Type-Safe Pydantic Schemas for Django JSONFields
Project description
Type-Safe Pydantic Schemas for Django JSONFields
django-pydantic-field provides a way to use Pydantic models as schemas for Django's JSONField.
It offers full support for Pydantic v1 and v2, type safety and integration with Django's ecosystem, including Forms and Django REST Framework.
Highlights
- Unified API: Transparent support for Pydantic v1 and v2 through the
SchemaAdapters. - Type-Safe: Support for static type checking (ty/mypy/pyright) with type inference for models and annotations.
- Forward References: Lazy resolution of forward references, allowing schemas to be defined anywhere.
- Django Integration: Support for Django Forms and the Admin interface.
- DRF Support: Typed Serializers, Parsers, and Renderers with automatic OpenAPI schema generation via DRF's native schema generator.
Installation
pip install django-pydantic-field
Basic Usage
The SchemaField can be used by passing the schema as the first argument (Django-like style) or by using type annotations.
import pydantic
import typing
from django.db import models
from django_pydantic_field import SchemaField
class Foo(pydantic.BaseModel):
count: int
slug: str = "default"
class MyModel(models.Model):
# Django-like style (explicit schema)
bar = SchemaField(Foo, default={"count": 5})
# Annotation-based style (Pydantic-like)
foo: Foo = SchemaField()
# Supports standard Python types and annotations
items: list[Foo] = SchemaField(default=list)
# null=True correctly infers t.Optional[Foo] for type checkers
optional_foo = SchemaField(Foo, null=True, default=None)
model = MyModel(foo={"count": 42})
model.save()
# Data is automatically parsed into Pydantic models
assert isinstance(model.foo, Foo)
assert model.foo.count == 42
typing.assert_type(model.optional_foo, Foo | None)
Supported Types
Any type supported by Pydantic can be used as a schema:
pydantic.BaseModelandpydantic.RootModel(v2)- Standard Python types (
list[str],dict[int, float], etc.) dataclasses.dataclassandTypedDictprotocolstyping.Annotatedwith metadata.
from typing import Annotated
from pydantic import Field
class AdvancedModel(models.Model):
# Annotated with validation rules
positive_ints: Annotated[list[int], Field(min_length=1)] = SchemaField()
Forward References & Lazy Resolution
SchemaField supports forward references via string literals or typing.ForwardRef. Resolution is deferred until the first time the field is accessed.
import typing
class MyModel(models.Model):
foo = SchemaField(typing.ForwardRef("DeferredFoo"))
another_foo: "DeferredFoo" = SchemaField()
class DeferredFoo(pydantic.BaseModel):
...
Pydantic Version Support
The package automatically detects the Pydantic version in your environment and adapts accordingly.
For Pydantic v2 environments, you can still explicitly use Pydantic v1 models by importing from the .v1 subpackage:
from pydantic import v1 as pydantic_v1
from django_pydantic_field.v1 import SchemaField as SchemaFieldV1
class LegacySchema(pydantic_v1.BaseModel):
...
class LegacyModel(models.Model):
legacy_field = SchemaFieldV1(LegacySchema)
Django Forms & Admin
It is possible to create Django forms, which would validate against the given schema:
from django import forms
from django_pydantic_field.forms import SchemaField
class FooForm(forms.Form):
field = SchemaField(Foo)
form = FooForm(data={"field": '{"slug": "asdf", "count": 1}'})
assert form.is_valid()
django-jsonform support
For a better user experience in the Admin, you can use django-jsonform, which provides a dynamic editor based on the Pydantic model's JSON schema.
from django.contrib import admin
from django_pydantic_field import fields
from django_jsonform.widgets import JSONFormWidget
class MyModelAdmin(admin.ModelAdmin):
formfield_overrides = {
fields.PydanticSchemaField: {"widget": JSONFormWidget},
}
Django REST Framework
Serializers
from rest_framework import serializers
from django_pydantic_field.rest_framework import SchemaField
class MySerializer(serializers.Serializer):
pydantic_field = SchemaField(Foo)
Typed Views (Parsers & Renderers)
You can use SchemaParser and SchemaRenderer to handle Pydantic models directly in your views.
from rest_framework.decorators import api_view, parser_classes, renderer_classes
from rest_framework.response import Response
from django_pydantic_field.rest_framework import SchemaParser, SchemaRenderer
@api_view(["POST"])
@parser_classes([SchemaParser[Foo]])
@renderer_classes([SchemaRenderer[list[Foo]]])
def foo_view(request):
# request.data is a Foo instance
instance: Foo = request.data
return Response([instance])
OpenAPI Generation
django-pydantic-field provides an AutoSchema that automatically generates OpenAPI definitions for your Pydantic-backed DRF components.
from django_pydantic_field.rest_framework import AutoSchema
class SampleView(generics.RetrieveAPIView):
serializer_class = MySerializer
schema = AutoSchema()
System Checks
The field performs validation during Django's manage.py check command:
pydantic.E001: Schema resolution errors.pydantic.E002: Default value serialization errors.pydantic.W003: Data integrity warnings forinclude/excludeconfigurations.
Contributing
To get django-pydantic-field up and running in development mode:
- Install
uv; - Install the project and its dependencies:
uv sync; - Setup
pre-commit:pre-commit install. - Run tests:
make test. - Run linters:
make lint.
Acknowledgement
- Churkin Oleg for his Gist as a source of inspiration
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