o 6Wj3@sUdZddlmZddlZddlZddlZddlZddlm Z ddl m Z ddl m Z ddlmZmZmZmZmZddlmZmZmZmZdd lmZmZd d lmZd d lmZd d l m!Z!m"Z"d dlm#Z#ddl$m%Z%m&Z&ddl'm(Z(ddl)m*Z*m+Z+ddl,m-Z-ddl.m/Z/ddl0m1Z1ddl2m3Z3ddl4m5Z5erddl6m7Z8d dl9m:Z:Gddde8eZ; dd-d.Z=d?d0d1Z>d@d5d6Z?e@eAejBefZCd7eDd8<e dAd:d;ZEdS)Bz0Private logic for creating pydantic dataclasses.) annotationsN) Generator)contextmanager)partial) TYPE_CHECKINGAnyClassVarProtocolcast) ArgsKwargsSchemaSerializerSchemaValidator core_schema) TypeAliasTypeIs)PydanticUndefinedAnnotation) FieldInfo)PluggableSchemaValidatorcreate_schema_validator)PydanticDeprecatedSince20)_config _decorators)collect_dataclass_fields)GenerateSchemaInvalidSchemaError)get_standard_typevars_map)set_dataclass_mocks) NsResolver)generate_pydantic_signature)LazyClassAttribute)DataclassInstance) ConfigDictc@sXeZdZUdZded<ded<ded<ded <d ed <d ed <ded<edddZdS)PydanticDataclassaiA protocol containing attributes only available once a class has been decorated as a Pydantic dataclass. 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To create this Pydantic dataclass, we first apply the stdlib `@dataclass` decorator on it. During the construction of the stdlib dataclass, the `kw_only` and `repr` field arguments need to be understood by the stdlib *during* the dataclass construction. To do so, we temporarily patch the fields dictionary of the affected bases. For instance, with the following example: ```python {test="skip" lint="skip"} import dataclasses as stdlib_dc import pydantic import pydantic.dataclasses as pydantic_dc @stdlib_dc.dataclass class A: a: int = pydantic.Field(repr=False) # Notice that the `repr` attribute of the dataclass field is `True`: A.__dataclass_fields__['a'] #> dataclass.Field(default=FieldInfo(repr=False), repr=True, ...) @pydantic_dc.dataclass class B(A): b: int = pydantic.Field(repr=False) ``` When passing `B` to the stdlib `@dataclass` decorator, it will look for fields in the parent classes and reuse them directly. When this context manager is active, `A` will be temporarily patched to be equivalent to: ```python {test="skip" lint="skip"} @stdlib_dc.dataclass class A: a: int = stdlib_dc.field(default=Field(repr=False), repr=False) ``` !!! note This is only applied to the bases of `cls`, and not `cls` itself. The reason is that the Pydantic dataclass decorator "owns" `cls` (in the previous example, `B`). As such, we instead modify the fields directly (in the previous example, we simply do `setattr(B, 'b', as_dataclass_field(pydantic_field))`). !!! note This approach is far from ideal, and can probably be the source of unwanted side effects/race conditions. 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