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fangke/server/tracker/api/dashboard.py
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"""数据总览接口(客迹视觉 V1:周期卡 + 趋势双线 + 渠道分布)。
?range=today|7d|30d(默认 7d,非法值回落默认)+ ?site=(可选,缺省聚合全部站点)。
- 周期卡四指标全口径排除爬虫,与上一个等长周期比较出 delta_pct(today 比昨天);
上期值为 0 时 delta 为 null(前端显示 —)。
- 趋势为日粒度:历史位读 DailyStat 聚合(缺日补零),今天一位用 daily_counts 实时值
(聚合作业未跑也不缺当日)——与 refresh_daily 共享口径(Task8 审查结论)。
- channels 按窗口内会话入口分类聚合,pct = 占已分类会话比(列表含 direct/unknown,
总和 ≈ 1;未重算出分类行的历史会话不计入)。
- 最近访问不在本接口做:前端调既有 /api/admin/visitors?page=1 取前 5 行。
"""
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from datetime import datetime, time, timedelta
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from django.db.models import Count, Sum
from django.utils import timezone
from rest_framework.response import Response
from rest_framework.views import APIView
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from tracker.api.envelope import EnvelopeMixin, ok
from tracker.models import DailyStat, Event, Site, SourceClassification, VisitSession, Visitor
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from tracker.services.stats import daily_counts
RANGE_DAYS = {"today": 1, "7d": 7, "30d": 30}
CARD_KEYS = ("visitors", "visits", "avg_stay_ms", "returning")
def _window_stats(site, start, end):
"""窗口四指标(site=None 聚合全部站点;全口径排除爬虫)。
visitors 按 Event distinct visitor(与 daily_counts 的 uv 同源,跨日不重复计);
visits 按会话 started_at 落窗;avg_stay_ms = Sum(stay_ms)/会话数(0 保护);
returning = visitors - 窗口内新访客(first_seen_at 落窗;异常数据下限 0)。
"""
ev = Event.objects.filter(is_bot=False,
occurred_at__gte=start, occurred_at__lt=end)
vs = VisitSession.objects.filter(visitor__is_bot=False,
started_at__gte=start, started_at__lt=end)
vis = Visitor.objects.filter(is_bot=False,
first_seen_at__gte=start, first_seen_at__lt=end)
if site is not None:
ev = ev.filter(site=site)
vs = vs.filter(site=site)
vis = vis.filter(site=site)
agg = vs.aggregate(n=Count("id"), stay=Sum("stay_ms"))
sessions = agg["n"]
visitors = ev.values("visitor").distinct().count()
new_visitors = vis.count()
return {"visitors": visitors,
"visits": sessions,
"avg_stay_ms": round((agg["stay"] or 0) / sessions) if sessions else 0,
"returning": max(visitors - new_visitors, 0)}
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def _delta(cur, prev):
"""环比百分比(保留 1 位小数);上期值为 0 无意义 → None。"""
if prev == 0:
return None
return round((cur - prev) / prev * 100, 1)
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class OverviewView(EnvelopeMixin, APIView):
def get(self, request):
site = None
sid = request.query_params.get("site")
if sid:
site = Site.objects.filter(site_id=sid).first()
if not site:
return Response({"code": 404, "data": None,
"message": "site_not_found"}, status=404)
days = RANGE_DAYS.get(request.query_params.get("range", "7d"), 7)
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today = timezone.localdate()
# 当前窗口与上期等长窗口(上海自然日对齐:[T-N+1, T+1) 与 [T-2N+1, T-N+1))
cur_start = timezone.make_aware(
datetime.combine(today - timedelta(days=days - 1), time.min))
cur_end = timezone.make_aware(
datetime.combine(today + timedelta(days=1), time.min))
prev_start = cur_start - timedelta(days=days)
cur = _window_stats(site, cur_start, cur_end)
prev = _window_stats(site, prev_start, cur_start)
online = self._active_now(site)
return ok({
"header": {"online": online, "active_now": online}, # active_now 兼容保留
"cards": {k: {"value": cur[k], "delta_pct": _delta(cur[k], prev[k])}
for k in CARD_KEYS},
"trend": self._trend(site, today, days),
"channels": self._channels(site, cur_start, cur_end),
})
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@staticmethod
def _active_now(site):
# 5 分钟内有行为的访客(last_seen_at 有 site,-last_seen_at 索引;不用无索引的 received_at)
q = Visitor.objects.filter(is_bot=False,
last_seen_at__gt=timezone.now() - timedelta(minutes=5))
if site is not None:
q = q.filter(site=site)
return q.count()
def _trend(self, site, today, days):
"""窗口每日 [{date, uv, sessions}]:历史位读 DailyStat(缺日补零),
今天一位用 daily_counts 实时值覆盖——聚合作业未跑也不缺当日。"""
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start = today - timedelta(days=days - 1)
qs = DailyStat.objects.filter(date__gte=start, date__lte=today)
if site is not None:
qs = qs.filter(site=site)
rows = {r["date"]: r for r in qs.values("date").annotate(
uv=Sum("uv"), sessions=Sum("sessions"))}
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out = []
for i in range(days):
date = start + timedelta(days=i)
if date == today:
counts = daily_counts(site, today)
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out.append({"date": date.isoformat(),
"uv": counts["uv"], "sessions": counts["sessions"]})
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else:
r = rows.get(date, {})
out.append({"date": date.isoformat(),
"uv": r.get("uv") or 0, "sessions": r.get("sessions") or 0})
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return out
def _channels(self, site, start, end):
"""窗口内会话按 session_entry 分类聚合(session.started_at 落窗)。
从分类表正向聚合 + Count(distinct session):无唯一约束下分类表偶发同键重复行
也不会把同一会话计两次。pct = 占已分类会话比(含 direct/unknown,总和 ≈ 1;
无分类行的会话——未重算的历史数据——不计入)。"""
q = SourceClassification.objects.filter(
scope="session_entry",
session__visitor__is_bot=False,
session__started_at__gte=start, session__started_at__lt=end)
if site is not None:
q = q.filter(site=site)
rows = list(q.values("channel")
.annotate(n=Count("session", distinct=True))
.order_by("-n", "channel")) # 平局时次序跨请求稳定
total = sum(r["n"] for r in rows)
return [{"channel": r["channel"] or "unknown", "sessions": r["n"],
"pct": round(r["n"] / total, 4) if total else 0.0}
for r in rows]