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Datamodel Code Generator

Project description

datamodel-code-generator

๐Ÿš€ Generate Python data models from schema definitions in seconds.

๐Ÿงช Try it in your browser: Playground

[!NOTE] Playground privacy: generation runs locally in your browser with Pyodide. Schemas and options are not sent to a backend. Shared repro URLs encode them in the URL fragment (#state=...), which browsers do not send to the server; the full URL can still be stored in your browser history or wherever you share it.

PyPI version Conda-forge Downloads PyPI - Python Version codecov license Pydantic v2

๐Ÿ“ฃ ๐Ÿ’ผ Maintainer update: Open to opportunities. ๐Ÿ”— koxudaxi.dev

โœจ What it does

Schema files, raw data, and existing Python models flow through datamodel-code-generator into Python model output types

Pick any one of the supported inputs and pick the Python model style you want as output. --input-model path/to/file.py:ClassName can even retarget an existing Pydantic, dataclass, or TypedDict class defined in another Python file to a different output type.

  • ๐Ÿ“„ Converts OpenAPI 3, AsyncAPI, JSON Schema, Apache Avro, XML Schema, Protocol Buffers/gRPC, GraphQL, MCP tool schemas, and raw data (JSON/YAML/CSV) into Python models
  • ๐Ÿ Generates from existing Python types (Pydantic, dataclass, TypedDict) via --input-model
  • ๐ŸŽฏ Generates Pydantic v2, Pydantic v2 dataclass, dataclasses, TypedDict, or msgspec output
  • ๐Ÿ”— Handles complex schemas: $ref, allOf, oneOf, anyOf, enums, and nested types
  • โœ… Produces type-safe, validated code ready for your IDE and type checker

๐Ÿ“– Documentation

๐Ÿ‘‰ datamodel-code-generator.koxudaxi.dev


๐Ÿ“ฆ Installation

Recommended for standalone CLI use:

uv tool install datamodel-code-generator

For projects that should pin the generator version, add it as a development dependency instead:

uv add --dev datamodel-code-generator
Other installation methods

pip:

pip install datamodel-code-generator

uv (run without adding to project):

uv run --with datamodel-code-generator datamodel-codegen --help

conda:

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

With HTTP support (for resolving remote $ref):

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

With GraphQL support:

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

With Protocol Buffers support:

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

Docker:

docker pull koxudaxi/datamodel-code-generator

๐Ÿƒ Quick Start

datamodel-codegen --input schema.json --input-file-type jsonschema --output-model-type pydantic_v2.BaseModel --output model.py
๐Ÿ“„ schema.json (input)
{
  "$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
    }
  }
}
๐Ÿ model.py (output)
# 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

๐Ÿ“ฅ Supported Input

  • OpenAPI 3 (YAML/JSON)
  • AsyncAPI (YAML/JSON)
  • JSON Schema
  • Apache Avro schema (AVSC)
  • XML Schema (XSD)
  • Protocol Buffers / gRPC (.proto)
  • MCP tool schemas
  • JSON / YAML / CSV data
  • GraphQL schema
  • Python types (Pydantic, dataclass, TypedDict) via --input-model
  • Python dictionary

๐Ÿ“ค Supported Output


๐Ÿณ Common Recipes

๐Ÿค– Get CLI Help from LLMs

Generate a prompt to ask LLMs about CLI options:

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

See LLM Integration for more examples.

๐ŸŒ Generate from URL

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

โš™๏ธ Use with pyproject.toml

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

Then simply run:

datamodel-codegen

See pyproject.toml Configuration for more options.

๐Ÿ”„ CI/CD Integration

Validate generated models in your CI pipeline:

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

See CI/CD Integration for more options.


๐Ÿ’– Sponsors

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๐Ÿข Projects that use datamodel-code-generator

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

See all dependents โ†’


๐Ÿ”— Related Projects


๐Ÿค Contributing

See Development & Contributing for how to get started!

๐Ÿ“„ License

MIT License - see LICENSE for details.

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