feat: standings Bronze 血缘补齐 + 队名归一 MVP
standings 成功 upsert 后写入 RawEvent(source_record_id=standings:{league}:{season})
+ DataLineage(target_table=standings),与 events/stats 管线对称。
队名归一化收敛到 TeamRepository.get_or_create 唯一咽喉点,
创建新 Team 时 info 日志打出原始名与归一后名;
Admin 新增 GET /api/v1/admin/team-name-duplicates 只读接口,
启发式列出近似重名候选(大小写变体/子串/前缀碰撞),不做自动合并。
This commit is contained in:
shangfangjian
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"""后台管理:管理区统计、数据完整性分析、数据质量检查。
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所有接口需管理员鉴权(require_admin)。路由前缀 /api/v1/admin。
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"""
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from __future__ import annotations
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import logging
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from datetime import datetime, timedelta, timezone
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from fastapi import APIRouter, Depends
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from sqlalchemy import func, select
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from src.api.deps import require_admin
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from src.db.base import AsyncSession, get_db_read
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from src.db.models import DataQualityCheck, IngestFailure, League, Match, MatchStats, Prediction, Standing
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/admin", tags=["admin"], dependencies=[Depends(require_admin)])
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@router.get("/stats")
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async def admin_stats(db: AsyncSession = Depends(get_db_read)):
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"""管理区统计(只读):预测次数 + 比赛覆盖。轻量聚合,无 LLM 调用。"""
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day_ago = datetime.now(timezone.utc) - timedelta(days=1)
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week_ago = datetime.now(timezone.utc) - timedelta(days=7)
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r = (
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await db.execute(
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select(
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func.count().label("total"),
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func.count().filter(Prediction.created_at >= day_ago).label("last_24h"),
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func.count().filter(Prediction.created_at >= week_ago).label("last_7d"),
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)
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)
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).one()
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# F3 修复: 补充真实比赛计数(非 limit=100 近似)
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match_cnt = (await db.execute(select(func.count()).select_from(Match))).scalar() or 0
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finished_cnt = (await db.execute(select(func.count()).where(Match.match_status == "finished"))).scalar() or 0
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stats_cnt = (await db.execute(select(func.count()).select_from(MatchStats))).scalar() or 0
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standings_cnt = (await db.execute(select(func.count()).select_from(Standing))).scalar() or 0
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return {
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"predictions": {"total": r.total, "last_24h": r.last_24h, "last_7d": r.last_7d},
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"matches": {"total": match_cnt, "finished": finished_cnt},
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"stats": {"total": stats_cnt},
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"standings": {"total": standings_cnt},
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}
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# ── 数据完整性分析(可视化数据源) ────────────────────────────────
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@router.get("/data-completeness")
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async def data_completeness(db: AsyncSession = Depends(get_db_read)):
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"""按联赛统计数据完整性:比赛覆盖、字段覆盖、积分榜覆盖。
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前端「数据完整性」页据此渲染,回答三个问题:
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1. 数据是否齐全(各联赛比赛/统计/积分榜量级)
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2. 字段是否齐全(每张统计表各字段非空率)
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3. 覆盖是否新鲜(最近一场/最近一次采集)
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"""
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from src.data.config import BZZOIRO_LEAGUE_IDS, LEAGUE_NAMES, LEAGUE_COUNTRIES
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out_leagues: list[dict] = []
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for code, bzz_id in BZZOIRO_LEAGUE_IDS.items():
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# 比赛覆盖
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m = (
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await db.execute(
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select(
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func.count().label("total"),
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func.count().filter(Match.match_status == "finished").label("finished"),
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func.count().filter(Match.match_status == "scheduled").label("scheduled"),
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func.count().filter(Match.source_event_id.is_not(None)).label("with_source_id"),
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func.max(Match.match_date).label("latest_match"),
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func.min(Match.match_date).label("earliest_match"),
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)
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.select_from(Match)
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.join(League, League.id == Match.league_id)
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.where(League.code == code)
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)
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).one()
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# 统计字段覆盖(联表 matches)
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s = (
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await db.execute(
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select(
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func.count().label("rows"),
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func.count(MatchStats.home_xg).label("xg"),
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func.count(MatchStats.home_shots).label("shots"),
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func.count(MatchStats.home_possession).label("possession"),
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func.count(MatchStats.home_corners).label("corners"),
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func.count(MatchStats.home_fouls).label("fouls"),
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func.count(MatchStats.home_big_chances).label("big_chances"),
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func.count(MatchStats.home_yellow_cards).label("cards"),
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)
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.select_from(MatchStats)
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.join(Match, Match.id == MatchStats.match_id)
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.join(League, League.id == Match.league_id)
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.where(League.code == code)
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)
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).one()
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# 积分榜覆盖
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st = (
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await db.execute(
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select(
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func.count().label("rows"),
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func.max(Standing.retrieved_at).label("latest_retrieved"),
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)
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.select_from(Standing)
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.join(League, League.id == Standing.league_id)
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.where(League.code == code)
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)
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).one()
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stats_rows = s.rows or 0
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pct = lambda n: round(n / stats_rows * 100, 1) if stats_rows else 0.0 # noqa: E731
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out_leagues.append(
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{
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"code": code,
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"name": LEAGUE_NAMES.get(code, code),
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"country": LEAGUE_COUNTRIES.get(code),
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"matches": {
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"total": m.total or 0,
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"finished": m.finished or 0,
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"scheduled": m.scheduled or 0,
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"with_source_id": m.with_source_id or 0,
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"earliest_match": m.earliest_match.isoformat() if m.earliest_match else None,
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"latest_match": m.latest_match.isoformat() if m.latest_match else None,
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},
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"stats": {
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"rows": stats_rows,
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"fields": {
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"xg": {"count": s.xg or 0, "pct": pct(s.xg or 0)},
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"shots": {"count": s.shots or 0, "pct": pct(s.shots or 0)},
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"possession": {"count": s.possession or 0, "pct": pct(s.possession or 0)},
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"corners": {"count": s.corners or 0, "pct": pct(s.corners or 0)},
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"fouls": {"count": s.fouls or 0, "pct": pct(s.fouls or 0)},
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"big_chances": {"count": s.big_chances or 0, "pct": pct(s.big_chances or 0)},
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"cards": {"count": s.cards or 0, "pct": pct(s.cards or 0)},
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},
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},
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"standings": {
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"rows": st.rows or 0,
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"latest_retrieved": st.latest_retrieved.isoformat() if st.latest_retrieved else None,
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},
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}
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)
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# 整体健康信号
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total_finished = sum(l["matches"]["finished"] for l in out_leagues)
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total_stats = sum(l["stats"]["rows"] for l in out_leagues)
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stats_coverage = round(total_stats / total_finished * 100, 1) if total_finished else 0.0
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issues: list[str] = []
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for l in out_leagues:
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if l["matches"]["finished"] == 0:
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issues.append(f"{l['name']}: 无已完赛比赛,请先运行「比赛数据」采集")
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elif l["stats"]["rows"] == 0:
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issues.append(f"{l['name']}: 已完赛 {l['matches']['finished']} 场但无统计回填,请运行「统计回填」采集")
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elif stats_coverage < 80:
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issues.append(f"{l['name']}: 统计覆盖率仅 {stats_coverage}%,建议增量回填")
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if l["standings"]["rows"] == 0:
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issues.append(f"{l['name']}: 无积分榜数据,请运行「积分榜」采集")
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if not issues:
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issues.append("各联赛数据完整度良好")
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return {
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"generated_at": datetime.now(timezone.utc).isoformat(),
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"leagues": out_leagues,
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"totals": {
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"finished_matches": total_finished,
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"stats_rows": total_stats,
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"stats_coverage_pct": stats_coverage,
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},
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"issues": issues,
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}
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# ── 数据质量检查 API ────────────────────────────────────────────
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@router.get("/data-quality")
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async def data_quality_checks(db: AsyncSession = Depends(get_db_read)):
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"""数据质量检查结果(只读)。"""
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# 最近的失败记录
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failures = (
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await db.execute(
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select(IngestFailure)
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.where(IngestFailure.status.in_(["pending", "retrying"]))
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.order_by(IngestFailure.created_at.desc())
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.limit(20)
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)
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).scalars().all()
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# 最近的质量检查
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checks = (
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await db.execute(
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select(DataQualityCheck)
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.order_by(DataQualityCheck.checked_at.desc())
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.limit(20)
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)
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).scalars().all()
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return {
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"failures": [
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{
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"id": f.id,
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"source": f.source_system,
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"entity_type": f.entity_type,
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"source_record_id": f.source_record_id,
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"error_type": f.error_type,
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"error_detail": f.error_detail,
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"retry_count": f.retry_count,
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"status": f.status,
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"created_at": f.created_at.isoformat() if f.created_at else None,
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}
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for f in failures
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],
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"checks": [
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{
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"id": c.id,
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"check_name": c.check_name,
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"entity_type": c.entity_type,
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"passed": c.passed,
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"severity": c.severity,
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"detail": c.detail,
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"checked_at": c.checked_at.isoformat() if c.checked_at else None,
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}
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for c in checks
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],
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}
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@router.post("/data-quality/run")
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async def run_data_quality_check(db: AsyncSession = Depends(get_db_read)):
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"""手动触发一次数据质量检查。"""
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checks = []
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# 检查1: 已完赛但无统计的比赛
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finished_no_stats = (
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await db.execute(
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select(func.count())
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.select_from(Match)
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.outerjoin(MatchStats, Match.id == MatchStats.match_id)
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.where(Match.match_status == "finished")
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.where(MatchStats.id.is_(None))
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)
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).scalar() or 0
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checks.append(DataQualityCheck(
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check_name="finished_without_stats",
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entity_type="match",
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actual_value=float(finished_no_stats),
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passed=finished_no_stats == 0,
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severity="warning" if finished_no_stats > 0 else "info",
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detail={"message": f"{finished_no_stats} 场已完赛比赛缺少统计数据"},
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))
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# 检查2: 积分榜缺失的联赛
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leagues_without_standings = (
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await db.execute(
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select(func.count())
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.select_from(League)
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.outerjoin(Standing, League.id == Standing.league_id)
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.where(Standing.id.is_(None))
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)
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).scalar() or 0
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checks.append(DataQualityCheck(
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check_name="league_without_standings",
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entity_type="league",
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actual_value=float(leagues_without_standings),
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passed=leagues_without_standings == 0,
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severity="warning" if leagues_without_standings > 0 else "info",
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detail={"message": f"{leagues_without_standings} 个联赛缺少积分榜"},
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))
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for c in checks:
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db.add(c)
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await db.commit()
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return {"ok": True, "checks": [{"name": c.check_name, "passed": c.passed} for c in checks]}
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# ── 近似重名候选(只读,启发式,不做自动合并) ──────────────────────
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@router.get("/team-name-duplicates")
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async def team_name_duplicates(db: AsyncSession = Depends(get_db_read)):
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"""只读列出近似重名候选(大小写变体/子串包含/前缀碰撞)。
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启发式规则(命中任一即列为候选):
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- 大小写变体: lower(name) 相同但 name 不同
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- 子串包含: A 是 B 的子串且 len(A) ≥ 5
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- 前缀碰撞: 前 8 字符相同(忽略大小写)
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仅作排查参考,合并需走人工 SQL(见 docs/05-data.md)。
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"""
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teams = (await db.execute(select(Team.id, Team.name))).all()
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by_lower: dict[str, list[dict]] = {}
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for t in teams:
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key = (t.name or "").lower()
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by_lower.setdefault(key, []).append({"id": t.id, "name": t.name})
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groups: list[dict] = []
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# 规则1: 大小写变体(lower 相同但原名不同)
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for key, members in by_lower.items():
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if len(members) > 1:
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groups.append({
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"rule": "case_variant",
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"key": key,
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"members": members,
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})
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# 规则2 & 3: 子串包含 / 前缀碰撞(仅在 lower 名不同的组间比较)
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distinct = [m for members in by_lower.values() for m in members]
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seen_pairs: set[tuple[int, int]] = set()
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for i, a in enumerate(distinct):
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na = (a["name"] or "").lower()
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for b in distinct[i + 1:]:
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nb = (b["name"] or "").lower()
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if na == nb:
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continue # 已被规则1覆盖
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pair = (min(a["id"], b["id"]), max(a["id"], b["id"]))
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if pair in seen_pairs:
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continue
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hit = None
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if len(na) >= 5 and na in nb:
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hit = "substring"
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elif len(nb) >= 5 and nb in na:
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hit = "substring"
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elif len(na) >= 8 and len(nb) >= 8 and na[:8] == nb[:8]:
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hit = "prefix"
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if hit:
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seen_pairs.add(pair)
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groups.append({
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"rule": hit,
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"members": [a, b],
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})
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return {
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"count": len(groups),
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"hint": "命中任一启发式仅表示'可疑',合并前请人工确认是否同一球队",
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"groups": groups,
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}
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Reference in New Issue
Block a user