Use pydantic with the Django REST framework
Project description
Use pydantic with Django REST framework
Introduction
Pydantic is a Python library used to perform data serialization and validation.
Django REST framework is a framework built on top of Django used to write REST APIs.
If you develop DRF APIs and rely on pydantic for data validation/(de)serialization ,
then drf-pydantic
is for you 😍.
ℹ️ INFO
>drf_pydantic
supportspydantic
v2. Due to breaking API changes inpydantic
v2 support forpydantic
v1 is available only indrf_pydantic
1.*.*.
Performance
Translation between pydantic
models and DRF
serializers is done during class
creation (e.g., when you first import the model). This means that there will be
zero impact on the performance of your application
(server instance or serverless session)
when using drf_pydantic
while your application is running.
Installation
pip install drf-pydantic
Usage
General
Use drf_pydantic.BaseModel
instead of pydantic.BaseModel
when creating your
models:
from drf_pydantic import BaseModel
class MyModel(BaseModel):
name: str
addresses: list[str]
MyModel.drf_serializer
would be equvalent to the following DRF Serializer class:
class MyModelSerializer:
name = CharField(allow_null=False, required=True)
addresses = ListField(
allow_empty=True,
allow_null=False,
child=CharField(allow_null=False),
required=True,
)
Whenever you need a DRF serializer you can get it from the model like this:
my_value = MyModel.drf_serializer(data={"name": "Van", addresses: ["Gym"]})
my_value.is_valid(raise_exception=True)
ℹ️ INFO
Models created usingdrf_pydantic
are fully idenditcal to those created bypydantic
. The only change is the addition of thedrf_serializer
attribute.
Existing Models
If you have an existing code base and you would like to add the drf_serializer
attribute only to some of your models, then I have great news 🥳 - you can easily
extend your existing pydantic
models by adding drf_pydantic.BaseModel
to the list
of parent classes of the model you want to extend.
Your existing pydantic models:
from pydantic import BaseModel
class Pet(BaseModel):
name: str
class Dog(Pet):
breed: str
Update your Dog
model and get serializer via the drf_serializer
:
from drf_pydantic import BaseModel as DRFBaseModel
from pydantic import BaseModel
class Pet(BaseModel):
name: str
class Dog(DRFBaseModel, Pet):
breed: str
Dog.drf_serializer
⚠️ ATTENTION
Inheritance order is important:drf_pydantic.BaseModel
must always go before thepydantic.BaseModel
class.
Nested Models
If you have nested models and you want to generate serializer only from one of them,
you don't have to update all models - only update the model you need, drf_pydantic
will generate serializers for all normal nested pydantic
models for free 🥷.
from drf_pydantic import BaseModel as DRFBaseModel
from pydantic import BaseModel
class Apartment(BaseModel):
floor: int
tenant: str
class Building(BaseModel):
address: str
aparments: list[Apartment]
class Block(DRFBaseModel):
buildings: list[Buildind]
Block.drf_serializer
Manual Serializer Configuration
If drf_pydantic
does not generate the serializer you need, you can either granularly
configure which DRF serializer fields to use for each pydantic field, or you can
create a custom serializer for the model altogether.
⚠️ WARNING
When manually configuring the serializer you are responsible for setting all properties of the fields (e.g.,allow_null
,required
,default
, etc.).drf_pydantic
does not perform any introspection for fields that are manually configured or for any fields if a custom serializer is used.
Per-Field Configuration
from typing import Annotated
from drf_pydantic import BaseModel
from rest_framework.serializers import IntegerField
class Person(BaseModel):
name: str
age: Annotated[float, IntegerField(min_value=0, max_value=100)]
Custom Serializer
In example below, Person
will use MyCustomSerializer
as its drf serializer.
Employee
will have its own serializer generated by drf_pydantic
because it
does not have a user-defined drf_serializer
attribute (it's never inherited).
Company
will have its own serializer generated by drf_pydantic
and it will use
Person
's manually-defined serializer for its ceo
field.
from drf_pydantic import BaseModel
from rest_framework.serializers import Serializer
class MyCustomSerializer(Serializer):
name = CharField(allow_null=False, required=True)
age = IntegerField(allow_null=False, required=True)
class Person(BaseModel):
name: str
age: float
drf_serializer = MyCustomSerializer
class Employee(Person):
salary: float
class Company(BaseModel):
ceo: Person
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