/datamodel-code-generator

Pydantic model and dataclasses.dataclass generator for easy conversion of JSON, OpenAPI, JSON Schema, and YAML data sources.

Primary LanguagePythonMIT LicenseMIT

datamodel-code-generator

This code generator creates pydantic v1 and v2 model, dataclasses.dataclass, typing.TypedDict and msgspec.Struct from an openapi file and others.

PyPI version Conda-forge Downloads PyPI - Python Version codecov license Ruff Pydantic v1 Pydantic v2

Help

See documentation for more details.

Sponsors

JetBrains

Quick Installation

To install datamodel-code-generator:

$ pip install datamodel-code-generator

Simple Usage

You can generate models from a local file.

$ datamodel-codegen --input api.yaml --output model.py
api.yaml 
openapi: "3.0.0"
info:
  version: 1.0.0
  title: Swagger Petstore
  license:
    name: MIT
servers:
  - url: http://petstore.swagger.io/v1
paths:
  /pets:
    get:
      summary: List all pets
      operationId: listPets
      tags:
        - pets
      parameters:
        - name: limit
          in: query
          description: How many items to return at one time (max 100)
          required: false
          schema:
            type: integer
            format: int32
      responses:
        '200':
          description: A paged array of pets
          headers:
            x-next:
              description: A link to the next page of responses
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Pets"
        default:
          description: unexpected error
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Error"
                x-amazon-apigateway-integration:
                  uri:
                    Fn::Sub: arn:aws:apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/${PythonVersionFunction.Arn}/invocations
                  passthroughBehavior: when_no_templates
                  httpMethod: POST
                  type: aws_proxy
    post:
      summary: Create a pet
      operationId: createPets
      tags:
        - pets
      responses:
        '201':
          description: Null response
        default:
          description: unexpected error
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Error"
                x-amazon-apigateway-integration:
                  uri:
                    Fn::Sub: arn:aws:apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/${PythonVersionFunction.Arn}/invocations
                  passthroughBehavior: when_no_templates
                  httpMethod: POST
                  type: aws_proxy
  /pets/{petId}:
    get:
      summary: Info for a specific pet
      operationId: showPetById
      tags:
        - pets
      parameters:
        - name: petId
          in: path
          required: true
          description: The id of the pet to retrieve
          schema:
            type: string
      responses:
        '200':
          description: Expected response to a valid request
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Pets"
        default:
          description: unexpected error
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Error"
    x-amazon-apigateway-integration:
      uri:
        Fn::Sub: arn:aws:apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/${PythonVersionFunction.Arn}/invocations
      passthroughBehavior: when_no_templates
      httpMethod: POST
      type: aws_proxy
components:
  schemas:
    Pet:
      required:
        - id
        - name
      properties:
        id:
          type: integer
          format: int64
        name:
          type: string
        tag:
          type: string
    Pets:
      type: array
      items:
        $ref: "#/components/schemas/Pet"
    Error:
      required:
        - code
        - message
      properties:
        code:
          type: integer
          format: int32
        message:
          type: string
    apis:
      type: array
      items:
        type: object
        properties:
          apiKey:
            type: string
            description: To be used as a dataset parameter value
          apiVersionNumber:
            type: string
            description: To be used as a version parameter value
          apiUrl:
            type: string
            format: uri
            description: "The URL describing the dataset's fields"
          apiDocumentationUrl:
            type: string
            format: uri
            description: A URL to the API console for each API
model.py 
# generated by datamodel-codegen:
#   filename:  api.yaml
#   timestamp: 2020-06-02T05:28:24+00:00

from __future__ import annotations

from typing import List, Optional

from pydantic import AnyUrl, BaseModel, Field


class Pet(BaseModel):
    id: int
    name: str
    tag: Optional[str] = None


class Pets(BaseModel):
    __root__: List[Pet]


class Error(BaseModel):
    code: int
    message: str


class Api(BaseModel):
    apiKey: Optional[str] = Field(
        None, description='To be used as a dataset parameter value'
    )
    apiVersionNumber: Optional[str] = Field(
        None, description='To be used as a version parameter value'
    )
    apiUrl: Optional[AnyUrl] = Field(
        None, description="The URL describing the dataset's fields"
    )
    apiDocumentationUrl: Optional[AnyUrl] = Field(
        None, description='A URL to the API console for each API'
    )


class Apis(BaseModel):
    __root__: List[Api]

Projects that use datamodel-code-generator

These OSS projects use datamodel-code-generator to generate many models. See the following linked projects for real world examples and inspiration.

Supported input types

Supported output types

Installation

To install datamodel-code-generator:

$ pip install datamodel-code-generator

http extra option

If you want to resolve $ref for remote files then you should specify http extra option.

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

graphql extra option

If you want to generate data model from a GraphQL schema then you should specify graphql extra option.

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

Docker Image

The docker image is in Docker Hub

$ docker pull koxudaxi/datamodel-code-generator

Advanced Uses

You can generate models from a URL.

$ datamodel-codegen --url https://<INPUT FILE URL> --output model.py

This method needs the http extra option

All Command Options

The datamodel-codegen command:

usage:
  datamodel-codegen [options]

Generate Python data models from schema definitions or structured data

Options:
  --http-headers HTTP_HEADER [HTTP_HEADER ...]
                        Set headers in HTTP requests to the remote host.
                        (example: "Authorization: Basic dXNlcjpwYXNz")
  --http-ignore-tls     Disable verification of the remote host's TLS
                        certificate
  --input INPUT         Input file/directory (default: stdin)
  --input-file-type {auto,openapi,graphql,jsonschema,json,yaml,dict,csv}
                        Input file type (default: auto)
  --output OUTPUT       Output file (default: stdout)
  --output-model-type {pydantic.BaseModel,pydantic_v2.BaseModel,dataclasses.dataclass,typing.TypedDict,msgspec.Struct}
  --url URL             Input file URL. `--input` is ignored when `--url` is
                        used

Typing customization:
  --base-class BASE_CLASS
                        Base Class (default: pydantic.BaseModel)
  --enum-field-as-literal {all,one}
                        Parse enum field as literal. all: all enum field type
                        are Literal. one: field type is Literal when an enum
                        has only one possible value
  --field-constraints   Use field constraints and not con* annotations
  --set-default-enum-member
                        Set enum members as default values for enum field
  --strict-types {str,bytes,int,float,bool} [{str,bytes,int,float,bool} ...]
                        Use strict types
  --use-annotated       Use typing.Annotated for Field(). Also, `--field-
                        constraints` option will be enabled.
  --use-generic-container-types
                        Use generic container types for type hinting
                        (typing.Sequence, typing.Mapping). If `--use-standard-
                        collections` option is set, then import from
                        collections.abc instead of typing
  --use-non-positive-negative-number-constrained-types
                        Use the Non{Positive,Negative}{FloatInt} types instead
                        of the corresponding con* constrained types.
  --use-one-literal-as-default
                        Use one literal as default value for one literal field
  --use-standard-collections
                        Use standard collections for type hinting (list, dict)
  --use-subclass-enum   Define Enum class as subclass with field type when
                        enum has type (int, float, bytes, str)
  --use-union-operator  Use | operator for Union type (PEP 604).
  --use-unique-items-as-set
                        define field type as `set` when the field attribute
                        has `uniqueItems`

Field customization:
  --capitalise-enum-members, --capitalize-enum-members
                        Capitalize field names on enum
  --empty-enum-field-name EMPTY_ENUM_FIELD_NAME
                        Set field name when enum value is empty (default: `_`)
  --field-extra-keys FIELD_EXTRA_KEYS [FIELD_EXTRA_KEYS ...]
                        Add extra keys to field parameters
  --field-extra-keys-without-x-prefix FIELD_EXTRA_KEYS_WITHOUT_X_PREFIX [FIELD_EXTRA_KEYS_WITHOUT_X_PREFIX ...]
                        Add extra keys with `x-` prefix to field parameters.
                        The extra keys are stripped of the `x-` prefix.
  --field-include-all-keys
                        Add all keys to field parameters
  --force-optional      Force optional for required fields
  --original-field-name-delimiter ORIGINAL_FIELD_NAME_DELIMITER
                        Set delimiter to convert to snake case. This option
                        only can be used with --snake-case-field (default: `_`
                        )
  --remove-special-field-name-prefix
                        Remove field name prefix if it has a special meaning
                        e.g. underscores
  --snake-case-field    Change camel-case field name to snake-case
  --special-field-name-prefix SPECIAL_FIELD_NAME_PREFIX
                        Set field name prefix when first character can't be
                        used as Python field name (default: `field`)
  --strip-default-none  Strip default None on fields
  --use-default         Use default value even if a field is required
  --use-default-kwarg   Use `default=` instead of a positional argument for
                        Fields that have default values.
  --use-field-description
                        Use schema description to populate field docstring

Model customization:
  --allow-extra-fields  Allow to pass extra fields, if this flag is not
                        passed, extra fields are forbidden.
  --allow-population-by-field-name
                        Allow population by field name
  --class-name CLASS_NAME
                        Set class name of root model
  --collapse-root-models
                        Models generated with a root-type field will be
                        mergedinto the models using that root-type model
  --disable-appending-item-suffix
                        Disable appending `Item` suffix to model name in an
                        array
  --disable-timestamp   Disable timestamp on file headers
  --enable-faux-immutability
                        Enable faux immutability
  --enable-version-header
                        Enable package version on file headers
  --keep-model-order    Keep generated models' order
  --reuse-model         Reuse models on the field when a module has the model
                        with the same content
  --target-python-version {3.6,3.7,3.8,3.9,3.10,3.11}
                        target python version (default: 3.7)
  --use-schema-description
                        Use schema description to populate class docstring
  --use-title-as-name   use titles as class names of models

Template customization:
  --aliases ALIASES     Alias mapping file
  --custom-file-header CUSTOM_FILE_HEADER
                        Custom file header
  --custom-file-header-path CUSTOM_FILE_HEADER_PATH
                        Custom file header file path
  --custom-template-dir CUSTOM_TEMPLATE_DIR
                        Custom template directory
  --encoding ENCODING   The encoding of input and output (default: UTF-8)
  --extra-template-data EXTRA_TEMPLATE_DATA
                        Extra template data
  --use-double-quotes   Model generated with double quotes. Single quotes or
                        your black config skip_string_normalization value will
                        be used without this option.
  --wrap-string-literal
                        Wrap string literal by using black `experimental-
                        string-processing` option (require black 20.8b0 or
                        later)
  --additional-imports  Custom imports for output (delimited list input).
                        For example "datetime.date,datetime.datetime"
  --custom-formatters   List of modules with custom formatter (delimited list input).
  --custom-formatters-kwargs A file with kwargs for custom formatters.

OpenAPI-only options:
  --openapi-scopes {schemas,paths,tags,parameters} [{schemas,paths,tags,parameters} ...]
                        Scopes of OpenAPI model generation (default: schemas)
  --strict-nullable     Treat default field as a non-nullable field (Only
                        OpenAPI)
  --use-operation-id-as-name
                        use operation id of OpenAPI as class names of models
  --validation          Deprecated: Enable validation (Only OpenAPI). this
                        option is deprecated. it will be removed in future
                        releases

General options:
  --debug               show debug message (require "debug". `$ pip install 'datamodel-code-generator[debug]'`)
  --disable-warnings    disable warnings
  --no-color            disable colorized output
  --version             show version
  -h, --help            show this help message and exit

Related projects

fastapi-code-generator

This code generator creates FastAPI app from an openapi file.

https://github.com/koxudaxi/fastapi-code-generator

pydantic-pycharm-plugin

A JetBrains PyCharm plugin for pydantic.

https://github.com/koxudaxi/pydantic-pycharm-plugin

PyPi

https://pypi.org/project/datamodel-code-generator

Contributing

See docs/development-contributing.md for how to get started!

License

datamodel-code-generator is released under the MIT License. http://www.opensource.org/licenses/mit-license