o niF@sUdZddlmZddlZddlmZmZddlmZm Z m Z m Z m Z m Z mZddlmZmZddlmZmZmZddlmZd d lmZd d lmZmZd d lmZd d lm Z ej!dUiej"ddiGdddZ#ej!dUiej"ddiGdddZ$erdZ%de&d<dZ'de&d< dZ(de&d< dZ)de&d< e de'dZ*e de(dZ+ed d d d!dVd/d0Z,ed d d d d1dWd4d0Z,d5ed6dd1dXd9d0Z,er)e e ee ge fZ-de&d:< e e ge fZ.de&d;< d< e e ege fZ1de&d?< d@Z2de&dA< dBZ3de&dC<e dDe/dZ4e dEe2dZ5edYdGdHZ6ed6d dIdZdKdHZ6ed d6d dLd[dNdHZ6 d\d5d6edLd]dQdHZ6e dRZ7erbe e7d fZ8dSej!dUiej"GdSdTdTZ8dS)^zEThis module contains related classes and functions for serialization.) annotationsN)partial partialmethod) TYPE_CHECKING AnnotatedAnyCallableLiteralTypeVaroverload)PydanticUndefined core_schema)SerializationInfoSerializerFunctionWrapHandlerWhenUsed) TypeAlias)PydanticUndefinedAnnotation) _decorators_internal_dataclass)GetCoreSchemaHandler)PydanticUserErrorfrozenTc@<eZdZUdZded<eZded<dZded<dddZdS)PlainSerializeraPlain 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 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_typealwaysr when_used source_typehandlerrreturncore_schema.CoreSchemac C||}|jtur |j}n z tj|j|jd}Wnty,}zt ||d}~ww|tur3dn| |}t j |jt |jd||jd|d<|S)zGets the Pydantic core schema. Args: source_type: The source type. handler: The `GetCoreSchemaHandler` instance. Returns: The Pydantic core schema. localnsNplainfunctioninfo_arg return_schemar serialization)rr rget_callable_return_typer_get_types_namespacelocals NameErrorrfrom_name_errorgenerate_schemar $plain_serializer_function_ser_schemainspect_annotated_serializerrselfrr schemarer*r8_/var/www/html/arapca_proje/venv/lib/python3.10/site-packages/pydantic/functional_serializers.py__get_pydantic_core_schema__6(     z,PlainSerializer.__get_pydantic_core_schema__Nrrr rr!r" __name__ __module__ __qualname____doc____annotations__r rrr:r8r8r8r9rs   rc@r)WrapSerializeraWrap 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. ```python 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: 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.WrapSerializerFunctionrrrrrrrr rr!r"c 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. r$Nwrapr'r+)rr rr,rr-r.r/rr0r1r #wrap_serializer_function_ser_schemar3rr4r8r8r9r:r;z+WrapSerializer.__get_pydantic_core_schema__Nr<r=r8r8r8r9rCYs >  rCz!partial[Any] | partialmethod[Any]r_Partialz)core_schema.SerializerFunction | _PartialFieldPlainSerializerz-core_schema.WrapSerializerFunction | _PartialFieldWrapSerializerz*FieldPlainSerializer | FieldWrapSerializerFieldSerializer_FieldPlainSerializerT)bound_FieldWrapSerializerT.)rr check_fieldsfieldstrfieldsmodeLiteral['wrap']rrrrrM bool | Noner!8Callable[[_FieldWrapSerializerT], _FieldWrapSerializerT]cGdSNr8rNrQrrrMrPr8r8r9field_serializer rX)rQrrrMLiteral['plain']:Callable[[_FieldPlainSerializerT], _FieldPlainSerializerT]cGrUrVr8rWr8r8r9rXrYr&rLiteral['plain', 'wrap']uCallable[[_FieldWrapSerializerT], _FieldWrapSerializerT] | Callable[[_FieldPlainSerializerT], _FieldPlainSerializerT]csbt|s t|trtddd|gRtddDs$tddddfd d }|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 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](../concepts/serialization.md#serializers) 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)` Args: *fields: The field names the serializer should apply to. 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. 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. zThe `@field_serializer` decorator cannot be used without arguments, at least one field must be provided. For example: `@field_serializer('', ...)`.zdecorator-missing-arguments)codecss|]}t|tVqdSrV) isinstancerO).0rNr8r8r9 *sz#field_serializer..zThe provided field names to the `@field_serializer` decorator should be strings. For example: `@field_serializer('', '', ...).`zdecorator-invalid-fieldsfrIr!(_decorators.PydanticDescriptorProxy[Any]cs tjd}t||S)N)rPrQrrrM)rFieldSerializerDecoratorInfoPydanticDescriptorProxyrbdec_inforMrPrQrrr8r9dec1s zfield_serializer..decN)rbrIr!rc)callabler_ classmethodrall)rNrQrrrMrPrir8rhr9rXs:  ModelPlainSerializerWithInfoModelPlainSerializerWithoutInfoz>ModelPlainSerializerWithInfo | ModelPlainSerializerWithoutInfoModelPlainSerializerModelWrapSerializerWithInfoModelWrapSerializerWithoutInfoz {'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](../concepts/serialization.md#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. rbrsr!rccstjd}t||S)NrQrr)rModelSerializerDecoratorInforerfr|r8r9ris zmodel_serializer..decN)rbrsr!rcr8)rbrQrrrir8r|r9rvls@AnyTypec@s*eZdZdZdddZdd d ZejZd S)SerializeAsAnyzAnnotation used to mark a type as having duck-typing serialization behavior. See [usage documentation](../concepts/serialization.md#serializing-with-duck-typing) for more details. itemrr!cCst|tfSrV)rr)clsrr8r8r9__class_getitem__sz SerializeAsAny.__class_getitem__rr rr"cCsF||}|}|ddkr|}|d}|ddks td|d<|S)Ntype definitionsr6anyr+)copyr simple_ser_schema)r5rr r6schema_to_updater8r8r9r:s  z+SerializeAsAny.__get_pydantic_core_schema__N)rrr!rr<)r>r?r@rArr:object__hash__r8r8r8r9rs    rr8)rNrOrPrOrQrRrrrrrMrSr!rT)rNrOrPrOrQrZrrrrrMrSr!r[)rNrOrPrOrQr\rrrrrMrSr!r])rbrtr!rt)rQrRrrrrr!rw)rQrZrrrrr!ryrV) rbrzrQr\rrrrr!r{)9rA __future__r dataclasses functoolsrrtypingrrrrr r r pydantic_corer r pydantic_core.core_schemarrrtyping_extensionsrr _internalrrannotated_handlersrerrorsr dataclass slots_truerrCrFrBrGrHrIrJrLrXrmrnrorprqrrrsrtrurvr~rr8r8r8r9s $    Ef       V       J