如何使用基于 class 的视图继承来覆盖父级 class?

How use class-based views inheritance to override to parent class?

在我的 ShowChart 中有一个名为 Electronic(Electronic.objects.values..etc) 的模型,在我的继承 class(ChartElectrical) 中它需要更改为 Electrical (Electronic.objects.values..etc ), 这里我就传过去了。我不知道该怎么做

 class ShowChart(View):
   def get(self, request):
    my_count = Electrical.objects.values('allocated_time')\
        .annotate(complete=Count('allocated_time', filter=Q(batch_18=True)),
                  not_complete=Count('allocated_time', 
                   filter=Q(batch_18=False)),
                  complete_1=Count('allocated_time', 
                       filter=Q(batch_19=True)),
                  not_complete_1=Count('allocated_time', 
                  filter=Q(batch_19=False)),
                  complete_2=Count('allocated_time', 
                     filter=Q(batch_20=True)),
                  not_complete_2=Count('allocated_time', 
                   filter=Q(batch_20=False)),
                  complete_3=Count('allocated_time', 
                   filter=Q(batch_21=True)),
                  not_complete_3=Count('allocated_time', 
                filter=Q(batch_21=False)))

    c_batch_18 = list()
    n_batch_18 = list()
    c_batch_19 = list()
    n_batch_19 = list()
    c_batch_20 = list()
    n_batch_20 = list()
    c_batch_21 = list()
    n_batch_21 = list()

    for entry in my_count:
        c_batch_18.append(entry['complete'] * entry['allocated_time'])
        n_batch_18.append(entry['not_complete'] * entry['allocated_time'])
        c_batch_19.append(entry['complete_1'] * entry['allocated_time'])
        n_batch_19.append(entry['not_complete_1'] * entry['allocated_time'])
        c_batch_20.append(entry['complete_2'] * entry['allocated_time'])
        n_batch_20.append(entry['not_complete_2'] * entry['allocated_time'])
        c_batch_21.append(entry['complete_3'] * entry['allocated_time'])
        n_batch_21.append(entry['not_complete_3'] * entry['allocated_time'])

    survived_series = [sum(c_batch_18), sum(c_batch_19), sum(c_batch_20), sum(c_batch_21), 0]
    not_survived_series = [sum(n_batch_18), sum(n_batch_19), sum(n_batch_20), sum(n_batch_21), 0]

    return render(request, 'chart.html', {'survived_series': json.dumps(survived_series),
                                          'not_survived_series': json.dumps(not_survived_series)})


   class ChartElectrical(ShowChart):
    pass

我认为您应该用另一种方法移动视图的 my_count 部分,然后在子视图中覆盖它。像这样:

class ShowChart(View):
   def get_my_count(self):
      my_count = Electrical.objects.values('allocated_time')\
        .annotate(complete=Count('allocated_time', filter=Q(batch_18=True)),
                  not_complete=Count('allocated_time', 
                   filter=Q(batch_18=False)),
                  complete_1=Count('allocated_time', 
                       filter=Q(batch_19=True)),
                  not_complete_1=Count('allocated_time', 
                  filter=Q(batch_19=False)),
                  complete_2=Count('allocated_time', 
                     filter=Q(batch_20=True)),
                  not_complete_2=Count('allocated_time', 
                   filter=Q(batch_20=False)),
                  complete_3=Count('allocated_time', 
                   filter=Q(batch_21=True)),
                  not_complete_3=Count('allocated_time', 
                filter=Q(batch_21=False)))
     return my_count

   def get(self, request):
    c_batch_18 = list()
    n_batch_18 = list()
    c_batch_19 = list()
    n_batch_19 = list()
    c_batch_20 = list()
    n_batch_20 = list()
    c_batch_21 = list()
    n_batch_21 = list()

    for entry in self.get_my_count():
        c_batch_18.append(entry['complete'] * entry['allocated_time'])
        n_batch_18.append(entry['not_complete'] * entry['allocated_time'])
        c_batch_19.append(entry['complete_1'] * entry['allocated_time'])
        n_batch_19.append(entry['not_complete_1'] * entry['allocated_time'])
        c_batch_20.append(entry['complete_2'] * entry['allocated_time'])
        n_batch_20.append(entry['not_complete_2'] * entry['allocated_time'])
        c_batch_21.append(entry['complete_3'] * entry['allocated_time'])
        n_batch_21.append(entry['not_complete_3'] * entry['allocated_time'])

    survived_series = [sum(c_batch_18), sum(c_batch_19), sum(c_batch_20), sum(c_batch_21), 0]
    not_survived_series = [sum(n_batch_18), sum(n_batch_19), sum(n_batch_20), sum(n_batch_21), 0]

    return render(request, 'chart.html', {'survived_series': json.dumps(survived_series),
                                          'not_survived_series': json.dumps(not_survived_series)})

class ChartElectrical(ShowChart):
   def get_my_count(self):
      # overriding get_my_count function
      my_count = Electrical.objects.values(...)
      return my_count

可能的优化

另外,这里有一些优化思路:

1.可以通过注解进行c_batch_18n_batch_18等计算。像这样:

from django.db.models import ExpressionWrapper, IntegerField

mycount = mycount.annotate(c_batch_18=ExpressionWrapper(
            F('complete') * F('allocated_time'), output_field=IntegerField()))
         .annotate(n_batch_18=ExpressionWrapper(
            F('not_complete') * F('allocated_time'), output_field=IntegerField())) # and so on

2. 也可以通过聚合计算Sum

from django.db.models import Sum

my_count_sums = my_count.aggregate(c_batch_18_sum=Sum('c_batch_18'), n_batch_18=Sum('n_batch_18')) # and so on

survived = list(filter(lambda x: x.key().startswith('c_batch'), my_count_sums))

not_survived = list(filter(lambda x: x.key().startswith('n_batch'), my_count_sums))

通过使用这些优化,您将通过数据库完成大部分计算,而不是依赖 python 资源。