109 lines
4.9 KiB
Python
109 lines
4.9 KiB
Python
from rest_framework import status
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from rest_framework.views import APIView
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from rest_framework.permissions import IsAuthenticated
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from rest_framework.response import Response
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from drf_spectacular.utils import extend_schema, OpenApiResponse, OpenApiExample, OpenApiParameter
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from api.utils.decorators import handle_exceptions
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from datetime import timedelta
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from django.utils import timezone
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from django.db.models import Count
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from django.db.models.functions import TruncHour
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from sitemanagement.models import Alert
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from api.account.serializers.dashboard_serializers import DashboardSerializer
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@extend_schema(tags=['Дашборд'])
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class DashboardView(APIView):
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permission_classes = [IsAuthenticated]
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@extend_schema(
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summary="Получение статистики алертов",
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description="Возвращает статистику алертов за выбранный период времени",
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parameters=[OpenApiParameter(
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name='time_period',
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type=str,
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location=OpenApiParameter.QUERY,
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description='Период времени в часах',
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required=False,
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enum=['24', '72', '168', '720'],
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default='168'
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)],
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responses = {
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200: OpenApiResponse(response=DashboardSerializer, description="Данные для дашборда успешно получены",
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examples=[OpenApiExample(
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'Успешный ответ',
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value={
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"chart_data": [
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{"timestamp": "2025-10-07T10:00:00+03:00", "value": 5},
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{"timestamp": "2025-10-07T11:00:00+03:00", "value": 3}
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],
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"table_data": [
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{
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"id": 1,
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"name": "GA-1",
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"object": "Объект 1",
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"metric_value": "23.5 °C",
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"sensor_type_name": "Датчик температуры",
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"message": "Превышение температуры",
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"severity": "warning",
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"created_at": "2025-10-07T10:30:00+03:00",
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"resolved": False
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}
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]
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}
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)])
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}
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)
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@handle_exceptions
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def get(self, request):
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time_period = request.query_params.get('time_period', '168')
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if time_period not in ['720', '168', '72', '24']:
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return Response(
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- {"error": "Неверный период. Допустимые значения: 720, 168, 72, 24"},
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+ {"error": "Неверный период. Допустимые значения: 24, 72, 168, 720"},
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status=status.HTTP_400_BAD_REQUEST
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)
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# определяем начальную дату
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start_date = timezone.now() - timedelta(hours=int(time_period))
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# получаем все алерты за период с фронта
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alerts = Alert.objects.filter(created_at__gte=start_date)
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# данные для графиков (группировка по часам)
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alerts_by_hour = alerts.annotate(
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hour=TruncHour('created_at')
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).values('hour').annotate(
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count=Count('id')
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).order_by('hour')
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# !! обязательно локальное время
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chart_data = []
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for entry in alerts_by_hour:
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local_time = timezone.localtime(entry['hour'])
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chart_data.append({
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"timestamp": local_time.isoformat(),
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"value": entry['count']
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})
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# данные для таблицы с алертами
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alerts_list = alerts.select_related(
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'sensor',
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'sensor_type',
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'metric',
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'sensor__signal_format'
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).prefetch_related(
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'sensor__zones',
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'sensor__zones__object'
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).order_by('-created_at')
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dashboard_data = {
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"chart_data": chart_data,
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"table_data": alerts_list
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}
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serializer = DashboardSerializer(instance=dashboard_data)
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return Response(serializer.data, status=status.HTTP_200_OK) |