o f9@sDUdZddlmZddlZddlmZddlmZmZm Z m Z m Z m Z ddl mZmZddl mZddlmZmZmZd d lmZd d lmZmZd d lmZejd@iejd diGdddZejd@iejd diGdddZere e eeefe!eefeefZ"de#d<e ej$e"fZ%e ej&e"fZ'e de%dZ(e de'dZ)e dddddAd%d&Z*e dddddBd)d&Z*e dddddCd,d&Z*d-ed.dd/dDd2d&Z*e d3e defdZ+e dEd5d6Z,e dd.dd7dFd9d6Z, dGd-d.ed7dHdd?d?Z.dS)IzEThis module contains related classes and functions for serialization.) annotationsN) partialmethod) TYPE_CHECKINGAnyCallableTypeVarUnionoverload)PydanticUndefined core_schema)r ) AnnotatedLiteral TypeAlias)PydanticUndefinedAnnotation) _decorators_internal_dataclass)GetCoreSchemaHandlerfrozenTc@<eZdZUdZded<eZded<dZded<dddZdS)PlainSerializeraCPlain 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. ```python 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'} ``` Attributes: func: The serializer function. return_type: The return type for the function. If omitted it will be inferred from the type annotation. 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'. zcore_schema.SerializerFunctionfuncr return_typealways 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"}} ''' ``` Attributes: func: The serializer function to be wrapped. return_type: The return type for the function. If omitted it will be inferred from the type annotation. 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'. z"core_schema.WrapSerializerFunctionrrrrrrrrrrrc Cr )zThis method is used to get the Pydantic core schema of the class. Args: source_type: Source type. handler: Core schema handler. Returns: The generated core schema of the class. Nwrapr"r&)rr'rrr(r)rr*r r+r #wrap_serializer_function_ser_schemar-rr.r2r2r3r4r5z+WrapSerializer.__get_pydantic_core_schema__Nr6r7r2r2r2r3r=Rs ?  r=r_PartialClsOrStaticMethod_PlainSerializeMethodType)bound_WrapSerializeMethodType.)rr check_fieldsfieldstrfieldsrrrrrD bool | Noner@Callable[[_PlainSerializeMethodType], _PlainSerializeMethodType]cGdSNr2)rErrrDrGr2r2r3field_serializersrLmodeLiteral['plain']cGrJrKr2rErMrrrDrGr2r2r3rL Literal['wrap']>Callable[[_WrapSerializeMethodType], _WrapSerializeMethodType]cGrJrKr2rOr2r2r3rLrPr!r)rMrrrDLiteral['plain', 'wrap']Callable[[Any], Any]csdfdd }|S) aDecorator 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. ```python 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](../concepts/serialization.md#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)` Args: fields: Which field(s) the method should be called on. mode: 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. return_type: Optional return type for the function, if omitted it will be inferred from the type annotation. when_used: Determines the serializer will be used for serialization. check_fields: Whether to check that the fields actually exist on the model. Returns: The decorator function. fHCallable[..., Any] | staticmethod[Any, Any] | classmethod[Any, Any, Any]r(_decorators.PydanticDescriptorProxy[Any]cs tjd}t||S)N)rGrMrrrD)rFieldSerializerDecoratorInfoPydanticDescriptorProxyrUdec_inforDrGrMrrr2r3decs zfield_serializer..decN)rUrVrrWr2)rMrrrDrGr]r2r\r3rLs5 FuncType__fcCrJrKr2)r_r2r2r3model_serializer$sr`rMrrCallable[[FuncType], FuncType]cCrJrKr2rar2r2r3r`(srUCallable[..., Any] | Nonecs&dfdd }|dur|S||S) aDecorator 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. ```python 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](../concepts/serialization.md#custom-serializers) for more information. Args: f: The function to be decorated. mode: 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: Determines when this serializer should be used. return_type: The return type for the function. If omitted it will be inferred from the type annotation. Returns: The decorator function. rUCallable[..., Any]rrWcstjd}t||S)NrMrr)rModelSerializerDecoratorInforYrZrer2r3r]cs zmodel_serializer..decN)rUrdrrWr2)rUrMrrr]r2rer3r`1s2AnyTypec@s&eZdZd ddZdd d ZejZd S)SerializeAsAnyitemrrcCst|tfSrK)r rh)clsrir2r2r3__class_getitem__{sz SerializeAsAny.__class_getitem__rrrrcCsR||}|}|ddkr|}|d}|ddks tjddtd|d<|S)Ntype definitionsr0cSs||SrKr2)xhr2r2r3sz=SerializeAsAny.__get_pydantic_core_schema__..)r0r&)copyr r? any_schema)r/rrr0schema_to_updater2r2r3r4~s    z+SerializeAsAny.__get_pydantic_core_schema__N)rirrrr6)r8r9r:rkr4object__hash__r2r2r2r3rhys   rhr2) rErFrGrFrrrrrDrHrrI)rErFrGrFrMrNrrrrrDrHrrI)rErFrGrFrMrQrrrrrDrHrrR) rGrFrMrSrrrrrDrHrrT)r_r^rr^)rMrSrrrrrrbrK) rUrcrMrSrrrrrrT)/r; __future__r dataclasses functoolsrtypingrrrrrr pydantic_corer r _core_schematyping_extensionsr r rr _internalrrannotated_handlersr dataclass slots_truerr= classmethod staticmethodr@r<SerializerFunction_PlainSerializationFunctionWrapSerializerFunction_WrapSerializationFunctionrArCrLr^r`rgrhr2r2r2r3sz      ?_,     D  <