loki.tools.dataclass

dataclass_strict(_cls: type[_T] | None = None, *, init: Literal[False] = False, repr: bool = True, eq: bool = True, order: bool = False, unsafe_hash: bool = False, frozen: bool | None = None, config: ConfigDict | type[object] | None = {'arbitrary_types_allowed': True}, validate_on_init: bool | None = None, kw_only: bool = False, slots: bool = False) → Callable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]

Usage docs: https://docs.pydantic.dev/2.9/concepts/dataclasses/

A decorator used to create a Pydantic-enhanced dataclass, similar to the standard Python dataclass, but with added validation.

This function should be used similarly to dataclasses.dataclass.

Parameters:

  • _cls – The target dataclass.

  • init – Included for signature compatibility with dataclasses.dataclass, and is passed through to dataclasses.dataclass when appropriate. If specified, must be set to False, as pydantic inserts its own __init__ function.

  • repr – A boolean indicating whether to include the field in the __repr__ output.

  • eq – Determines if a __eq__ method should be generated for the class.

  • order – Determines if comparison magic methods should be generated, such as __lt__, but not __eq__.

  • unsafe_hash – Determines if a __hash__ method should be included in the class, as in dataclasses.dataclass.

  • frozen – Determines if the generated class should be a ‘frozen’ dataclass, which does not allow its attributes to be modified after it has been initialized. If not set, the value from the provided config argument will be used (and will default to False otherwise).

  • config – The Pydantic config to use for the dataclass.

  • validate_on_init – A deprecated parameter included for backwards compatibility; in V2, all Pydantic dataclasses are validated on init.

  • kw_only – Determines if __init__ method parameters must be specified by keyword only. Defaults to False.

  • slots – Determines if the generated class should be a ‘slots’ dataclass, which does not allow the addition of new attributes after instantiation.

Returns:

A decorator that accepts a class as its argument and returns a Pydantic dataclass.

Raises:

AssertionError – Raised if init is not False or validate_on_init is False.