Functional Serializers
This module contains related classes and functions for serialization.
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 List
from typing_extensions 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'}
The serializer function.
Type: core_schema.SerializerFunction
The return type for the function. If omitted it will be inferred from the type annotation.
Type: Any
Determines when this serializer should be used. Accepts a string with values 'always',
'unless-none', 'json', and 'json-unless-none'. Defaults to ‘always’.
Type: Literal[‘always’, ‘unless-none’, ‘json’, ‘json-unless-none’]
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 Any, Dict
from typing_extensions import Annotated
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 `helper` 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"}}
'''
The serializer function to be wrapped.
Type: core_schema.WrapSerializerFunction
The return type for the function. If omitted it will be inferred from the type annotation.
Type: Any
Determines when this serializer should be used. Accepts a string with values 'always',
'unless-none', 'json', and 'json-unless-none'. Defaults to ‘always’.
Type: Literal[‘always’, ‘unless-none’, ‘json’, ‘json-unless-none’]
def field_serializer(
field: str,
fields: str = (),
return_type: Any = ...,
when_used: Literal['always', 'unless-none', 'json', 'json-unless-none'] = ...,
check_fields: bool | None = ...,
) -> Callable[[_PlainSerializeMethodType], _PlainSerializeMethodType]
def field_serializer(
field: str,
fields: str = (),
mode: Literal['plain'],
return_type: Any = ...,
when_used: Literal['always', 'unless-none', 'json', 'json-unless-none'] = ...,
check_fields: bool | None = ...,
) -> Callable[[_PlainSerializeMethodType], _PlainSerializeMethodType]
def field_serializer(
field: str,
fields: str = (),
mode: Literal['wrap'],
return_type: Any = ...,
when_used: Literal['always', 'unless-none', 'json', 'json-unless-none'] = ...,
check_fields: bool | None = ...,
) -> Callable[[_WrapSerializeMethodType], _WrapSerializeMethodType]
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 typing import Set
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(courses: Set[str]):
return sorted(courses)
student = StudentModel(courses={'Math', 'Chemistry', 'English'})
print(student.model_dump_json())
#> {"name":"Jane","courses":["Chemistry","English","Math"]}
See Custom serializers for more information.
Four signatures are supported:
(self, value: Any, info: FieldSerializationInfo)(self, value: Any, nxt: SerializerFunctionWrapHandler, info: FieldSerializationInfo)(value: Any, info: SerializationInfo)(value: Any, nxt: SerializerFunctionWrapHandler, info: SerializationInfo)
Callable[[Any], Any] — The decorator function.
Which field(s) the method should be called on.
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.
Optional return type for the function, if omitted it will be inferred from the type annotation.
Determines the serializer will be used for serialization.
Whether to check that the fields actually exist on the model.
def model_serializer(__f: FuncType) -> FuncType
def model_serializer(
mode: Literal['plain', 'wrap'] = ...,
when_used: Literal['always', 'unless-none', 'json', 'json-unless-none'] = 'always',
return_type: Any = ...,
) -> Callable[[FuncType], FuncType]
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}
See Custom serializers for more information.
Callable[[Any], Any] — The decorator function.
The function to be decorated.
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.
Determines when this serializer should be used.
The return type for the function. If omitted it will be inferred from the type annotation.