🚀 Generate Python data models from schema definitions in seconds.

• 📄 Converts OpenAPI 3, JSON Schema, GraphQL, and raw data (JSON/YAML/CSV) into Python models
• 🎯 Generates Pydantic v1/v2, dataclasses, TypedDict, or msgspec output
• 🔗 Handles complex schemas: $ref, allOf, oneOf, anyOf, enums, and nested types
• ✅ Produces type-safe, validated code ready for your IDE and type checker

👉 koxudaxi.github.io/datamodel-code-generator

• 🖥️ CLI Reference - All command-line options
• ⚙️ pyproject.toml - Configuration file
• 🔄 CI/CD Integration - GitHub Actions, pre-commit hooks
• 🚀 One-liner Usage - uvx, pipx, clipboard integration
• ❓ FAQ - Common questions

pip install datamodel-code-generator

uv add datamodel-code-generator

conda install -c conda-forge datamodel-code-generator

pip install 'datamodel-code-generator[http]'

pip install 'datamodel-code-generator[graphql]'

docker pull koxudaxi/datamodel-code-generator

datamodel-codegen --input schema.json --input-file-type jsonschema --output-model-type pydantic_v2.BaseModel --output model.py

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Pet",
  "type": "object",
  "required": ["name", "species"],
  "properties": {
    "name": {
      "type": "string",
      "description": "The pet's name"
    },
    "species": {
      "type": "string",
      "enum": ["dog", "cat", "bird", "fish"]
    },
    "age": {
      "type": "integer",
      "minimum": 0,
      "description": "Age in years"
    },
    "vaccinated": {
      "type": "boolean",
      "default": false
    }
  }
}

# generated by datamodel-codegen:
#   filename:  schema.json

from __future__ import annotations

from enum import Enum
from typing import Optional

from pydantic import BaseModel, Field


class Species(Enum):
    dog = 'dog'
    cat = 'cat'
    bird = 'bird'
    fish = 'fish'


class Pet(BaseModel):
    name: str = Field(..., description="The pet's name")
    species: Species
    age: Optional[int] = Field(None, description='Age in years', ge=0)
    vaccinated: Optional[bool] = False

• OpenAPI 3 (YAML/JSON)
• JSON Schema
• JSON / YAML / CSV data
• GraphQL schema
• Python dictionary

• pydantic v1 BaseModel
• pydantic v2 BaseModel
• dataclasses
• TypedDict
• msgspec Struct

datamodel-codegen --input schema.json --input-file-type jsonschema --output-model-type pydantic_v2.BaseModel --output model.py

pip install 'datamodel-code-generator[http]'
datamodel-codegen --url https://example.com/api/openapi.yaml --input-file-type openapi --output-model-type pydantic_v2.BaseModel --output model.py

[tool.datamodel-codegen]
input = "schema.yaml"
input-file-type = "openapi"
output = "src/models.py"
output-model-type = "pydantic_v2.BaseModel"

See pyproject.toml Configuration for more options.

datamodel-codegen --check

Verify generated code stays in sync with schemas. See CI/CD Integration for GitHub Actions and pre-commit hooks.

Astral

These projects use datamodel-code-generator. See the linked examples for real-world usage.

• PostHog/posthog - Generate models via npm run
• airbytehq/airbyte - Generate Python, Java/Kotlin, and Typescript protocol models
• apache/iceberg - Generate Python code
• open-metadata/OpenMetadata - datamodel_generation.py
• awslabs/aws-lambda-powertools-python - Recommended for advanced-use-cases
• Netflix/consoleme - Generate models from Swagger
• DataDog/integrations-core - Config models
• argoproj-labs/hera - Makefile
• SeldonIO/MLServer - generate-types.sh
• geojupyter/jupytergis - Python type generation from JSONSchema
• Nike-Inc/brickflow - Code generate tools
• cloudcoil/cloudcoil - Model generation
• IBM/compliance-trestle - Building models from OSCAL schemas
• hashintel/hash - codegen.sh

See all dependents →

• fastapi-code-generator - Generate FastAPI app from OpenAPI
• pydantic-pycharm-plugin - PyCharm plugin for Pydantic

See Development & Contributing for how to get started!

MIT License - see LICENSE for details.