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Custom Class Decorators

The --class-decorators option adds custom decorators to all generated model classes. This is useful for integrating with serialization libraries like dataclasses_json, or adding custom behavior to your models.

Why use this?

When using dataclasses.dataclass output with --snake-case-field, Python field names are snake_case but the original JSON keys may be camelCase. Libraries like dataclasses_json can handle this conversion automatically via decorators.

Example: Using dataclasses_json

Convert a JSON Schema with camelCase properties to dataclasses with snake_case fields that serialize back to camelCase.

schema.json 

{
  "type": "object",
  "title": "User",
  "properties": {
    "firstName": { "type": "string" },
    "lastName": { "type": "string" },
    "emailAddress": { "type": "string" }
  },
  "required": ["firstName", "lastName"]
}

Without --class-decorators

datamodel-codegen --input schema.json \
  --output-model-type dataclasses.dataclass \
  --snake-case-field

Generated model.py 

from __future__ import annotations

from dataclasses import dataclass


@dataclass
class User:
    first_name: str
    last_name: str
    email_address: str | None = None

The field names are snake_case, but there's no way to map them back to the original camelCase JSON keys.

With --class-decorators

datamodel-codegen --input schema.json \
  --output-model-type dataclasses.dataclass \
  --snake-case-field \
  --class-decorators "@dataclass_json(letter_case=LetterCase.CAMEL)" \
  --additional-imports "dataclasses_json.dataclass_json,dataclasses_json.LetterCase"

Generated model.py 

from __future__ import annotations

from dataclasses import dataclass

from dataclasses_json import LetterCase, dataclass_json


@dataclass_json(letter_case=LetterCase.CAMEL)
@dataclass
class User:
    first_name: str
    last_name: str
    email_address: str | None = None

Now serialization automatically converts between snake_case and camelCase:

user = User(first_name="John", last_name="Doe")
print(user.to_json())
# {"firstName": "John", "lastName": "Doe", "emailAddress": null}

Usage Notes

  • Multiple decorators: Use comma separation for multiple decorators: 

    --class-decorators "@decorator1,@decorator2"

  • @ prefix is optional: Both @dataclass_json and dataclass_json work - the @ is added automatically if missing.

  • Combine with --additional-imports: Always add the required imports for your decorators using --additional-imports.

Other Use Cases

The --class-decorators option works with any output model type:

  • Pydantic models: Add custom validators or behavior
  • TypedDict: Add runtime type-checking decorators
  • msgspec.Struct: Add custom serialization hooks

See Also

  • #2358 - Feature request for dataclasses_json support