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🚀 Generate Python data models from schema definitions in seconds.

• 📄 ConvertsOpenAPI 3,JSON Schema,GraphQL, and raw data (JSON/YAML/CSV) into Python models
• 🐍 Generates fromexisting Python types (Pydantic, dataclass, TypedDict) via--input-model
• 🎯 GeneratesPydantic v1/v2,dataclasses,TypedDict, ormsgspec output
• 🔗 Handles complex schemas:$ref,allOf,oneOf,anyOf, enums, and nested types
• ✅ Produces type-safe, validated code ready for your IDE and type checker

👉datamodel-code-generator.koxudaxi.dev

• 🖥️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

uv tool install datamodel-code-generator

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.jsonfrom __future__importannotationsfromenumimportEnumfromtypingimportOptionalfrompydanticimportBaseModel,FieldclassSpecies(Enum):dog='dog'cat='cat'bird='bird'fish='fish'classPet(BaseModel):name:str=Field(...,description="The pet's name")species:Speciesage: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 types (Pydantic, dataclass, TypedDict) via--input-model
• Python dictionary

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

Generate a prompt to ask LLMs about CLI options:

datamodel-codegen --generate-prompt"Best options for Pydantic v2?"| claude -p

SeeLLM Integration for more examples.

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

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

Then simply run:

datamodel-codegen

Seepyproject.toml Configuration for more options.

Validate generated models in your CI pipeline:

-uses:koxudaxi/datamodel-code-generator@0.44.0with:input:schemas/api.yamloutput:src/models/api.py

SeeCI/CD Integration for more options.

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

SeeDevelopment & Contributing for how to get started!

MIT License - seeLICENSE for details.