Functional Serializers
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Functional Serializers
Section titled “Functional Serializers”This module contains related classes and functions for serialization.
PlainSerializer
Section titled “PlainSerializer”Plain serializers use a function to modify the output of serialization.
This is particularly helpful when you want to customize the serialization for annotated types. Consider an input of list, which will be serialized into a space-delimited string.
from typing import Annotated
from pydantic import BaseModel, PlainSerializer
CustomStr = Annotated[
list, PlainSerializer(lambda x: ' '.join(x), return_type=str)
]
class StudentModel(BaseModel):
courses: CustomStr
student = StudentModel(courses=['Math', 'Chemistry', 'English'])
print(student.model_dump())
#> {'courses': 'Math Chemistry English'}Attributes
Section titled “Attributes”The serializer function.
Type: core_schema.SerializerFunction
return_type
Section titled “return_type”The return type for the function. If omitted it will be inferred from the type annotation.
Type: Any
when_used
Section titled “when_used”Determines when this serializer should be used. Accepts a string with values 'always', 'unless-none', 'json', and 'json-unless-none'. Defaults to 'always'.
Type: WhenUsed
WrapSerializer
Section titled “WrapSerializer”Wrap serializers receive the raw inputs along with a handler function that applies the standard serialization logic, and can modify the resulting value before returning it as the final output of serialization.
For example, here's a scenario in which a wrap serializer transforms timezones to UTC and utilizes the existing datetime serialization logic.
from datetime import datetime, timezone
from typing import Annotated, Any
from pydantic import BaseModel, WrapSerializer
class EventDatetime(BaseModel):
start: datetime
end: datetime
def convert_to_utc(value: Any, handler, info) -> dict[str, datetime]:
# Note that `handler` can actually help serialize the `value` for
# further custom serialization in case it's a subclass.
partial_result = handler(value, info)
if info.mode == 'json':
return {
k: datetime.fromisoformat(v).astimezone(timezone.utc)
for k, v in partial_result.items()
}
return {k: v.astimezone(timezone.utc) for k, v in partial_result.items()}
UTCEventDatetime = Annotated[EventDatetime, WrapSerializer(convert_to_utc)]
class EventModel(BaseModel):
event_datetime: UTCEventDatetime
dt = EventDatetime(
start='2024-01-01T07:00:00-08:00', end='2024-01-03T20:00:00+06:00'
)
event = EventModel(event_datetime=dt)
print(event.model_dump())
'''
{
'event_datetime': {
'start': datetime.datetime(
2024, 1, 1, 15, 0, tzinfo=datetime.timezone.utc
),
'end': datetime.datetime(
2024, 1, 3, 14, 0, tzinfo=datetime.timezone.utc
),
}
}
'''
print(event.model_dump_json())
'''
{"event_datetime":{"start":"2024-01-01T15:00:00Z","end":"2024-01-03T14:00:00Z"}}
'''Attributes
Section titled “Attributes”The serializer function to be wrapped.
Type: core_schema.WrapSerializerFunction
return_type
Section titled “return_type”The return type for the function. If omitted it will be inferred from the type annotation.
Type: Any
when_used
Section titled “when_used”Determines when this serializer should be used. Accepts a string with values 'always', 'unless-none', 'json', and 'json-unless-none'. Defaults to 'always'.
Type: WhenUsed
SerializeAsAny
Section titled “SerializeAsAny”Annotation used to mark a type as having duck-typing serialization behavior.
See usage documentation for more details.
field_serializer
Section titled “field_serializer”def field_serializer(
field: str,
/,
*fields: str,
mode: Literal['wrap'],
return_type: Any = ...,
when_used: WhenUsed = ...,
check_fields: bool | None = ...,
) -> Callable[[_FieldWrapSerializerT], _FieldWrapSerializerT]
def field_serializer(
field: str,
/,
*fields: str,
mode: Literal['plain'] = ...,
return_type: Any = ...,
when_used: WhenUsed = ...,
check_fields: bool | None = ...,
) -> Callable[[_FieldPlainSerializerT], _FieldPlainSerializerT]Decorator that enables custom field serialization.
In the below example, a field of type set is used to mitigate duplication. A field_serializer is used to serialize the data as a sorted list.
from pydantic import BaseModel, field_serializer
class StudentModel(BaseModel):
name: str = 'Jane'
courses: set[str]
@field_serializer('courses', when_used='json')
def serialize_courses_in_order(self, courses: set[str]):
return sorted(courses)
student = StudentModel(courses={'Math', 'Chemistry', 'English'})
print(student.model_dump_json())
#> {"name":"Jane","courses":["Chemistry","English","Math"]}See the usage documentation for more information.
Four signatures are supported for the decorated serializer:
(self, value: Any, info: FieldSerializationInfo)(self, value: Any, nxt: SerializerFunctionWrapHandler, info: FieldSerializationInfo)(value: Any, info: SerializationInfo)(value: Any, nxt: SerializerFunctionWrapHandler, info: SerializationInfo)
Returns
Section titled “Returns”Callable[[_FieldWrapSerializerT], _FieldWrapSerializerT] | Callable[[_FieldPlainSerializerT], _FieldPlainSerializerT]
Parameters
Section titled “Parameters”*fields : str Default: ()
The field names the serializer should apply to.
mode : Literal['plain', 'wrap'] Default: 'plain'
The serialization mode.
plainmeans the function will be called instead of the default serialization logic,wrapmeans the function will be called with an argument to optionally call the default serialization logic.
return_type : Any Default: PydanticUndefined
Optional return type for the function, if omitted it will be inferred from the type annotation.
when_used : WhenUsed Default: 'always'
Determines the serializer will be used for serialization.
check_fields : bool | None Default: None
Whether to check that the fields actually exist on the model.
Raises
Section titled “Raises”PydanticUserError--- If the decorator is used without any arguments (at least one field name must be provided).
- If the provided field names are not strings.
model_serializer
Section titled “model_serializer”def model_serializer(f: _ModelPlainSerializerT, /) -> _ModelPlainSerializerT
def model_serializer(
*,
mode: Literal['wrap'],
when_used: WhenUsed = 'always',
return_type: Any = ...,
) -> Callable[[_ModelWrapSerializerT], _ModelWrapSerializerT]
def model_serializer(
*,
mode: Literal['plain'] = ...,
when_used: WhenUsed = 'always',
return_type: Any = ...,
) -> Callable[[_ModelPlainSerializerT], _ModelPlainSerializerT]Decorator that enables custom model serialization.
This is useful when a model need to be serialized in a customized manner, allowing for flexibility beyond just specific fields.
An example would be to serialize temperature to the same temperature scale, such as degrees Celsius.
from typing import Literal
from pydantic import BaseModel, model_serializer
class TemperatureModel(BaseModel):
unit: Literal['C', 'F']
value: int
@model_serializer()
def serialize_model(self):
if self.unit == 'F':
return {'unit': 'C', 'value': int((self.value - 32) / 1.8)}
return {'unit': self.unit, 'value': self.value}
temperature = TemperatureModel(unit='F', value=212)
print(temperature.model_dump())
#> {'unit': 'C', 'value': 100}Two signatures are supported for mode='plain', which is the default:
(self)(self, info: SerializationInfo)
And two other signatures for mode='wrap':
-
(self, nxt: SerializerFunctionWrapHandler) -
(self, nxt: SerializerFunctionWrapHandler, info: SerializationInfo)See the usage documentation for more information.
Returns
Section titled “Returns”_ModelPlainSerializerT | Callable[[_ModelWrapSerializerT], _ModelWrapSerializerT] | Callable[[_ModelPlainSerializerT], _ModelPlainSerializerT] -- The decorator function.
Parameters
Section titled “Parameters”f : _ModelPlainSerializerT | _ModelWrapSerializerT | None Default: None
The function to be decorated.
mode : Literal['plain', 'wrap'] Default: 'plain'
The serialization mode.
'plain'means the function will be called instead of the default serialization logic'wrap'means the function will be called with an argument to optionally call the default serialization logic.
when_used : WhenUsed Default: 'always'
Determines when this serializer should be used.
return_type : Any Default: PydanticUndefined
The return type for the function. If omitted it will be inferred from the type annotation.
FieldPlainSerializer
Section titled “FieldPlainSerializer”A field serializer method or function in plain mode.
Type: TypeAlias Default: 'core_schema.SerializerFunction | _Partial'
FieldWrapSerializer
Section titled “FieldWrapSerializer”A field serializer method or function in wrap mode.
Type: TypeAlias Default: 'core_schema.WrapSerializerFunction | _Partial'
FieldSerializer
Section titled “FieldSerializer”A field serializer method or function.
Type: TypeAlias Default: 'FieldPlainSerializer | FieldWrapSerializer'
ModelPlainSerializerWithInfo
Section titled “ModelPlainSerializerWithInfo”A model serializer method with the info argument, in plain mode.
Type: TypeAlias Default: Callable[[Any, SerializationInfo[Any]], Any]
ModelPlainSerializerWithoutInfo
Section titled “ModelPlainSerializerWithoutInfo”A model serializer method without the info argument, in plain mode.
Type: TypeAlias Default: Callable[[Any], Any]
ModelPlainSerializer
Section titled “ModelPlainSerializer”A model serializer method in plain mode.
Type: TypeAlias Default: 'ModelPlainSerializerWithInfo | ModelPlainSerializerWithoutInfo'
ModelWrapSerializerWithInfo
Section titled “ModelWrapSerializerWithInfo”A model serializer method with the info argument, in wrap mode.
Type: TypeAlias Default: Callable[[Any, SerializerFunctionWrapHandler, SerializationInfo[Any]], Any]
ModelWrapSerializerWithoutInfo
Section titled “ModelWrapSerializerWithoutInfo”A model serializer method without the info argument, in wrap mode.
Type: TypeAlias Default: Callable[[Any, SerializerFunctionWrapHandler], Any]
ModelWrapSerializer
Section titled “ModelWrapSerializer”A model serializer method in wrap mode.
Type: TypeAlias Default: 'ModelWrapSerializerWithInfo | ModelWrapSerializerWithoutInfo'