2015-10-14 74 views
8

我有一些车型,如这些:Django的REST框架抽象类串行

class TypeBase(models.Model): 
    name = models.CharField(max_length=20) 
    class Meta: 
     abstract=True 

class PersonType(TypeBase): 
    pass 

class CompanyType(TypeBase): 
    pass 

到这一点,我想只创建一个串行包含所有这些字段类型(序列化,反序列化,更新和保存)。更具体地说,我只需要一个在UI上打印Dropdown的序列化程序(TypeBaseSerializer),序列化json响应,在后期将其反序列化并将其保存为所有基于我的类型。

事情是这样的:

class TypeBaseSerializer(serializers.Serializer): 
    class Meta: 
     model = TypeBase 
     fields = ('id', 'name') 

这可能吗?

+0

这个讨论也子类串行有用:https://github.com/tomchristie/django-rest-framework/issues/1926 – PhoebeB

回答

7

can't use a ModelSerializer与抽象的基本模型。 从restframework.serializers:

if model_meta.is_abstract_model(self.Meta.model): 
     raise ValueError(
      'Cannot use ModelSerializer with Abstract Models.' 
     ) 

我写了一个serializer_factory功能类似的问题:

from collections import OrderedDict 
from restframework.serializers import ModelSerializer 
def serializer_factory(mdl, fields=None, **kwargss): 
""" Generalized serializer factory to increase DRYness of code. 

:param mdl: The model class that should be instanciated 
:param fields: the fields that should be exclusively present on the serializer 
:param kwargss: optional additional field specifications 
:return: An awesome serializer 
""" 

    def _get_declared_fields(attrs): 
     fields = [(field_name, attrs.pop(field_name)) 
        for field_name, obj in list(attrs.items()) 
        if isinstance(obj, Field)] 
     fields.sort(key=lambda x: x[1]._creation_counter) 
     return OrderedDict(fields) 

    # Create an object that will look like a base serializer 
    class Base(object): 
     pass 

    Base._declared_fields = _get_declared_fields(kwargss) 

    class MySerializer(Base, ModelSerializer): 
     class Meta: 
      model = mdl 

     if fields: 
      setattr(Meta, "fields", fields) 

    return MySerializer 

然后,您可以使用工厂生产串行需要:

def typebase_serializer_factory(mdl): 
    myserializer = serializer_factory(
     mdl,fields=["id","name"], 
     #owner=HiddenField(default=CurrentUserDefault()),#Optional additional configuration for subclasses 
    ) 
    return myserializer 

现在instanciate不同的子类序列化程序:

persontypeserializer = typebase_serializer_factory(PersonType) 
companytypeserializer = typebase_serializer_factory(CompanyType) 
+0

该解决方案似乎为我的问题的工作,但有没有办法减少通用性?我认为在我的情况下,我会一直知道我的类型的领域,我只需要动态地实例化它。 –

+0

您可以为子类创建两个序列化器。我处于有7个子类和不同串行器模式的情况,所以通用性至关重要。 –

2

我认为以下方法更清洁。您可以将基本序列化器的“abstract”字段设置为true,并为所有子序列化器添加公共逻辑。

class TypeBaseSerializer(serializers.Serializer): 
    class Meta: 
     model = TypeBase 
     fields = ('id', 'name') 
     abstract = True 

    def func(...): 
    # ... some logic 

然后创建子序列化器并将它们用于数据操作。

class PersonTypeSerializer(TypeBaseSerializer): 
    class Meta: 
     model = PersonType 
     fields = ('id', 'name') 


class CompanyTypeSerializer(TypeBaseSerializer): 
    class Meta: 
     model = CompanyType 
     fields = ('id', 'name') 

现在你可以使用这两种串行器通常为每个模型。

但是,如果你真的想为两个模型都有一个序列化器,那么也为他创建一个容器模型和一个序列化器。这是干净多了:)

0

只是迭代有点过@ adki的回答是:

  1. 有可能跳过型号为TypeBaseSerializer;
  2. 派生序列化器可以引用TypeBaseSerializer.meta.fields,所以你可以在一个地方改变它们。
class TypeBaseSerializer(serializers.Serializer): 
    class Meta: 
     fields = ('id', 'name', 'created') 
     abstract = True 

    def func(...): 
    # ... some logic 

class PersonTypeSerializer(TypeBaseSerializer): 
    class Meta: 
     model = PersonType 
     fields = TypeBaseSerializer.meta.fields + ('age', 'date_of_birth') 

class CompanyTypeSerializer(TypeBaseSerializer): 
    class Meta: 
     model = CompanyType 
     fields = TypeBaseSerializer.meta.fields