dataclass_args_schema

Returns a schema for validating dataclass arguments, e.g.:

from pydantic_core import SchemaValidator, core_schema

field_a = core_schema.dataclass_field(
    name='a', schema=core_schema.str_schema(), kw_only=False
)
field_b = core_schema.dataclass_field(
    name='b', schema=core_schema.bool_schema(), kw_only=False
)
schema = core_schema.dataclass_args_schema('Foobar', [field_a, field_b])
v = SchemaValidator(schema)
assert v.validate_python({'a': 'hello', 'b': True}) == ({'a': 'hello', 'b': True}, None)

def dataclass_args_schema(
    dataclass_name: str,
    fields: list[DataclassField],
    computed_fields: list[ComputedField] | None = None,
    collect_init_only: bool | None = None,
    ref: str | None = None,
    metadata: dict[str, Any] | None = None,
    serialization: SerSchema | None = None,
    extra_behavior: ExtraBehavior | None = None
) - > DataclassArgsSchema

Returns a schema for validating dataclass arguments, e.g.:

from pydantic_core import SchemaValidator, core_schema

field_a = core_schema.dataclass_field(
    name='a', schema=core_schema.str_schema(), kw_only=False
)
field_b = core_schema.dataclass_field(
    name='b', schema=core_schema.bool_schema(), kw_only=False
)
schema = core_schema.dataclass_args_schema('Foobar', [field_a, field_b])
v = SchemaValidator(schema)
assert v.validate_python({'a': 'hello', 'b': True}) == ({'a': 'hello', 'b': True}, None)

Parameters

Name	Type	Description
dataclass_name	`str`	The name of the dataclass being validated
fields	`list[DataclassField]`	The fields to use for the dataclass
computed_fields	`list[ComputedField]	None` = None
collect_init_only	`bool	None` = None
ref	`str	None` = None
metadata	`dict[str, Any]	None` = None
serialization	`SerSchema	None` = None
extra_behavior	`ExtraBehavior	None` = None

Returns

Type	Description
`DataclassArgsSchema`	A core schema dictionary defining how to validate and parse arguments for a specific dataclass structure

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