我有一些这样的模型:
class TypeBase(models.Model):
name = models.CharField(max_length=20)
class Meta:
abstract=True
class PersonType(TypeBase):
pass
class CompanyType(TypeBase):
pass
有了这个,我想创建一个包含所有这些字段类型的序列化器(序列化,反序列化,更新和保存)。
更具体地说,我只想要一个序列化程序(TypeBaseSerializer)在UI上打印Dropdown,序列化json响应,在post上反序列化并保存它以用于所有基于类型。
这样的事情:
class TypeBaseSerializer(serializers.Serializer):
class Meta:
model = TypeBase
fields = ('id', 'name')
有可能吗?
答案 0 :(得分:11)
您can't use ModelSerializer
一个抽象基础模型。
来自restframework.serializers:
if model_meta.is_abstract_model(self.Meta.model):
raise ValueError(
'Cannot use ModelSerializer with Abstract Models.'
)
我为类似的问题写了一个serializer_factory函数:
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,您可以根据需要使用工厂生成序列化程序:
def typebase_serializer_factory(mdl):
myserializer = serializer_factory(
mdl,fields=["id","name"],
#owner=HiddenField(default=CurrentUserDefault()),#Optional additional configuration for subclasses
)
return myserializer
现在实现不同的子类序列化器:
persontypeserializer = typebase_serializer_factory(PersonType)
companytypeserializer = typebase_serializer_factory(CompanyType)
答案 1 :(得分:5)
我认为以下方法更清洁。您可以为基本序列化程序将“abstract”字段设置为true,并为所有子序列化程序添加公共逻辑。
class TypeBaseSerializer(serializers.ModelSerializer):
class Meta:
model = TypeBase
fields = ('id', 'name')
abstract = True
def func(...):
# ... some logic
然后创建子序列化器并将其用于数据操作。
class PersonTypeSerializer(TypeBaseSerializer):
class Meta:
model = PersonType
fields = ('id', 'name')
class CompanyTypeSerializer(TypeBaseSerializer):
class Meta:
model = CompanyType
fields = ('id', 'name')
现在,您可以为每个模型正常使用这两个序列化程序。
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。这更清洁:)
答案 2 :(得分:3)
在@ adki的回答中重复一下:
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
答案 3 :(得分:0)
正如Sebastian Wozny's answer中已经提到的那样,您不能将ModelSerializer与抽象基础模型一起使用。
此外,正如其他一些答案所建议的那样,没有什么像抽象的序列化程序那样。因此,在序列化程序的元类上设置abstract = True
将不起作用。
但是,您不必使用ModelSerializer
作为基本/父序列化程序。您可以使用Serializer
,然后利用Django的多重继承。运作方式如下:
class TypeBaseSerializer(serializers.Serializer):
# Need to re-declare fields since this is not a ModelSerializer
name = serializers.CharField()
id = serializers.CharField()
class Meta:
fields = ['id', 'name']
def someFunction(self):
#... will be available on child classes ...
pass
class PersonTypeSerializer(TypeBaseSerializer, serializers.ModelSerializer):
class Meta:
model = PersonType
fields = TypeBaseSerializer.Meta.fields + ['another_field']
class CompanyTypeSerializer(TypeBaseSerializer, serializers.ModelSerializer):
class Meta:
model = CompanyType
fields = TypeBaseSerializer.Meta.fields + ['some_other_field']
因此,由于字段name
和id
是在父类(TypeBaseSerializer)上声明的,因此它们将在PersonTypeSerializer
上可用,并且由于这是{{1 }}这些字段将从模型实例中填充。
即使它不是ModelSerializer,也可以在ModelSerializer
上使用SerializerMethodField
。
TypeBaseSerializer