze_events(db, raw_events, batch_id)
# 获取或创建联赛
stmt = select(League).where(League.code == code)
league = (await db.execute(stmt)).scalar_one_or_none()
@@ -185,6 +348,11 @@ class BzzoiroSource:
except Exception as e:
# P1-3: 统一使用 warning,不追加到 errors(仅运行时错误入 errors)
logger.warning("normalize skip: %s", e)
# 写死信表:规范化失败
await _write_ingest_failure(
db, "bzzoiro", "match", str(raw.get("id", "")),
"normalize_error", str(e), raw,
)
continue
normalized_matches.append((nm, raw))
all_team_names.add(nm.home_team)
@@ -255,6 +423,16 @@ class BzzoiroSource:
db.add(m)
await db.flush()
existing_matches[match_key] = m # 防止同批重复
# P2-1: Silver 层血缘 — Match 创建
await _write_data_lineage(
db,
source_system="bzzoiro",
source_record_id=str(raw.get("id", "")),
target_table="matches",
target_id=m.id,
transform_name="silver_upsert",
batch_id=batch_id,
)
if nm.home_xg is not None or nm.away_xg is not None:
now = datetime.now(timezone.utc)
stats = MatchStats(
@@ -273,11 +451,22 @@ class BzzoiroSource:
home_red_cards=nm.home_red_cards,
away_red_cards=nm.away_red_cards,
source="bzzoiro",
source_event_id=str(raw.get("id", "")),
source_record_id=str(raw.get("id", "")),
retrieved_at=now,
available_at=now,
)
db.add(stats)
await db.flush()
# P2-1: Silver 层血缘 — MatchStats 创建
await _write_data_lineage(
db,
source_system="bzzoiro",
source_record_id=str(raw.get("id", "")),
target_table="match_stats",
target_id=m.id,
transform_name="silver_upsert",
batch_id=batch_id,
)
league_r["inserted"] += 1
else:
# 已有比赛: 直接从内存获取对象更新(无需再查询)
@@ -298,13 +487,36 @@ class BzzoiroSource:
now = datetime.now(timezone.utc)
existing_match.stats = MatchStats(
match_id=existing_match.id,
home_xg=nm.home_xg,
away_xg=nm.away_xg,
home_shots=nm.home_shots,
away_shots=nm.away_shots,
home_shots_on_target=nm.home_shots_on_target,
away_shots_on_target=nm.away_shots_on_target,
home_corners=nm.home_corners,
away_corners=nm.away_corners,
home_possession=nm.home_possession,
home_yellow_cards=nm.home_yellow_cards,
away_yellow_cards=nm.away_yellow_cards,
home_red_cards=nm.home_red_cards,
away_red_cards=nm.away_red_cards,
source="bzzoiro",
source_event_id=str(raw.get("id", "")),
source_record_id=str(raw.get("id", "")),
retrieved_at=now,
available_at=now,
)
db.add(existing_match.stats)
await db.flush()
# P2-1: Silver 层血缘 — MatchStats 创建(更新路径)
await _write_data_lineage(
db,
source_system="bzzoiro",
source_record_id=str(raw.get("id", "")),
target_table="match_stats",
target_id=existing_match.id,
transform_name="silver_upsert",
batch_id=batch_id,
)
if existing_match.stats is not None:
for fld in ("home_xg", "away_xg", "home_shots", "away_shots",
"home_shots_on_target", "away_shots_on_target",
@@ -323,4 +535,19 @@ class BzzoiroSource:
result["leagues"][code] = league_r
result["total_inserted"] += league_r["inserted"]
result["total_updated"] += league_r["updated"]
# P2-2: 数据质量检查 — 行计数合理性(某联赛比赛数不应为 0)
total_records = league_r["inserted"] + league_r["updated"]
await _write_data_quality_check(
db,
check_name="bzzoiro_row_count",
entity_type="match",
entity_id=code,
expected_value=">=1",
actual_value=str(total_records),
passed=total_records > 0,
severity="critical" if total_records == 0 else "info",
detail=f"league={code} inserted={league_r['inserted']} updated={league_r['updated']}",
)
return result
+238 -10
View File
@@ -1,16 +1,25 @@
"""伤停数据采集器(api-football / api-sports.io)。
采集伤停数据并入库(injuries 表),供 injuries agent 使用。
改进(P0):
- 原子写缓存(tempfile + os.replace)
- TTL 分级:未来比赛 1h,当天 5min,历史 7day
- 文件锁防止并发写缓存冲突
- Bronze 层集成(RawEvent)
- 死信表集成(IngestFailure)
"""
from __future__ import annotations
import asyncio
import json
import logging
import os
import random
import tempfile
import time
from datetime import datetime, timezone
import uuid
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any
@@ -18,6 +27,7 @@ import httpx
from src.core.config import settings
from src.core.http_client import get_client
from src.db.models import DataQualityCheck
logger = logging.getLogger(__name__)
@@ -27,6 +37,138 @@ DEFAULT_HOST = "v3.football.api-sports.io"
# P2-3: 缓存目录改用系统临时目录,避免源码树内写入
_CACHE_DIR = Path(tempfile.gettempdir()) / "profeto_injuries"
# 模块级锁:防止并发写同一缓存文件
_cache_lock = asyncio.Lock()
def _sanitize_cache_component(value: str | int | None) -> str:
"""消毒缓存键组件,防止路径遍历。
只允许 [A-Za-z0-9_.-],其余字符替换为 '_'
"""
import re
s = str(value) if value is not None else "none"
return re.sub(r'[^A-Za-z0-9_.]', '_', s)[:60]
def _build_cache_key(prefix: str, *components: str | int | None) -> str:
"""构造安全的缓存文件名。"""
parts = [_sanitize_cache_component(c) for c in components]
return f"{prefix}_{'_'.join(parts)}.json"
def _compute_ttl_hours(date_str: str | None, fixture_id: int | None, league_id: int | None) -> float:
"""根据查询参数计算缓存 TTL(小时)。
TTL 分级策略:
- 未来比赛(date > now): 1 小时(赛前伤停变化频繁)
- 当天比赛(date == today): 5 分钟(赛中实时更新)
- 历史比赛(date < now): 7 天(历史数据不变)
- 无日期参数: 1 小时(保守策略)
"""
if date_str is None:
# 无日期参数(按 fixture_id 或 league_id 查询),保守 TTL
return 1.0
try:
query_date = datetime.strptime(date_str, "%Y-%m-%d").replace(tzinfo=timezone.utc)
now = datetime.now(timezone.utc)
today = now.date()
if query_date.date() > today:
return 1.0 # 未来
elif query_date.date() == today:
return 5.0 / 60 # 当天:5 分钟
else:
return 168.0 # 历史:7 天
except (ValueError, TypeError):
return 1.0 # 解析失败,保守 TTL
def _write_cache_atomic(cache_file: Path, data: Any) -> None:
"""原子写缓存文件。
使用 tempfile + os.replace 实现原子写,防止读到写了一半的文件。
配合模块级 asyncio.Lock,杜绝并发写冲突。
"""
cache_file.parent.mkdir(parents=True, exist_ok=True)
# 在同一目录创建临时文件(保证 os.replace 是原子操作)
fd, tmp_path = tempfile.mkstemp(
dir=str(cache_file.parent),
prefix=f".{cache_file.name}.tmp_",
)
try:
with os.fdopen(fd, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, default=str)
os.replace(tmp_path, cache_file)
except BaseException:
# 失败时清理临时文件
try:
os.unlink(tmp_path)
except OSError:
pass
raise
def _cleanup_expired_cache() -> int:
"""P2-4: 扫描缓存目录,删除过期的 .json 文件。
TTL 策略(保守取最大值,避免误删有效缓存):
- 最短 TTL 为 5 分钟(当天比赛),但清理阈值用 1 小时
- 超过 1 小时的缓存文件视为过期
Returns:
删除的文件数。
"""
import glob as _glob
cache_dir = _CACHE_DIR
if not cache_dir.exists():
return 0
removed = 0
max_ttl_seconds = 3600 # 1 小时(保守阈值,最短实际 TTL 5 分钟)
now_ts = time.time()
for cache_file in _glob.glob(str(cache_dir / "*.json")):
try:
file_age = now_ts - os.path.getmtime(cache_file)
if file_age > max_ttl_seconds:
os.unlink(cache_file)
removed += 1
except OSError:
continue
if removed > 0:
logger.info("injuries cache cleanup: removed %d expired files", removed)
return removed
async def _write_data_quality_check(
db,
*,
check_name: str,
entity_type: str,
entity_id: str | None = None,
expected_value: str | None = None,
actual_value: str | None = None,
passed: bool,
severity: str = "warning",
detail: str | None = None,
) -> None:
"""写入数据质量检查结果(DataQualityCheck 表)。"""
try:
check = DataQualityCheck(
check_name=check_name,
entity_type=entity_type,
entity_id=entity_id,
expected_value=expected_value,
actual_value=actual_value,
passed=passed,
severity=severity,
detail=detail,
)
db.add(check)
await db.flush()
except Exception:
logger.warning("injuries data_quality_check write failed", exc_info=True)
async def fetch_injuries(*, date: str | None = None, fixture_id: int | None = None, league_id: int | None = None) -> list[dict]:
"""采集伤停数据。
@@ -43,20 +185,25 @@ async def fetch_injuries(*, date: str | None = None, fixture_id: int | None = No
if not api_key:
raise RuntimeError("API_FOOTBALL_KEY 未设置")
# P2-4: 清理过期缓存文件
_cleanup_expired_cache()
cache_dir = _CACHE_DIR
cache_dir.mkdir(parents=True, exist_ok=True)
# 缓存命中 (7 天内有效)
cache_key = f"injuries_{date}_{fixture_id}_{league_id}.json"
# TTL 分级缓存
ttl_hours = _compute_ttl_hours(date, fixture_id, league_id)
# P0-fix: 消毒缓存键,防止路径遍历(date 参数可能含 '../' 等)
cache_key = _build_cache_key("injuries", date, fixture_id, league_id)
cache_file = cache_dir / cache_key
if cache_file.exists():
age_hours = (time.time() - cache_file.stat().st_mtime) / 3600
if age_hours < 168: # 7 天
logger.debug("injuries cache hit: %s (%.1fh old)", cache_key, age_hours)
if age_hours < ttl_hours:
logger.debug("injuries cache hit: %s (%.1fh old, ttl=%.2fh)", cache_key, age_hours, ttl_hours)
with open(cache_file, encoding="utf-8") as f:
return json.load(f)
else:
logger.debug("injuries cache expired: %s (%.1fh old)", cache_key, age_hours)
logger.debug("injuries cache expired: %s (%.1fh old, ttl=%.2fh)", cache_key, age_hours, ttl_hours)
headers = {
"x-apisports-key": api_key,
@@ -93,9 +240,9 @@ async def fetch_injuries(*, date: str | None = None, fixture_id: int | None = No
data = resp.json()
injuries = data.get("response", [])
# 写缓存
with open(cache_file, "w", encoding="utf-8") as f:
json.dump(injuries, ensure_ascii=False, default=str, fp=f)
# 原子写缓存 + 文件锁(防止并发写冲突)
async with _cache_lock:
_write_cache_atomic(cache_file, injuries)
return injuries
@@ -106,25 +253,64 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
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)。
P1 Bronze: 采集成功后先存 RawEvent,再规范化。
P1 死信: 采集/规范化失败时写 IngestFailure。
"""
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
from src.db.models import DataQualityCheck, Injury, IngestFailure, RawEvent, Team
result = {"count": 0, "inserted": 0, "errors": []}
batch_id = uuid.uuid4().hex[:16]
try:
raw_injuries = await fetch_injuries(date=date)
except Exception as e:
logger.exception("injuries fetch failed")
result["errors"].append(f"fetch failed: {e}")
# 写死信表(IngestFailure)
try:
failure = IngestFailure(
source_system="api-football",
entity_type="injury",
source_record_id=f"fetch_{batch_id}",
error_type="fetch_error",
error_detail=str(e)[:2000],
raw_payload={"date": date},
status="pending",
next_retry_at=datetime.now(timezone.utc) + timedelta(minutes=5),
)
db.add(failure)
await db.flush()
except Exception:
logger.warning("failed to write fetch error to ingest_failures", exc_info=True)
return result
result["count"] = len(raw_injuries)
# === Bronze 层:写 RawEvent ===
for raw in raw_injuries:
try:
player = raw.get("player", {}) or {}
fixture = raw.get("fixture", {}) or {}
source_record_id = f"inj_{player.get('id')}_{fixture.get('id')}"
bronze = RawEvent(
source_system="api-football",
source_record_id=source_record_id,
raw_payload=raw,
ingest_batch_id=batch_id,
)
db.add(bronze)
except Exception as e:
logger.warning("raw_event write failed for injury: %s", e)
try:
await db.flush()
except Exception as e:
logger.warning("raw_events flush failed: %s", e)
# 预加载所有球队(用于按名匹配)
teams = (await db.execute(select(Team))).scalars().all()
team_by_name = {t.name: t.id for t in teams}
@@ -132,6 +318,7 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
# 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] = []
parse_failures: list[dict] = [] # 规范化失败的原始数据,用于写死信表
for raw in raw_injuries:
try:
player = raw.get("player", {}) or {}
@@ -176,6 +363,31 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
})
except Exception as e:
result["errors"].append(f"parse error: {e}")
parse_failures.append({"raw": raw, "error": str(e)})
# 写规范化失败到死信表
for fail in parse_failures:
try:
raw = fail["raw"]
player = raw.get("player", {}) or {}
failure = IngestFailure(
source_system="api-football",
entity_type="injury",
source_record_id=f"inj_{player.get('id', 'unknown')}",
error_type="normalize_error",
error_detail=fail["error"][:2000],
raw_payload=raw,
status="pending",
next_retry_at=datetime.now(timezone.utc) + timedelta(minutes=5),
)
db.add(failure)
except Exception:
logger.warning("failed to write parse error to ingest_failures", exc_info=True)
if parse_failures:
try:
await db.flush()
except Exception:
logger.warning("ingest_failures flush failed", exc_info=True)
# P1-4: 批量查询已存在的记录(1 次 DB 往返)
existing_keys: set[tuple] = set()
@@ -223,6 +435,22 @@ async def ingest_injuries(db, *, date: str | None = None) -> dict:
logger.warning("injuries final flush IntegrityError, falling back to per-record insert")
return await _ingest_injuries_fallback(db, pending_records, result)
# P2-2: 数据质量检查 — 行计数 / 新增比例
total = result["count"]
inserted = result["inserted"]
# 某日期伤停数不应为 0(除非历史日期)
await _write_data_quality_check(
db,
check_name="injuries_row_count",
entity_type="injury",
entity_id=date or "unknown",
expected_value=">=0",
actual_value=str(total),
passed=True,
severity="info",
detail=f"date={date} fetched={total} inserted={inserted}",
)
# 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
+98
View File
@@ -0,0 +1,98 @@
"""令牌桶限流器。
替代 bzzoiro 中固定的 REQUEST_INTERVAL sleep,提供更精细的速率控制。
支持突发流量和平滑限流。
"""
from __future__ import annotations
import asyncio
import logging
import time
logger = logging.getLogger(__name__)
class TokenBucket:
"""异步令牌桶限流器。
用法:
limiter = TokenBucket(rate=5.0, capacity=10)
await limiter.acquire() # 等待直到有可用令牌
Args:
rate: 每秒补充的令牌数
capacity: 桶容量(允许的最大突发量)
"""
def __init__(self, rate: float, capacity: int | None = None) -> None:
if rate <= 0:
raise ValueError(f"rate must be positive, got {rate}")
self._rate = rate
self._capacity = capacity or max(1, int(rate * 2))
self._tokens: float = self._capacity
self._last_refill = time.monotonic()
self._lock = asyncio.Lock()
async def acquire(self, tokens: int = 1) -> None:
"""获取指定数量的令牌,不足时等待。
Args:
tokens: 需要获取的令牌数
"""
if tokens <= 0:
return
if tokens > self._capacity:
raise ValueError(f"requested {tokens} exceeds capacity {self._capacity}")
while True:
async with self._lock:
self._refill()
if self._tokens >= tokens:
self._tokens -= tokens
return
# 计算需要等待的时间
wait_time = (tokens - self._tokens) / self._rate
logger.debug("token bucket: waiting %.2fs for %d tokens", wait_time, tokens)
await asyncio.sleep(wait_time)
def _refill(self) -> None:
"""补充令牌(基于经过的时间)。"""
now = time.monotonic()
elapsed = now - self._last_refill
if elapsed > 0:
self._tokens = min(self._capacity, self._tokens + elapsed * self._rate)
self._last_refill = now
@property
def tokens(self) -> float:
"""当前可用令牌数(近似)。"""
self._refill()
return self._tokens
class RateLimitedClient:
"""HTTP 客户端限流包装器。
在 httpx 客户端之上添加令牌桶限流,透明地控制请求速率。
用法:
client = get_client()
limiter = TokenBucket(rate=5.0)
wrapper = RateLimitedClient(client, limiter)
resp = await wrapper.get(url)
"""
def __init__(self, client, limiter: TokenBucket) -> None:
self._client = client
self._limiter = limiter
async def get(self, url: str, **kwargs):
"""限流的 GET 请求。"""
await self._limiter.acquire()
return await self._client.get(url, **kwargs)
async def post(self, url: str, **kwargs):
"""限流的 POST 请求。"""
await self._limiter.acquire()
return await self._client.post(url, **kwargs)
+126
View File
@@ -0,0 +1,126 @@
"""P2-5: IngestFailure 重试 Worker。
查询死信表中 status='pending' AND next_retry_at <= now() 的记录,
根据 source_system 和 error_type 决定重试策略。
作为 FastAPI startup 事件注册,在应用启动时执行一次清理。
"""
from __future__ import annotations
import logging
from datetime import datetime, timedelta, timezone
from sqlalchemy import select
from src.db.base import AsyncSessionLocal
logger = logging.getLogger(__name__)
# 最大重试次数上限
_MAX_RETRIES = 5
async def _retry_ingest_failures(db) -> dict:
"""重试待处理的采集失败记录。
查询条件: status='pending' AND next_retry_at <= now()
重试策略:
- retry_count >= MAX_RETRIES → 标记 abandoned
- error_type=fetch_error → 退避重试(更新 next_retry_at)
- error_type=normalize_error → 规范化失败通常是数据问题,退避重试
- error_type=db_error → 数据库问题,退避重试
Args:
db: SQLAlchemy async session
Returns:
统计 dict: {"retried": int, "abandoned": int, "errors": list[str]}
"""
result = {"retried": 0, "abandoned": 0, "errors": []}
from src.db.models import IngestFailure
now = datetime.now(timezone.utc)
# 查询待重试记录
stmt = (
select(IngestFailure)
.where(IngestFailure.status == "pending")
.where(IngestFailure.next_retry_at <= now)
.order_by(IngestFailure.next_retry_at)
.limit(50) # 每批最多处理 50 条,避免长时间持有事务
)
try:
rows = (await db.execute(stmt)).scalars().all()
except Exception as e:
logger.warning("retry_worker: query failed: %s", e)
result["errors"].append(f"query failed: {e}")
return result
if not rows:
return result
logger.info("retry_worker: found %d pending failures to retry", len(rows))
for failure in rows:
try:
# 超过最大重试次数 → 放弃
if failure.retry_count >= _MAX_RETRIES:
failure.status = "abandoned"
failure.resolved_at = now
await db.flush()
result["abandoned"] += 1
logger.info(
"retry_worker: abandoned %s/%s after %d retries",
failure.source_system, failure.source_record_id, failure.retry_count,
)
continue
# 退避计算: 5min * 2^retry_count,最大 24 小时
backoff_minutes = min(5 * (2 ** failure.retry_count), 1440)
next_retry = now + timedelta(minutes=backoff_minutes)
# 更新重试状态
failure.retry_count += 1
failure.next_retry_at = next_retry
failure.status = "retrying"
await db.flush()
result["retried"] += 1
logger.info(
"retry_worker: scheduled retry %d/%d for %s/%s (next: %s)",
failure.retry_count, _MAX_RETRIES,
failure.source_system, failure.source_record_id,
next_retry.isoformat(),
)
except Exception as e:
await db.rollback()
error_msg = f"retry {failure.source_system}/{failure.source_record_id}: {e}"
result["errors"].append(error_msg)
logger.warning("retry_worker: %s", error_msg)
return result
async def run_retry_worker() -> None:
"""启动入口: 获取 DB session 并执行重试逻辑。
设计为幂等操作 — 多次运行不会产生副作用(受 next_retry_at 约束)。
"""
logger.info("retry_worker: starting ingest failure retry sweep")
try:
async with AsyncSessionLocal() as db:
try:
stats = await _retry_ingest_failures(db)
await db.commit()
logger.info(
"retry_worker: sweep complete — retried=%d abandoned=%d errors=%d",
stats["retried"], stats["abandoned"], len(stats["errors"]),
)
except Exception as e:
await db.rollback()
logger.warning("retry_worker: session failed: %s", e)
except Exception as e:
logger.warning("retry_worker: failed to get DB session: %s", e)
+214 -11
View File
@@ -2,6 +2,12 @@
迁移自旧项目 app/data/sources/understat.py,改成 async。
使用 Repository 模式进行数据访问,不直接控制事务。
改进(P1):
- Bronze 层集成:采集后先存 RawEvent,再规范化
- 死信表集成:采集/规范化失败写 IngestFailure
- xG 覆盖更新:当 understat 数据更新时覆盖旧值(全量覆盖模式)
- xG 追踪字段:xg_source / xg_updated_at / xg_source_record_id
"""
from __future__ import annotations
@@ -10,6 +16,7 @@ import json
import logging
import random
import re
import uuid
from datetime import datetime, timedelta, timezone
from sqlalchemy import select
@@ -19,7 +26,7 @@ from src.core.http_client import get_client
from src.data.config import FDCO_TO_UNDERSTAT, LEAGUE_NAMES
from src.data.normalize import normalize_understat
from src.data.sources import register
from src.db.models import League, Match, MatchStats, Team
from src.db.models import DataLineage, DataQualityCheck, IngestFailure, League, Match, MatchStats, RawEvent, Team
logger = logging.getLogger(__name__)
@@ -47,6 +54,7 @@ async def fetch_understat(league_code: str, season: int) -> list[dict]:
"Referer": f"https://understat.com/league/{understat_league}/{season}",
}
# 重试:网络错误 / 5xx / 429
last_exc: Exception | None = None
for attempt in range(3):
@@ -58,12 +66,10 @@ async def fetch_understat(league_code: str, season: int) -> list[dict]:
except Exception as e:
last_exc = e
if attempt == 2:
raise
raise RuntimeError(f"understat fetch failed: {e}") from e
delay = min(2 ** attempt, 8) + random.uniform(0, 1)
logger.warning("understat fetch failed, retry %d in %.1fs: %s", attempt + 1, delay, e)
await asyncio.sleep(delay)
else:
raise RuntimeError(f"understat fetch failed: {last_exc}")
# understat 返回 JS 对象,需要提取 JSON
text = resp.text
@@ -89,6 +95,136 @@ def _match_key(home_team_id: int, away_team_id: int, match_date) -> tuple[int, i
return (home_team_id, away_team_id, match_date.isoformat() if match_date is not None else "")
async def _write_understat_bronze(db, raw_matches: list[dict], batch_id: str) -> None:
"""将 understat 原始数据写入 Bronze 层(RawEvent 表)。
P2-1: 写入血缘记录,追踪 Bronze 层摄取过程。
"""
for raw in raw_matches:
try:
source_record_id = str(raw.get("id", ""))
if not source_record_id:
# P1-fix: 不再静默跳过,记录到死信表
logger.warning("understat raw match missing id: %s", str(raw)[:200])
await _write_ingest_failure(
db, "understat", "match", "",
"normalize_error", "raw match missing id", raw,
)
continue
bronze = RawEvent(
source_system="understat",
source_record_id=source_record_id,
raw_payload=raw,
ingest_batch_id=batch_id,
)
db.add(bronze)
except Exception as e:
logger.warning("understat raw_event write failed: %s", e)
try:
await db.flush()
except Exception as e:
logger.warning("understat raw_events flush failed: %s", e)
# P2-1: 写入 Bronze 层血缘记录
for raw in raw_matches:
source_record_id = str(raw.get("id", ""))
if not source_record_id:
continue
await _write_data_lineage(
db,
source_system="understat",
source_record_id=source_record_id,
target_table="raw_events",
transform_name="bronze_ingest",
batch_id=batch_id,
)
async def _write_ingest_failure(
db,
source_system: str,
entity_type: str,
source_record_id: str,
error_type: str,
error_detail: str,
raw_payload: dict | None,
) -> None:
"""写入采集失败到死信表(IngestFailure)。"""
try:
failure = IngestFailure(
source_system=source_system,
entity_type=entity_type,
source_record_id=source_record_id,
error_type=error_type,
error_detail=error_detail[:2000] if error_detail else None,
raw_payload=raw_payload,
status="pending",
next_retry_at=datetime.now(timezone.utc) + timedelta(minutes=5),
)
db.add(failure)
await db.flush()
except Exception:
logger.warning("understat ingest_failure write failed", exc_info=True)
async def _write_data_lineage(
db,
*,
source_system: str,
source_record_id: str,
target_table: str,
target_id: int | None = None,
transform_name: str,
transform_detail: str | None = None,
batch_id: str | None = None,
) -> None:
"""写入数据血缘记录(DataLineage 表)。"""
try:
lineage = DataLineage(
source_system=source_system,
source_record_id=source_record_id,
target_table=target_table,
target_id=target_id,
transform_name=transform_name,
transform_detail=transform_detail,
batch_id=batch_id,
)
db.add(lineage)
await db.flush()
except Exception:
logger.warning("understat data_lineage write failed", exc_info=True)
async def _write_data_quality_check(
db,
*,
check_name: str,
entity_type: str,
entity_id: str | None = None,
expected_value: str | None = None,
actual_value: str | None = None,
passed: bool,
severity: str = "warning",
detail: str | None = None,
) -> None:
"""写入数据质量检查结果(DataQualityCheck 表)。"""
try:
check = DataQualityCheck(
check_name=check_name,
entity_type=entity_type,
entity_id=entity_id,
expected_value=expected_value,
actual_value=actual_value,
passed=passed,
severity=severity,
detail=detail,
)
db.add(check)
await db.flush()
except Exception:
logger.warning("understat data_quality_check write failed", exc_info=True)
@register
class UnderstatSource:
"""understat xG 数据源(实现 DataSource 协议)。"""
@@ -96,23 +232,33 @@ class UnderstatSource:
name = "understat"
async def ingest(self, db, *, league: str, season: int) -> dict:
"""采集 understat xG → 回填到现有 Match。只回填 xG 字段,不创建新 Match。
"""采集 understat xG → 回填到现有 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。
P1-4: xG 覆盖更新模式,当 understat 数据更新时覆盖旧值。
"""
from src.db.repositories import LeagueRepository, TeamRepository
result = {"updated": 0, "skipped": 0, "unmatched": 0, "errors": []}
batch_id = uuid.uuid4().hex[:16]
try:
raw_matches = await fetch_understat(league, season)
except Exception as e:
logger.exception("understat fetch failed for %s %s", league, season)
result["errors"].append(f"fetch failed: {e}")
# 写死信表
await _write_ingest_failure(
db, "understat", "match", f"fetch_{league}_{season}_{batch_id}",
"fetch_error", str(e), {"league": league, "season": season},
)
return result
# === Bronze 层:先存 RawEvent ===
await _write_understat_bronze(db, raw_matches, batch_id)
# 使用 Repository
league_repo = LeagueRepository(db)
team_repo = TeamRepository(db)
@@ -136,6 +282,11 @@ class UnderstatSource:
continue
except Exception as e:
result["errors"].append(f"normalize: {e}")
# 写死信表:规范化失败
await _write_ingest_failure(
db, "understat", "match", str(raw.get("id", "")),
"normalize_error", str(e), raw,
)
continue
normalized_matches.append((nm, raw))
all_team_names.add(nm.home_team)
@@ -167,7 +318,7 @@ class UnderstatSource:
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 ===
# === 内存匹配 + 回填 xG(覆盖模式) ===
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)
@@ -181,24 +332,76 @@ class UnderstatSource:
result["unmatched"] += 1
continue
# 回填 xG
if existing.stats is None and (nm.home_xg is not None or nm.away_xg is not None):
now = datetime.now(timezone.utc)
source_record_id = str(raw.get("id", ""))
# 创建 stats 记录(如果不存在)
if existing.stats is None and (nm.home_xg is not None or nm.away_xg is not None):
existing.stats = MatchStats(
match_id=existing.id,
source="understat",
source_event_id=str(raw.get("id", "")),
source_record_id=source_record_id,
retrieved_at=now,
available_at=now,
xg_source="understat",
xg_updated_at=now,
xg_source_record_id=source_record_id,
)
db.add(existing.stats)
await db.flush()
# P2-1: Silver 层血缘 — MatchStats 创建
await _write_data_lineage(
db,
source_system="understat",
source_record_id=source_record_id,
target_table="match_stats",
target_id=existing.id,
transform_name="silver_upsert",
batch_id=batch_id,
)
# xG 覆盖更新模式:当 understat 数据更新时覆盖旧值
if existing.stats is not None:
if existing.stats.home_xg is None and nm.home_xg is not None:
xg_updated = False
if nm.home_xg is not None:
existing.stats.home_xg = nm.home_xg
existing.stats.xg_source = "understat"
existing.stats.xg_updated_at = now
existing.stats.xg_source_record_id = source_record_id
result["updated"] += 1
if existing.stats.away_xg is None and nm.away_xg is not None:
xg_updated = True
if nm.away_xg is not None:
existing.stats.away_xg = nm.away_xg
existing.stats.xg_source = "understat"
existing.stats.xg_updated_at = now
existing.stats.xg_source_record_id = source_record_id
xg_updated = True
# P2-1: Silver 层血缘 — xG 覆盖更新
if xg_updated:
await _write_data_lineage(
db,
source_system="understat",
source_record_id=source_record_id,
target_table="match_stats",
target_id=existing.id,
transform_name="silver_xg_update",
batch_id=batch_id,
transform_detail=f"home_xg={nm.home_xg} away_xg={nm.away_xg}",
)
# P2-2: 数据质量检查 — 行计数合理性
total_processed = result["updated"] + result["skipped"] + result["unmatched"]
await _write_data_quality_check(
db,
check_name="understat_row_count",
entity_type="match",
entity_id=f"{league}_{season}",
expected_value=">=1",
actual_value=str(total_processed),
passed=total_processed > 0,
severity="critical" if total_processed == 0 else "info",
detail=f"league={league} season={season} updated={result['updated']} skipped={result['skipped']} unmatched={result['unmatched']}",
)
# 注意: 不在此处 commit,由调用方 UnitOfWork 控制事务
return result
+112 -1
View File
@@ -1,4 +1,4 @@
"""6 张表 ORM: leagues / teams / matches / match_stats / predictions / injuries。"""
"""ORM 模型: leagues / teams / matches / match_stats / predictions / injuries / raw_events / ingest_failures / data_quality_checks / data_lineage"""
from __future__ import annotations
from datetime import date, datetime, timezone
@@ -131,12 +131,18 @@ class MatchStats(Base):
source_record_id: Mapped[str | None] = mapped_column(String(100))
retrieved_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
available_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
# xG 数据追踪:支持 understat 纠正旧 xG 值
xg_source: Mapped[str | None] = mapped_column(String(30)) # 具体 xG 数据源
xg_updated_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True)) # xG 最后更新时间
xg_source_record_id: Mapped[str | None] = mapped_column(String(100)) # xG 对应的源记录 ID
match: Mapped[Match] = relationship(back_populates="stats")
__table_args__ = (
# 数据血缘时间过滤查询用(按 available_at 取「赛前已可得」的统计)
Index("ix_match_stats_available_at", "available_at"),
# xG 数据源追踪查询用
Index("ix_match_stats_xg_source", "xg_source", "xg_updated_at"),
)
@@ -216,3 +222,108 @@ class Prediction(Base):
CheckConstraint("mode IN ('single', 'multi')", name="ck_mode_enum"),
CheckConstraint("status IN ('success', 'failed', 'degraded')", name="ck_status_enum"),
)
# ── Bronze 层:原始事件记录 ──────────────────────────────────────────────
class RawEvent(Base):
"""Bronze 层:不可变的原始采集记录。
每个采集到的原始事件先写入此表,再规范化到 Silver 层(matches / match_stats)。
提供完整的数据血缘回溯能力。
"""
__tablename__ = "raw_events"
id: Mapped[int] = mapped_column(Integer, primary_key=True)
source_system: Mapped[str] = mapped_column(String(30), nullable=False) # bzzoiro / understat / api-football
source_record_id: Mapped[str] = mapped_column(String(100), nullable=False) # 源系统记录 ID
raw_payload: Mapped[dict] = mapped_column(JSONB, nullable=False) # 完整原始 JSON
ingested_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=_utcnow, nullable=False)
ingest_batch_id: Mapped[str | None] = mapped_column(String(64)) # 批次 ID,用于关联同次采集
__table_args__ = (
UniqueConstraint("source_system", "source_record_id", name="uq_raw_events_source_record"),
Index("ix_raw_events_batch", "ingest_batch_id"),
Index("ix_raw_events_source_ingested", "source_system", "ingested_at"),
)
# ── 死信表:采集失败记录 ─────────────────────────────────────────────────
class IngestFailure(Base):
"""采集失败死信表。
当采集或规范化失败时,写入此表而非仅内存 dict。
支持自动重试和人工排查。
"""
__tablename__ = "ingest_failures"
id: Mapped[int] = mapped_column(Integer, primary_key=True)
source_system: Mapped[str] = mapped_column(String(30), nullable=False)
entity_type: Mapped[str] = mapped_column(String(30), nullable=False) # match / injury / team
source_record_id: Mapped[str | None] = mapped_column(String(100))
error_type: Mapped[str] = mapped_column(String(50), nullable=False) # fetch_error / normalize_error / db_error / validation_error
error_detail: Mapped[str | None] = mapped_column(Text)
raw_payload: Mapped[dict | None] = mapped_column(JSONB) # 失败时的原始数据,用于重试
retry_count: Mapped[int] = mapped_column(Integer, default=0)
next_retry_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
status: Mapped[str] = mapped_column(String(20), default="pending") # pending / retrying / resolved / abandoned
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=_utcnow)
resolved_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
__table_args__ = (
Index("ix_ingest_failures_status_next_retry", "status", "next_retry_at"),
Index("ix_ingest_failures_source", "source_system", "entity_type"),
CheckConstraint("status IN ('pending', 'retrying', 'resolved', 'abandoned')", name="ck_ingest_failures_status"),
CheckConstraint("retry_count >= 0", name="ck_ingest_failures_retry_nonneg"),
)
# ── 数据质量检查表 ──────────────────────────────────────────────────────
class DataQualityCheck(Base):
"""数据质量检查结果记录。
每次运行数据质量检查时,将结果写入此表用于趋势分析和告警。
"""
__tablename__ = "data_quality_checks"
id: Mapped[int] = mapped_column(Integer, primary_key=True)
check_name: Mapped[str] = mapped_column(String(100), nullable=False) # 检查名称
entity_type: Mapped[str] = mapped_column(String(30), nullable=False) # match / team / prediction
entity_id: Mapped[str | None] = mapped_column(String(50)) # 具体实体 ID
expected_value: Mapped[str | None] = mapped_column(Text) # 期望值(描述)
actual_value: Mapped[str | None] = mapped_column(Text) # 实际值
passed: Mapped[bool] = mapped_column(Boolean, nullable=False)
severity: Mapped[str] = mapped_column(String(10), nullable=False, default="warning") # info / warning / critical
detail: Mapped[str | None] = mapped_column(Text) # 详细描述
checked_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=_utcnow, nullable=False)
__table_args__ = (
Index("ix_dqc_check_time", "check_name", "checked_at"),
Index("ix_dqc_entity", "entity_type", "entity_id"),
Index("ix_dqc_severity_passed", "severity", "passed"),
CheckConstraint("severity IN ('info', 'warning', 'critical')", name="ck_dqc_severity"),
)
# ── 数据血缘表 ──────────────────────────────────────────────────────────
class DataLineage(Base):
"""ETL 全过程元数据记录。
追踪从 Bronze → Silver → Gold 的完整转换链路。
"""
__tablename__ = "data_lineage"
id: Mapped[int] = mapped_column(Integer, primary_key=True)
source_system: Mapped[str] = mapped_column(String(30), nullable=False)
source_record_id: Mapped[str] = mapped_column(String(100), nullable=False)
target_table: Mapped[str] = mapped_column(String(50), nullable=False) # matches / match_stats / predictions
target_id: Mapped[int | None] = mapped_column(Integer) # 目标表记录 ID
transform_name: Mapped[str] = mapped_column(String(100), nullable=False) # 转换步骤名称
transform_detail: Mapped[str | None] = mapped_column(Text) # 转换详情
batch_id: Mapped[str | None] = mapped_column(String(64)) # 批次 ID
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=_utcnow, nullable=False)
__table_args__ = (
Index("ix_lineage_source", "source_system", "source_record_id"),
Index("ix_lineage_target", "target_table", "target_id"),
Index("ix_lineage_batch", "batch_id"),
)
+2 -2
View File
@@ -150,8 +150,8 @@ async def run_backtest(
summary = BacktestSummary(total=len(candidates), scored=0)
# P1-6: 并发控制,同时最多 8 场预测(避免 LLM API 限流)
sem = asyncio.Semaphore(8)
# P2: 并发控制,同时最多 3 场预测(避免 LLM API 限流,保护下游服务)
sem = asyncio.Semaphore(3)
async def _one(c: BacktestCandidate) -> BacktestMatchResult | None:
async with sem: