A dataclasses serializer for the Django REST Framework.
- Python (3.7+)
- Django (2.0+)
- Django REST Framework (3.9+)
These are the supported Python and package versions. Older versions will probably work as well, but haven't been tested by the author.
$ pip install djangorestframework-dataclasses
The package provides the DataclassSerializer serializer, defined in the rest_framework_dataclasses.serializers
namespace.
from rest_framework_dataclasses.serializers import DataclassSerializerThis serializer provides a shortcut that lets you automatically create a Serializer class with fields that
correspond to the fields on a dataclass. In usage, the DataclassSerializer is the same as a regular Serializer
class, except that:
- It will automatically generate fields for you, based on the declaration in the dataclass.
- To make this possible it requires that a
dataclassproperty is specified in theMetasubclass, with as value a dataclass that has type annotations. - It includes simple default implementations of
.create()and.update().
For example, define a dataclass as follows:
@dataclass
class Person:
name: str
email: str
alive: bool
gender: typing.Literal['male', 'female']
birth_date: typing.Optional[datetime.date]
phone: typing.List[str]
movie_ratings: typing.Dict[str, int]
def age(self) -> int:
return datetime.date.today().year - self.birth_date.yearThe serializer for this dataclass can now trivially be defined without having to duplicate all fields:
class PersonSerializer(DataclassSerializer):
class Meta:
dataclass = Person
# is equivalent to
class PersonSerializer(Serializer):
name = fields.CharField()
email = fields.CharField()
alive = fields.BooleanField()
gender = fields.ChoiceField(choices=['male', 'female'])
birth_date = fields.DateField(allow_null=True)
phone = fields.ListField(child=fields.CharField())
movie_ratings = fields.DictField(child=fields.IntegerField())Note that this usage pattern is very similar to that of the built-in ModelSerializer. This is intentional, with the
whole API modelled after that of ModelSerializer.
You can add extra fields or override default fields by declaring them explicitly on the class, just as you would for a
regular Serializer class. This allows to specify extra options or change the field type.
class PersonSerializer(Serializer):
email = fields.EmailField()
class Meta:
dataclass = PersonTo customize the generated fields, the DataclassSerializer accepts the following options in the Meta class. All
options have the same behaviour as the identical options in ModelSerializer.
dataclassspecifies the type of dataclass used by the serializer. This is equivalent to themodeloption inModelSerializer.fieldsandexcludecan be used to specify which fields should respectively be included and excluded in the serializer. These cannot both be specified.The
fieldsoption accepts the magic value__all__to specify that all fields on the dataclass should be used. This is also the default value, so it is not mandatory to specify eitherfieldsorexclude.read_only_fieldscan be used to mark a subset of fields as read-only.extra_kwargscan be used to specify arbitrary additional keyword arguments on fields. This can be useful to extend or change the autogenerated field without explicitly declaring the field on the serializer. This option should be a dictionary, mapping field names to a dictionary of keyword arguments.If the autogenerated field is a composite field (a list or dictionary), the arguments are applied to the composite field. To add keyword arguments to the composite fields child field (that is, the field used for the items in the list or dictionary) list), they should be specified as a nested dictionary under the
child_kwargsname (see Nesting with extra kwargs section below for an example).class PersonSerializer(DataclassSerializer): class Meta: extra_kwargs = { 'height': { 'decimal_places': 1 }, 'movie_ratings': { 'child_kwargs': { 'min_value': 0, 'max_value': 10 } } }
validatorsfunctionality is unchanged.depth(as known fromModelSerializer) is not yet supported.
If your dataclass has a field that contains a dataclass instance as well, the DataclassSerializer will
automatically create another DataclassSerializer for that field, so that its value will be nested. This also works
for dataclasses contained in lists or dictionaries, or even several layers deep.
@dataclass
class House:
address: str
owner: Person
residents: typing.List[Person]
class HouseSerializer(DataclassSerializer):
class Meta:
dataclass = HouseThis will serialize as:
>>> serializer = HouseSerializer(instance=house)
>>> serializer.data
{
'address': 'Main Street 5',
'owner': { 'name': 'Alice' }
'residents': [
{ 'name': 'Alice', 'email': 'alice@example.org', ... },
{ 'name': 'Bob', 'email': 'bob@example.org', ... },
{ 'name': 'Charles', 'email': 'charles@example.org', ... }
]
}This does not give the option to customize the field generation of the nested dataclasses. If that is needed, you should declare the serializer to be used explicitly.
Likewise, if your dataclass has a field that contains a Django model, the DataclassSerializer will automatically
generate a relational field for you.
class Company(models.Model):
name = models.CharField()
@dataclass
class Person:
name: str
employer: CompanyThis will serialize as:
>>> serializer = PersonSerializer(instance=user)
>>> print(repr(serializer))
PersonSerializer():
name = fields.CharField()
employer = fields.PrimaryKeyRelatedField(queryset=Company.objects.all())
>>> serializer.data
{
"name": "Alice",
"employer": 1
}If you want to nest the model in the serialized representation, you should specify the model serializer to be used by declaring the field explicitly.
If you prefer to use hyperlinks to represent relationships rather than primary keys, in the same package you can find
the HyperlinkedDataclassSerializer class: it generates a HyperlinkedRelatedField instead of a
PrimaryKeyRelatedField.
The extra_kwargs option can be nested, in order to provide kwargs to fields belonging to nested dataclasses.
Consider the following:
@dataclass
class Transaction:
amount: Decimal
account_number: str
@dataclass
class Company:
sales: List[Transaction]In order to tell DRF to give 2 decimal places to the transaction account number, write the serializer as follows:
class CompanySerializer(DataclassSerializer):
class Meta:
dataclass = Company
extra_kwargs = {
'sales': {
'child_kwargs': { # Required because sales is a List, otherwise you could have the extra_kwargs directly
'extra_kwargs': {
'amount': {
'max_digits': 6,
'decimal_places': 2
}
}
}
}
}The output of methods or properties on the dataclass can be included as a (read-only) field in the serialized state by adding their name to the
fieldsoption in theMetaclass.If you don't need to customize the generated fields,
DataclassSerializercan also be used directly without creating a subclass. In that case, the dataclass should be specified using thedataclassconstructor parameter:serializer = DataclassSerializer(data=request.data, dataclass=Person)
So far, field generation is supported for the following types and their subclasses:
str,bool,intandfloat.date,datetime,timeandtimedeltafrom thedatetimepackage.decimal.Decimal(requires specifyingmax_digitsanddecimal_placesthroughextra_kwargs).uuid.UUIDtyping.Iterable(includingtyping.List).typing.Mapping(includingtyping.Dict).typing.Literal(mapped to aChoiceField).django.db.Model
For advanced users, the DataclassSerializer also exposes an API that you can override in order to alter how
serializer fields are generated:
- The
serializer_field_mappingproperty contains a dictionary that maps types to REST framework serializer classes. You can override or extend this mapping to change the serializer field classes that are used for fields based on their type. - The
serializer_related_fieldis the serializer field class that is used for relations to models. - The
build_unknown_typed_field()method is called to create serializer field classes for types that it does not understand. By default this throws an error, but you can extend this with custom logic to create serializer fields. - The
build_standard_field(),build_relational_field(),build_nested_field()andbuild_property_field()methods are used to process respectively fields, embedded models, embedded dataclasses and properties. These can be overridden to change the field generation logic, but at that point it's usually a better idea to just declare the field explicitly.