Pydantic2Django

Generate Django models from Pydantic models, Python dataclasses, or plain typed classes — and convert data back and forth reliably.

Features

• Automatic Django model generation (models.py) from your Python types
• Bidirectional mapping: use .from_pydantic() and .to_pydantic() on generated models
• Relationship handling: ForeignKey and ManyToManyField inferred from your types
• Type-hint aware: supports Optional, Union, Literal, and common collections
• Modular design: separate pipelines for Pydantic, Dataclasses, and Typed classes

Quickstart

1) Install

pip install pydantic2django

2) Define your Pydantic models

import uuid
from pydantic import BaseModel, Field

class User(BaseModel):
    id: uuid.UUID = Field(default_factory=uuid.uuid4)
    name: str
    email: str

class Product(BaseModel):
    id: uuid.UUID = Field(default_factory=uuid.uuid4)
    name: str
    price: float
    owner: User

3) Generate a models.py file

from pydantic2django.pydantic.generator import StaticPydanticModelGenerator

generator = StaticPydanticModelGenerator(
    output_path="my_app/models.py",
    packages=["my_app.pydantic_models"],
    app_label="my_app",
    verbose=True,
)

# Write my_app/models.py
generator.generate()

4) Use the generated models

from my_app.models import User as DjangoUser
from my_app.pydantic_models import User as PydanticUser

p_user = PydanticUser(name="Jane Doe", email="jane.doe@example.com")

# Create Django instance from Pydantic
dj_user = DjangoUser.from_pydantic(p_user)
dj_user.save()

# Convert back to Pydantic
assert dj_user.to_pydantic().name == "Jane Doe"

How it works

1. Discovery: scan packages to find your source models
2. Factory: analyze fields, type hints, and relationships
3. Generator: render a complete models.py with imports, classes, and fields

Explore next

• Architecture: high-level design and internals
• Docs: documentation files colocated with source code
• API: full reference generated from the code

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