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infer_4_37_2/lib/python3.10/site-packages/pydantic/__init__.py

@@ -0,0 +1,428 @@
+import typing
+from importlib import import_module
+from warnings import warn
+
+from ._migration import getattr_migration
+from .version import VERSION
+
+if typing.TYPE_CHECKING:
+    # import of virtually everything is supported via `__getattr__` below,
+    # but we need them here for type checking and IDE support
+    import pydantic_core
+    from pydantic_core.core_schema import (
+        FieldSerializationInfo,
+        SerializationInfo,
+        SerializerFunctionWrapHandler,
+        ValidationInfo,
+        ValidatorFunctionWrapHandler,
+    )
+
+    from . import dataclasses
+    from .aliases import AliasChoices, AliasGenerator, AliasPath
+    from .annotated_handlers import GetCoreSchemaHandler, GetJsonSchemaHandler
+    from .config import ConfigDict, with_config
+    from .errors import *
+    from .fields import Field, PrivateAttr, computed_field
+    from .functional_serializers import (
+        PlainSerializer,
+        SerializeAsAny,
+        WrapSerializer,
+        field_serializer,
+        model_serializer,
+    )
+    from .functional_validators import (
+        AfterValidator,
+        BeforeValidator,
+        InstanceOf,
+        PlainValidator,
+        SkipValidation,
+        WrapValidator,
+        field_validator,
+        model_validator,
+    )
+    from .json_schema import WithJsonSchema
+    from .main import *
+    from .networks import *
+    from .type_adapter import TypeAdapter
+    from .types import *
+    from .validate_call_decorator import validate_call
+    from .warnings import (
+        PydanticDeprecatedSince20,
+        PydanticDeprecatedSince26,
+        PydanticDeprecatedSince29,
+        PydanticDeprecationWarning,
+        PydanticExperimentalWarning,
+    )
+
+    # this encourages pycharm to import `ValidationError` from here, not pydantic_core
+    ValidationError = pydantic_core.ValidationError
+    from .deprecated.class_validators import root_validator, validator
+    from .deprecated.config import BaseConfig, Extra
+    from .deprecated.tools import *
+    from .root_model import RootModel
+
+__version__ = VERSION
+__all__ = (
+    # dataclasses
+    'dataclasses',
+    # functional validators
+    'field_validator',
+    'model_validator',
+    'AfterValidator',
+    'BeforeValidator',
+    'PlainValidator',
+    'WrapValidator',
+    'SkipValidation',
+    'InstanceOf',
+    # JSON Schema
+    'WithJsonSchema',
+    # deprecated V1 functional validators, these are imported via `__getattr__` below
+    'root_validator',
+    'validator',
+    # functional serializers
+    'field_serializer',
+    'model_serializer',
+    'PlainSerializer',
+    'SerializeAsAny',
+    'WrapSerializer',
+    # config
+    'ConfigDict',
+    'with_config',
+    # deprecated V1 config, these are imported via `__getattr__` below
+    'BaseConfig',
+    'Extra',
+    # validate_call
+    'validate_call',
+    # errors
+    'PydanticErrorCodes',
+    'PydanticUserError',
+    'PydanticSchemaGenerationError',
+    'PydanticImportError',
+    'PydanticUndefinedAnnotation',
+    'PydanticInvalidForJsonSchema',
+    # fields
+    'Field',
+    'computed_field',
+    'PrivateAttr',
+    # alias
+    'AliasChoices',
+    'AliasGenerator',
+    'AliasPath',
+    # main
+    'BaseModel',
+    'create_model',
+    # network
+    'AnyUrl',
+    'AnyHttpUrl',
+    'FileUrl',
+    'HttpUrl',
+    'FtpUrl',
+    'WebsocketUrl',
+    'AnyWebsocketUrl',
+    'UrlConstraints',
+    'EmailStr',
+    'NameEmail',
+    'IPvAnyAddress',
+    'IPvAnyInterface',
+    'IPvAnyNetwork',
+    'PostgresDsn',
+    'CockroachDsn',
+    'AmqpDsn',
+    'RedisDsn',
+    'MongoDsn',
+    'KafkaDsn',
+    'NatsDsn',
+    'MySQLDsn',
+    'MariaDBDsn',
+    'ClickHouseDsn',
+    'SnowflakeDsn',
+    'validate_email',
+    # root_model
+    'RootModel',
+    # deprecated tools, these are imported via `__getattr__` below
+    'parse_obj_as',
+    'schema_of',
+    'schema_json_of',
+    # types
+    'Strict',
+    'StrictStr',
+    'conbytes',
+    'conlist',
+    'conset',
+    'confrozenset',
+    'constr',
+    'StringConstraints',
+    'ImportString',
+    'conint',
+    'PositiveInt',
+    'NegativeInt',
+    'NonNegativeInt',
+    'NonPositiveInt',
+    'confloat',
+    'PositiveFloat',
+    'NegativeFloat',
+    'NonNegativeFloat',
+    'NonPositiveFloat',
+    'FiniteFloat',
+    'condecimal',
+    'condate',
+    'UUID1',
+    'UUID3',
+    'UUID4',
+    'UUID5',
+    'FilePath',
+    'DirectoryPath',
+    'NewPath',
+    'Json',
+    'Secret',
+    'SecretStr',
+    'SecretBytes',
+    'SocketPath',
+    'StrictBool',
+    'StrictBytes',
+    'StrictInt',
+    'StrictFloat',
+    'PaymentCardNumber',
+    'ByteSize',
+    'PastDate',
+    'FutureDate',
+    'PastDatetime',
+    'FutureDatetime',
+    'AwareDatetime',
+    'NaiveDatetime',
+    'AllowInfNan',
+    'EncoderProtocol',
+    'EncodedBytes',
+    'EncodedStr',
+    'Base64Encoder',
+    'Base64Bytes',
+    'Base64Str',
+    'Base64UrlBytes',
+    'Base64UrlStr',
+    'GetPydanticSchema',
+    'Tag',
+    'Discriminator',
+    'JsonValue',
+    'FailFast',
+    # type_adapter
+    'TypeAdapter',
+    # version
+    '__version__',
+    'VERSION',
+    # warnings
+    'PydanticDeprecatedSince20',
+    'PydanticDeprecatedSince26',
+    'PydanticDeprecatedSince29',
+    'PydanticDeprecationWarning',
+    'PydanticExperimentalWarning',
+    # annotated handlers
+    'GetCoreSchemaHandler',
+    'GetJsonSchemaHandler',
+    # pydantic_core
+    'ValidationError',
+    'ValidationInfo',
+    'SerializationInfo',
+    'ValidatorFunctionWrapHandler',
+    'FieldSerializationInfo',
+    'SerializerFunctionWrapHandler',
+    'OnErrorOmit',
+)
+
+# A mapping of {<member name>: (package, <module name>)} defining dynamic imports
+_dynamic_imports: 'dict[str, tuple[str, str]]' = {
+    'dataclasses': (__spec__.parent, '__module__'),
+    # functional validators
+    'field_validator': (__spec__.parent, '.functional_validators'),
+    'model_validator': (__spec__.parent, '.functional_validators'),
+    'AfterValidator': (__spec__.parent, '.functional_validators'),
+    'BeforeValidator': (__spec__.parent, '.functional_validators'),
+    'PlainValidator': (__spec__.parent, '.functional_validators'),
+    'WrapValidator': (__spec__.parent, '.functional_validators'),
+    'SkipValidation': (__spec__.parent, '.functional_validators'),
+    'InstanceOf': (__spec__.parent, '.functional_validators'),
+    # JSON Schema
+    'WithJsonSchema': (__spec__.parent, '.json_schema'),
+    # functional serializers
+    'field_serializer': (__spec__.parent, '.functional_serializers'),
+    'model_serializer': (__spec__.parent, '.functional_serializers'),
+    'PlainSerializer': (__spec__.parent, '.functional_serializers'),
+    'SerializeAsAny': (__spec__.parent, '.functional_serializers'),
+    'WrapSerializer': (__spec__.parent, '.functional_serializers'),
+    # config
+    'ConfigDict': (__spec__.parent, '.config'),
+    'with_config': (__spec__.parent, '.config'),
+    # validate call
+    'validate_call': (__spec__.parent, '.validate_call_decorator'),
+    # errors
+    'PydanticErrorCodes': (__spec__.parent, '.errors'),
+    'PydanticUserError': (__spec__.parent, '.errors'),
+    'PydanticSchemaGenerationError': (__spec__.parent, '.errors'),
+    'PydanticImportError': (__spec__.parent, '.errors'),
+    'PydanticUndefinedAnnotation': (__spec__.parent, '.errors'),
+    'PydanticInvalidForJsonSchema': (__spec__.parent, '.errors'),
+    # fields
+    'Field': (__spec__.parent, '.fields'),
+    'computed_field': (__spec__.parent, '.fields'),
+    'PrivateAttr': (__spec__.parent, '.fields'),
+    # alias
+    'AliasChoices': (__spec__.parent, '.aliases'),
+    'AliasGenerator': (__spec__.parent, '.aliases'),
+    'AliasPath': (__spec__.parent, '.aliases'),
+    # main
+    'BaseModel': (__spec__.parent, '.main'),
+    'create_model': (__spec__.parent, '.main'),
+    # network
+    'AnyUrl': (__spec__.parent, '.networks'),
+    'AnyHttpUrl': (__spec__.parent, '.networks'),
+    'FileUrl': (__spec__.parent, '.networks'),
+    'HttpUrl': (__spec__.parent, '.networks'),
+    'FtpUrl': (__spec__.parent, '.networks'),
+    'WebsocketUrl': (__spec__.parent, '.networks'),
+    'AnyWebsocketUrl': (__spec__.parent, '.networks'),
+    'UrlConstraints': (__spec__.parent, '.networks'),
+    'EmailStr': (__spec__.parent, '.networks'),
+    'NameEmail': (__spec__.parent, '.networks'),
+    'IPvAnyAddress': (__spec__.parent, '.networks'),
+    'IPvAnyInterface': (__spec__.parent, '.networks'),
+    'IPvAnyNetwork': (__spec__.parent, '.networks'),
+    'PostgresDsn': (__spec__.parent, '.networks'),
+    'CockroachDsn': (__spec__.parent, '.networks'),
+    'AmqpDsn': (__spec__.parent, '.networks'),
+    'RedisDsn': (__spec__.parent, '.networks'),
+    'MongoDsn': (__spec__.parent, '.networks'),
+    'KafkaDsn': (__spec__.parent, '.networks'),
+    'NatsDsn': (__spec__.parent, '.networks'),
+    'MySQLDsn': (__spec__.parent, '.networks'),
+    'MariaDBDsn': (__spec__.parent, '.networks'),
+    'ClickHouseDsn': (__spec__.parent, '.networks'),
+    'SnowflakeDsn': (__spec__.parent, '.networks'),
+    'validate_email': (__spec__.parent, '.networks'),
+    # root_model
+    'RootModel': (__spec__.parent, '.root_model'),
+    # types
+    'Strict': (__spec__.parent, '.types'),
+    'StrictStr': (__spec__.parent, '.types'),
+    'conbytes': (__spec__.parent, '.types'),
+    'conlist': (__spec__.parent, '.types'),
+    'conset': (__spec__.parent, '.types'),
+    'confrozenset': (__spec__.parent, '.types'),
+    'constr': (__spec__.parent, '.types'),
+    'StringConstraints': (__spec__.parent, '.types'),
+    'ImportString': (__spec__.parent, '.types'),
+    'conint': (__spec__.parent, '.types'),
+    'PositiveInt': (__spec__.parent, '.types'),
+    'NegativeInt': (__spec__.parent, '.types'),
+    'NonNegativeInt': (__spec__.parent, '.types'),
+    'NonPositiveInt': (__spec__.parent, '.types'),
+    'confloat': (__spec__.parent, '.types'),
+    'PositiveFloat': (__spec__.parent, '.types'),
+    'NegativeFloat': (__spec__.parent, '.types'),
+    'NonNegativeFloat': (__spec__.parent, '.types'),
+    'NonPositiveFloat': (__spec__.parent, '.types'),
+    'FiniteFloat': (__spec__.parent, '.types'),
+    'condecimal': (__spec__.parent, '.types'),
+    'condate': (__spec__.parent, '.types'),
+    'UUID1': (__spec__.parent, '.types'),
+    'UUID3': (__spec__.parent, '.types'),
+    'UUID4': (__spec__.parent, '.types'),
+    'UUID5': (__spec__.parent, '.types'),
+    'FilePath': (__spec__.parent, '.types'),
+    'DirectoryPath': (__spec__.parent, '.types'),
+    'NewPath': (__spec__.parent, '.types'),
+    'Json': (__spec__.parent, '.types'),
+    'Secret': (__spec__.parent, '.types'),
+    'SecretStr': (__spec__.parent, '.types'),
+    'SecretBytes': (__spec__.parent, '.types'),
+    'StrictBool': (__spec__.parent, '.types'),
+    'StrictBytes': (__spec__.parent, '.types'),
+    'StrictInt': (__spec__.parent, '.types'),
+    'StrictFloat': (__spec__.parent, '.types'),
+    'PaymentCardNumber': (__spec__.parent, '.types'),
+    'ByteSize': (__spec__.parent, '.types'),
+    'PastDate': (__spec__.parent, '.types'),
+    'SocketPath': (__spec__.parent, '.types'),
+    'FutureDate': (__spec__.parent, '.types'),
+    'PastDatetime': (__spec__.parent, '.types'),
+    'FutureDatetime': (__spec__.parent, '.types'),
+    'AwareDatetime': (__spec__.parent, '.types'),
+    'NaiveDatetime': (__spec__.parent, '.types'),
+    'AllowInfNan': (__spec__.parent, '.types'),
+    'EncoderProtocol': (__spec__.parent, '.types'),
+    'EncodedBytes': (__spec__.parent, '.types'),
+    'EncodedStr': (__spec__.parent, '.types'),
+    'Base64Encoder': (__spec__.parent, '.types'),
+    'Base64Bytes': (__spec__.parent, '.types'),
+    'Base64Str': (__spec__.parent, '.types'),
+    'Base64UrlBytes': (__spec__.parent, '.types'),
+    'Base64UrlStr': (__spec__.parent, '.types'),
+    'GetPydanticSchema': (__spec__.parent, '.types'),
+    'Tag': (__spec__.parent, '.types'),
+    'Discriminator': (__spec__.parent, '.types'),
+    'JsonValue': (__spec__.parent, '.types'),
+    'OnErrorOmit': (__spec__.parent, '.types'),
+    'FailFast': (__spec__.parent, '.types'),
+    # type_adapter
+    'TypeAdapter': (__spec__.parent, '.type_adapter'),
+    # warnings
+    'PydanticDeprecatedSince20': (__spec__.parent, '.warnings'),
+    'PydanticDeprecatedSince26': (__spec__.parent, '.warnings'),
+    'PydanticDeprecatedSince29': (__spec__.parent, '.warnings'),
+    'PydanticDeprecationWarning': (__spec__.parent, '.warnings'),
+    'PydanticExperimentalWarning': (__spec__.parent, '.warnings'),
+    # annotated handlers
+    'GetCoreSchemaHandler': (__spec__.parent, '.annotated_handlers'),
+    'GetJsonSchemaHandler': (__spec__.parent, '.annotated_handlers'),
+    # pydantic_core stuff
+    'ValidationError': ('pydantic_core', '.'),
+    'ValidationInfo': ('pydantic_core', '.core_schema'),
+    'SerializationInfo': ('pydantic_core', '.core_schema'),
+    'ValidatorFunctionWrapHandler': ('pydantic_core', '.core_schema'),
+    'FieldSerializationInfo': ('pydantic_core', '.core_schema'),
+    'SerializerFunctionWrapHandler': ('pydantic_core', '.core_schema'),
+    # deprecated, mostly not included in __all__
+    'root_validator': (__spec__.parent, '.deprecated.class_validators'),
+    'validator': (__spec__.parent, '.deprecated.class_validators'),
+    'BaseConfig': (__spec__.parent, '.deprecated.config'),
+    'Extra': (__spec__.parent, '.deprecated.config'),
+    'parse_obj_as': (__spec__.parent, '.deprecated.tools'),
+    'schema_of': (__spec__.parent, '.deprecated.tools'),
+    'schema_json_of': (__spec__.parent, '.deprecated.tools'),
+    # deprecated dynamic imports
+    'FieldValidationInfo': ('pydantic_core', '.core_schema'),
+    'GenerateSchema': (__spec__.parent, '._internal._generate_schema'),
+}
+_deprecated_dynamic_imports = {'FieldValidationInfo', 'GenerateSchema'}
+
+_getattr_migration = getattr_migration(__name__)
+
+
+def __getattr__(attr_name: str) -> object:
+    if attr_name in _deprecated_dynamic_imports:
+        warn(
+            f'Importing {attr_name} from `pydantic` is deprecated. This feature is either no longer supported, or is not public.',
+            DeprecationWarning,
+            stacklevel=2,
+        )
+
+    dynamic_attr = _dynamic_imports.get(attr_name)
+    if dynamic_attr is None:
+        return _getattr_migration(attr_name)
+
+    package, module_name = dynamic_attr
+
+    if module_name == '__module__':
+        result = import_module(f'.{attr_name}', package=package)
+        globals()[attr_name] = result
+        return result
+    else:
+        module = import_module(module_name, package=package)
+        result = getattr(module, attr_name)
+        g = globals()
+        for k, (_, v_module_name) in _dynamic_imports.items():
+            if v_module_name == module_name and k not in _deprecated_dynamic_imports:
+                g[k] = getattr(module, k)
+        return result
+
+
+def __dir__() -> 'list[str]':
+    return list(__all__)

infer_4_37_2/lib/python3.10/site-packages/pydantic/annotated_handlers.py

@@ -0,0 +1,122 @@
+"""Type annotations to use with `__get_pydantic_core_schema__` and `__get_pydantic_json_schema__`."""
+
+from __future__ import annotations as _annotations
+
+from typing import TYPE_CHECKING, Any, Union
+
+from pydantic_core import core_schema
+
+if TYPE_CHECKING:
+    from ._internal._namespace_utils import NamespacesTuple
+    from .json_schema import JsonSchemaMode, JsonSchemaValue
+
+    CoreSchemaOrField = Union[
+        core_schema.CoreSchema,
+        core_schema.ModelField,
+        core_schema.DataclassField,
+        core_schema.TypedDictField,
+        core_schema.ComputedField,
+    ]
+
+__all__ = 'GetJsonSchemaHandler', 'GetCoreSchemaHandler'
+
+
+class GetJsonSchemaHandler:
+    """Handler to call into the next JSON schema generation function.
+
+    Attributes:
+        mode: Json schema mode, can be `validation` or `serialization`.
+    """
+
+    mode: JsonSchemaMode
+
+    def __call__(self, core_schema: CoreSchemaOrField, /) -> JsonSchemaValue:
+        """Call the inner handler and get the JsonSchemaValue it returns.
+        This will call the next JSON schema modifying function up until it calls
+        into `pydantic.json_schema.GenerateJsonSchema`, which will raise a
+        `pydantic.errors.PydanticInvalidForJsonSchema` error if it cannot generate
+        a JSON schema.
+
+        Args:
+            core_schema: A `pydantic_core.core_schema.CoreSchema`.
+
+        Returns:
+            JsonSchemaValue: The JSON schema generated by the inner JSON schema modify
+            functions.
+        """
+        raise NotImplementedError
+
+    def resolve_ref_schema(self, maybe_ref_json_schema: JsonSchemaValue, /) -> JsonSchemaValue:
+        """Get the real schema for a `{"$ref": ...}` schema.
+        If the schema given is not a `$ref` schema, it will be returned as is.
+        This means you don't have to check before calling this function.
+
+        Args:
+            maybe_ref_json_schema: A JsonSchemaValue which may be a `$ref` schema.
+
+        Raises:
+            LookupError: If the ref is not found.
+
+        Returns:
+            JsonSchemaValue: A JsonSchemaValue that has no `$ref`.
+        """
+        raise NotImplementedError
+
+
+class GetCoreSchemaHandler:
+    """Handler to call into the next CoreSchema schema generation function."""
+
+    def __call__(self, source_type: Any, /) -> core_schema.CoreSchema:
+        """Call the inner handler and get the CoreSchema it returns.
+        This will call the next CoreSchema modifying function up until it calls
+        into Pydantic's internal schema generation machinery, which will raise a
+        `pydantic.errors.PydanticSchemaGenerationError` error if it cannot generate
+        a CoreSchema for the given source type.
+
+        Args:
+            source_type: The input type.
+
+        Returns:
+            CoreSchema: The `pydantic-core` CoreSchema generated.
+        """
+        raise NotImplementedError
+
+    def generate_schema(self, source_type: Any, /) -> core_schema.CoreSchema:
+        """Generate a schema unrelated to the current context.
+        Use this function if e.g. you are handling schema generation for a sequence
+        and want to generate a schema for its items.
+        Otherwise, you may end up doing something like applying a `min_length` constraint
+        that was intended for the sequence itself to its items!
+
+        Args:
+            source_type: The input type.
+
+        Returns:
+            CoreSchema: The `pydantic-core` CoreSchema generated.
+        """
+        raise NotImplementedError
+
+    def resolve_ref_schema(self, maybe_ref_schema: core_schema.CoreSchema, /) -> core_schema.CoreSchema:
+        """Get the real schema for a `definition-ref` schema.
+        If the schema given is not a `definition-ref` schema, it will be returned as is.
+        This means you don't have to check before calling this function.
+
+        Args:
+            maybe_ref_schema: A `CoreSchema`, `ref`-based or not.
+
+        Raises:
+            LookupError: If the `ref` is not found.
+
+        Returns:
+            A concrete `CoreSchema`.
+        """
+        raise NotImplementedError
+
+    @property
+    def field_name(self) -> str | None:
+        """Get the name of the closest field to this validator."""
+        raise NotImplementedError
+
+    def _get_types_namespace(self) -> NamespacesTuple:
+        """Internal method used during type resolution for serializer annotations."""
+        raise NotImplementedError

infer_4_37_2/lib/python3.10/site-packages/pydantic/color.py

@@ -0,0 +1,604 @@
+"""Color definitions are used as per the CSS3
+[CSS Color Module Level 3](http://www.w3.org/TR/css3-color/#svg-color) specification.
+
+A few colors have multiple names referring to the sames colors, eg. `grey` and `gray` or `aqua` and `cyan`.
+
+In these cases the _last_ color when sorted alphabetically takes preferences,
+eg. `Color((0, 255, 255)).as_named() == 'cyan'` because "cyan" comes after "aqua".
+
+Warning: Deprecated
+    The `Color` class is deprecated, use `pydantic_extra_types` instead.
+    See [`pydantic-extra-types.Color`](../usage/types/extra_types/color_types.md)
+    for more information.
+"""
+
+import math
+import re
+from colorsys import hls_to_rgb, rgb_to_hls
+from typing import Any, Callable, Optional, Tuple, Type, Union, cast
+
+from pydantic_core import CoreSchema, PydanticCustomError, core_schema
+from typing_extensions import deprecated
+
+from ._internal import _repr
+from ._internal._schema_generation_shared import GetJsonSchemaHandler as _GetJsonSchemaHandler
+from .json_schema import JsonSchemaValue
+from .warnings import PydanticDeprecatedSince20
+
+ColorTuple = Union[Tuple[int, int, int], Tuple[int, int, int, float]]
+ColorType = Union[ColorTuple, str]
+HslColorTuple = Union[Tuple[float, float, float], Tuple[float, float, float, float]]
+
+
+class RGBA:
+    """Internal use only as a representation of a color."""
+
+    __slots__ = 'r', 'g', 'b', 'alpha', '_tuple'
+
+    def __init__(self, r: float, g: float, b: float, alpha: Optional[float]):
+        self.r = r
+        self.g = g
+        self.b = b
+        self.alpha = alpha
+
+        self._tuple: Tuple[float, float, float, Optional[float]] = (r, g, b, alpha)
+
+    def __getitem__(self, item: Any) -> Any:
+        return self._tuple[item]
+
+
+# these are not compiled here to avoid import slowdown, they'll be compiled the first time they're used, then cached
+_r_255 = r'(\d{1,3}(?:\.\d+)?)'
+_r_comma = r'\s*,\s*'
+_r_alpha = r'(\d(?:\.\d+)?|\.\d+|\d{1,2}%)'
+_r_h = r'(-?\d+(?:\.\d+)?|-?\.\d+)(deg|rad|turn)?'
+_r_sl = r'(\d{1,3}(?:\.\d+)?)%'
+r_hex_short = r'\s*(?:#|0x)?([0-9a-f])([0-9a-f])([0-9a-f])([0-9a-f])?\s*'
+r_hex_long = r'\s*(?:#|0x)?([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})?\s*'
+# CSS3 RGB examples: rgb(0, 0, 0), rgba(0, 0, 0, 0.5), rgba(0, 0, 0, 50%)
+r_rgb = rf'\s*rgba?\(\s*{_r_255}{_r_comma}{_r_255}{_r_comma}{_r_255}(?:{_r_comma}{_r_alpha})?\s*\)\s*'
+# CSS3 HSL examples: hsl(270, 60%, 50%), hsla(270, 60%, 50%, 0.5), hsla(270, 60%, 50%, 50%)
+r_hsl = rf'\s*hsla?\(\s*{_r_h}{_r_comma}{_r_sl}{_r_comma}{_r_sl}(?:{_r_comma}{_r_alpha})?\s*\)\s*'
+# CSS4 RGB examples: rgb(0 0 0), rgb(0 0 0 / 0.5), rgb(0 0 0 / 50%), rgba(0 0 0 / 50%)
+r_rgb_v4_style = rf'\s*rgba?\(\s*{_r_255}\s+{_r_255}\s+{_r_255}(?:\s*/\s*{_r_alpha})?\s*\)\s*'
+# CSS4 HSL examples: hsl(270 60% 50%), hsl(270 60% 50% / 0.5), hsl(270 60% 50% / 50%), hsla(270 60% 50% / 50%)
+r_hsl_v4_style = rf'\s*hsla?\(\s*{_r_h}\s+{_r_sl}\s+{_r_sl}(?:\s*/\s*{_r_alpha})?\s*\)\s*'
+
+# colors where the two hex characters are the same, if all colors match this the short version of hex colors can be used
+repeat_colors = {int(c * 2, 16) for c in '0123456789abcdef'}
+rads = 2 * math.pi
+
+
+@deprecated(
+    'The `Color` class is deprecated, use `pydantic_extra_types` instead. '
+    'See https://docs.pydantic.dev/latest/api/pydantic_extra_types_color/.',
+    category=PydanticDeprecatedSince20,
+)
+class Color(_repr.Representation):
+    """Represents a color."""
+
+    __slots__ = '_original', '_rgba'
+
+    def __init__(self, value: ColorType) -> None:
+        self._rgba: RGBA
+        self._original: ColorType
+        if isinstance(value, (tuple, list)):
+            self._rgba = parse_tuple(value)
+        elif isinstance(value, str):
+            self._rgba = parse_str(value)
+        elif isinstance(value, Color):
+            self._rgba = value._rgba
+            value = value._original
+        else:
+            raise PydanticCustomError(
+                'color_error', 'value is not a valid color: value must be a tuple, list or string'
+            )
+
+        # if we've got here value must be a valid color
+        self._original = value
+
+    @classmethod
+    def __get_pydantic_json_schema__(
+        cls, core_schema: core_schema.CoreSchema, handler: _GetJsonSchemaHandler
+    ) -> JsonSchemaValue:
+        field_schema = {}
+        field_schema.update(type='string', format='color')
+        return field_schema
+
+    def original(self) -> ColorType:
+        """Original value passed to `Color`."""
+        return self._original
+
+    def as_named(self, *, fallback: bool = False) -> str:
+        """Returns the name of the color if it can be found in `COLORS_BY_VALUE` dictionary,
+        otherwise returns the hexadecimal representation of the color or raises `ValueError`.
+
+        Args:
+            fallback: If True, falls back to returning the hexadecimal representation of
+                the color instead of raising a ValueError when no named color is found.
+
+        Returns:
+            The name of the color, or the hexadecimal representation of the color.
+
+        Raises:
+            ValueError: When no named color is found and fallback is `False`.
+        """
+        if self._rgba.alpha is None:
+            rgb = cast(Tuple[int, int, int], self.as_rgb_tuple())
+            try:
+                return COLORS_BY_VALUE[rgb]
+            except KeyError as e:
+                if fallback:
+                    return self.as_hex()
+                else:
+                    raise ValueError('no named color found, use fallback=True, as_hex() or as_rgb()') from e
+        else:
+            return self.as_hex()
+
+    def as_hex(self) -> str:
+        """Returns the hexadecimal representation of the color.
+
+        Hex string representing the color can be 3, 4, 6, or 8 characters depending on whether the string
+        a "short" representation of the color is possible and whether there's an alpha channel.
+
+        Returns:
+            The hexadecimal representation of the color.
+        """
+        values = [float_to_255(c) for c in self._rgba[:3]]
+        if self._rgba.alpha is not None:
+            values.append(float_to_255(self._rgba.alpha))
+
+        as_hex = ''.join(f'{v:02x}' for v in values)
+        if all(c in repeat_colors for c in values):
+            as_hex = ''.join(as_hex[c] for c in range(0, len(as_hex), 2))
+        return '#' + as_hex
+
+    def as_rgb(self) -> str:
+        """Color as an `rgb(<r>, <g>, <b>)` or `rgba(<r>, <g>, <b>, <a>)` string."""
+        if self._rgba.alpha is None:
+            return f'rgb({float_to_255(self._rgba.r)}, {float_to_255(self._rgba.g)}, {float_to_255(self._rgba.b)})'
+        else:
+            return (
+                f'rgba({float_to_255(self._rgba.r)}, {float_to_255(self._rgba.g)}, {float_to_255(self._rgba.b)}, '
+                f'{round(self._alpha_float(), 2)})'
+            )
+
+    def as_rgb_tuple(self, *, alpha: Optional[bool] = None) -> ColorTuple:
+        """Returns the color as an RGB or RGBA tuple.
+
+        Args:
+            alpha: Whether to include the alpha channel. There are three options for this input:
+
+                - `None` (default): Include alpha only if it's set. (e.g. not `None`)
+                - `True`: Always include alpha.
+                - `False`: Always omit alpha.
+
+        Returns:
+            A tuple that contains the values of the red, green, and blue channels in the range 0 to 255.
+                If alpha is included, it is in the range 0 to 1.
+        """
+        r, g, b = (float_to_255(c) for c in self._rgba[:3])
+        if alpha is None:
+            if self._rgba.alpha is None:
+                return r, g, b
+            else:
+                return r, g, b, self._alpha_float()
+        elif alpha:
+            return r, g, b, self._alpha_float()
+        else:
+            # alpha is False
+            return r, g, b
+
+    def as_hsl(self) -> str:
+        """Color as an `hsl(<h>, <s>, <l>)` or `hsl(<h>, <s>, <l>, <a>)` string."""
+        if self._rgba.alpha is None:
+            h, s, li = self.as_hsl_tuple(alpha=False)  # type: ignore
+            return f'hsl({h * 360:0.0f}, {s:0.0%}, {li:0.0%})'
+        else:
+            h, s, li, a = self.as_hsl_tuple(alpha=True)  # type: ignore
+            return f'hsl({h * 360:0.0f}, {s:0.0%}, {li:0.0%}, {round(a, 2)})'
+
+    def as_hsl_tuple(self, *, alpha: Optional[bool] = None) -> HslColorTuple:
+        """Returns the color as an HSL or HSLA tuple.
+
+        Args:
+            alpha: Whether to include the alpha channel.
+
+                - `None` (default): Include the alpha channel only if it's set (e.g. not `None`).
+                - `True`: Always include alpha.
+                - `False`: Always omit alpha.
+
+        Returns:
+            The color as a tuple of hue, saturation, lightness, and alpha (if included).
+                All elements are in the range 0 to 1.
+
+        Note:
+            This is HSL as used in HTML and most other places, not HLS as used in Python's `colorsys`.
+        """
+        h, l, s = rgb_to_hls(self._rgba.r, self._rgba.g, self._rgba.b)  # noqa: E741
+        if alpha is None:
+            if self._rgba.alpha is None:
+                return h, s, l
+            else:
+                return h, s, l, self._alpha_float()
+        if alpha:
+            return h, s, l, self._alpha_float()
+        else:
+            # alpha is False
+            return h, s, l
+
+    def _alpha_float(self) -> float:
+        return 1 if self._rgba.alpha is None else self._rgba.alpha
+
+    @classmethod
+    def __get_pydantic_core_schema__(
+        cls, source: Type[Any], handler: Callable[[Any], CoreSchema]
+    ) -> core_schema.CoreSchema:
+        return core_schema.with_info_plain_validator_function(
+            cls._validate, serialization=core_schema.to_string_ser_schema()
+        )
+
+    @classmethod
+    def _validate(cls, __input_value: Any, _: Any) -> 'Color':
+        return cls(__input_value)
+
+    def __str__(self) -> str:
+        return self.as_named(fallback=True)
+
+    def __repr_args__(self) -> '_repr.ReprArgs':
+        return [(None, self.as_named(fallback=True))] + [('rgb', self.as_rgb_tuple())]
+
+    def __eq__(self, other: Any) -> bool:
+        return isinstance(other, Color) and self.as_rgb_tuple() == other.as_rgb_tuple()
+
+    def __hash__(self) -> int:
+        return hash(self.as_rgb_tuple())
+
+
+def parse_tuple(value: Tuple[Any, ...]) -> RGBA:
+    """Parse a tuple or list to get RGBA values.
+
+    Args:
+        value: A tuple or list.
+
+    Returns:
+        An `RGBA` tuple parsed from the input tuple.
+
+    Raises:
+        PydanticCustomError: If tuple is not valid.
+    """
+    if len(value) == 3:
+        r, g, b = (parse_color_value(v) for v in value)
+        return RGBA(r, g, b, None)
+    elif len(value) == 4:
+        r, g, b = (parse_color_value(v) for v in value[:3])
+        return RGBA(r, g, b, parse_float_alpha(value[3]))
+    else:
+        raise PydanticCustomError('color_error', 'value is not a valid color: tuples must have length 3 or 4')
+
+
+def parse_str(value: str) -> RGBA:
+    """Parse a string representing a color to an RGBA tuple.
+
+    Possible formats for the input string include:
+
+    * named color, see `COLORS_BY_NAME`
+    * hex short eg. `<prefix>fff` (prefix can be `#`, `0x` or nothing)
+    * hex long eg. `<prefix>ffffff` (prefix can be `#`, `0x` or nothing)
+    * `rgb(<r>, <g>, <b>)`
+    * `rgba(<r>, <g>, <b>, <a>)`
+
+    Args:
+        value: A string representing a color.
+
+    Returns:
+        An `RGBA` tuple parsed from the input string.
+
+    Raises:
+        ValueError: If the input string cannot be parsed to an RGBA tuple.
+    """
+    value_lower = value.lower()
+    try:
+        r, g, b = COLORS_BY_NAME[value_lower]
+    except KeyError:
+        pass
+    else:
+        return ints_to_rgba(r, g, b, None)
+
+    m = re.fullmatch(r_hex_short, value_lower)
+    if m:
+        *rgb, a = m.groups()
+        r, g, b = (int(v * 2, 16) for v in rgb)
+        if a:
+            alpha: Optional[float] = int(a * 2, 16) / 255
+        else:
+            alpha = None
+        return ints_to_rgba(r, g, b, alpha)
+
+    m = re.fullmatch(r_hex_long, value_lower)
+    if m:
+        *rgb, a = m.groups()
+        r, g, b = (int(v, 16) for v in rgb)
+        if a:
+            alpha = int(a, 16) / 255
+        else:
+            alpha = None
+        return ints_to_rgba(r, g, b, alpha)
+
+    m = re.fullmatch(r_rgb, value_lower) or re.fullmatch(r_rgb_v4_style, value_lower)
+    if m:
+        return ints_to_rgba(*m.groups())  # type: ignore
+
+    m = re.fullmatch(r_hsl, value_lower) or re.fullmatch(r_hsl_v4_style, value_lower)
+    if m:
+        return parse_hsl(*m.groups())  # type: ignore
+
+    raise PydanticCustomError('color_error', 'value is not a valid color: string not recognised as a valid color')
+
+
+def ints_to_rgba(r: Union[int, str], g: Union[int, str], b: Union[int, str], alpha: Optional[float] = None) -> RGBA:
+    """Converts integer or string values for RGB color and an optional alpha value to an `RGBA` object.
+
+    Args:
+        r: An integer or string representing the red color value.
+        g: An integer or string representing the green color value.
+        b: An integer or string representing the blue color value.
+        alpha: A float representing the alpha value. Defaults to None.
+
+    Returns:
+        An instance of the `RGBA` class with the corresponding color and alpha values.
+    """
+    return RGBA(parse_color_value(r), parse_color_value(g), parse_color_value(b), parse_float_alpha(alpha))
+
+
+def parse_color_value(value: Union[int, str], max_val: int = 255) -> float:
+    """Parse the color value provided and return a number between 0 and 1.
+
+    Args:
+        value: An integer or string color value.
+        max_val: Maximum range value. Defaults to 255.
+
+    Raises:
+        PydanticCustomError: If the value is not a valid color.
+
+    Returns:
+        A number between 0 and 1.
+    """
+    try:
+        color = float(value)
+    except ValueError:
+        raise PydanticCustomError('color_error', 'value is not a valid color: color values must be a valid number')
+    if 0 <= color <= max_val:
+        return color / max_val
+    else:
+        raise PydanticCustomError(
+            'color_error',
+            'value is not a valid color: color values must be in the range 0 to {max_val}',
+            {'max_val': max_val},
+        )
+
+
+def parse_float_alpha(value: Union[None, str, float, int]) -> Optional[float]:
+    """Parse an alpha value checking it's a valid float in the range 0 to 1.
+
+    Args:
+        value: The input value to parse.
+
+    Returns:
+        The parsed value as a float, or `None` if the value was None or equal 1.
+
+    Raises:
+        PydanticCustomError: If the input value cannot be successfully parsed as a float in the expected range.
+    """
+    if value is None:
+        return None
+    try:
+        if isinstance(value, str) and value.endswith('%'):
+            alpha = float(value[:-1]) / 100
+        else:
+            alpha = float(value)
+    except ValueError:
+        raise PydanticCustomError('color_error', 'value is not a valid color: alpha values must be a valid float')
+
+    if math.isclose(alpha, 1):
+        return None
+    elif 0 <= alpha <= 1:
+        return alpha
+    else:
+        raise PydanticCustomError('color_error', 'value is not a valid color: alpha values must be in the range 0 to 1')
+
+
+def parse_hsl(h: str, h_units: str, sat: str, light: str, alpha: Optional[float] = None) -> RGBA:
+    """Parse raw hue, saturation, lightness, and alpha values and convert to RGBA.
+
+    Args:
+        h: The hue value.
+        h_units: The unit for hue value.
+        sat: The saturation value.
+        light: The lightness value.
+        alpha: Alpha value.
+
+    Returns:
+        An instance of `RGBA`.
+    """
+    s_value, l_value = parse_color_value(sat, 100), parse_color_value(light, 100)
+
+    h_value = float(h)
+    if h_units in {None, 'deg'}:
+        h_value = h_value % 360 / 360
+    elif h_units == 'rad':
+        h_value = h_value % rads / rads
+    else:
+        # turns
+        h_value = h_value % 1
+
+    r, g, b = hls_to_rgb(h_value, l_value, s_value)
+    return RGBA(r, g, b, parse_float_alpha(alpha))
+
+
+def float_to_255(c: float) -> int:
+    """Converts a float value between 0 and 1 (inclusive) to an integer between 0 and 255 (inclusive).
+
+    Args:
+        c: The float value to be converted. Must be between 0 and 1 (inclusive).
+
+    Returns:
+        The integer equivalent of the given float value rounded to the nearest whole number.
+
+    Raises:
+        ValueError: If the given float value is outside the acceptable range of 0 to 1 (inclusive).
+    """
+    return int(round(c * 255))
+
+
+COLORS_BY_NAME = {
+    'aliceblue': (240, 248, 255),
+    'antiquewhite': (250, 235, 215),
+    'aqua': (0, 255, 255),
+    'aquamarine': (127, 255, 212),
+    'azure': (240, 255, 255),
+    'beige': (245, 245, 220),
+    'bisque': (255, 228, 196),
+    'black': (0, 0, 0),
+    'blanchedalmond': (255, 235, 205),
+    'blue': (0, 0, 255),
+    'blueviolet': (138, 43, 226),
+    'brown': (165, 42, 42),
+    'burlywood': (222, 184, 135),
+    'cadetblue': (95, 158, 160),
+    'chartreuse': (127, 255, 0),
+    'chocolate': (210, 105, 30),
+    'coral': (255, 127, 80),
+    'cornflowerblue': (100, 149, 237),
+    'cornsilk': (255, 248, 220),
+    'crimson': (220, 20, 60),
+    'cyan': (0, 255, 255),
+    'darkblue': (0, 0, 139),
+    'darkcyan': (0, 139, 139),
+    'darkgoldenrod': (184, 134, 11),
+    'darkgray': (169, 169, 169),
+    'darkgreen': (0, 100, 0),
+    'darkgrey': (169, 169, 169),
+    'darkkhaki': (189, 183, 107),
+    'darkmagenta': (139, 0, 139),
+    'darkolivegreen': (85, 107, 47),
+    'darkorange': (255, 140, 0),
+    'darkorchid': (153, 50, 204),
+    'darkred': (139, 0, 0),
+    'darksalmon': (233, 150, 122),
+    'darkseagreen': (143, 188, 143),
+    'darkslateblue': (72, 61, 139),
+    'darkslategray': (47, 79, 79),
+    'darkslategrey': (47, 79, 79),
+    'darkturquoise': (0, 206, 209),
+    'darkviolet': (148, 0, 211),
+    'deeppink': (255, 20, 147),
+    'deepskyblue': (0, 191, 255),
+    'dimgray': (105, 105, 105),
+    'dimgrey': (105, 105, 105),
+    'dodgerblue': (30, 144, 255),
+    'firebrick': (178, 34, 34),
+    'floralwhite': (255, 250, 240),
+    'forestgreen': (34, 139, 34),
+    'fuchsia': (255, 0, 255),
+    'gainsboro': (220, 220, 220),
+    'ghostwhite': (248, 248, 255),
+    'gold': (255, 215, 0),
+    'goldenrod': (218, 165, 32),
+    'gray': (128, 128, 128),
+    'green': (0, 128, 0),
+    'greenyellow': (173, 255, 47),
+    'grey': (128, 128, 128),
+    'honeydew': (240, 255, 240),
+    'hotpink': (255, 105, 180),
+    'indianred': (205, 92, 92),
+    'indigo': (75, 0, 130),
+    'ivory': (255, 255, 240),
+    'khaki': (240, 230, 140),
+    'lavender': (230, 230, 250),
+    'lavenderblush': (255, 240, 245),
+    'lawngreen': (124, 252, 0),
+    'lemonchiffon': (255, 250, 205),
+    'lightblue': (173, 216, 230),
+    'lightcoral': (240, 128, 128),
+    'lightcyan': (224, 255, 255),
+    'lightgoldenrodyellow': (250, 250, 210),
+    'lightgray': (211, 211, 211),
+    'lightgreen': (144, 238, 144),
+    'lightgrey': (211, 211, 211),
+    'lightpink': (255, 182, 193),
+    'lightsalmon': (255, 160, 122),
+    'lightseagreen': (32, 178, 170),
+    'lightskyblue': (135, 206, 250),
+    'lightslategray': (119, 136, 153),
+    'lightslategrey': (119, 136, 153),
+    'lightsteelblue': (176, 196, 222),
+    'lightyellow': (255, 255, 224),
+    'lime': (0, 255, 0),
+    'limegreen': (50, 205, 50),
+    'linen': (250, 240, 230),
+    'magenta': (255, 0, 255),
+    'maroon': (128, 0, 0),
+    'mediumaquamarine': (102, 205, 170),
+    'mediumblue': (0, 0, 205),
+    'mediumorchid': (186, 85, 211),
+    'mediumpurple': (147, 112, 219),
+    'mediumseagreen': (60, 179, 113),
+    'mediumslateblue': (123, 104, 238),
+    'mediumspringgreen': (0, 250, 154),
+    'mediumturquoise': (72, 209, 204),
+    'mediumvioletred': (199, 21, 133),
+    'midnightblue': (25, 25, 112),
+    'mintcream': (245, 255, 250),
+    'mistyrose': (255, 228, 225),
+    'moccasin': (255, 228, 181),
+    'navajowhite': (255, 222, 173),
+    'navy': (0, 0, 128),
+    'oldlace': (253, 245, 230),
+    'olive': (128, 128, 0),
+    'olivedrab': (107, 142, 35),
+    'orange': (255, 165, 0),
+    'orangered': (255, 69, 0),
+    'orchid': (218, 112, 214),
+    'palegoldenrod': (238, 232, 170),
+    'palegreen': (152, 251, 152),
+    'paleturquoise': (175, 238, 238),
+    'palevioletred': (219, 112, 147),
+    'papayawhip': (255, 239, 213),
+    'peachpuff': (255, 218, 185),
+    'peru': (205, 133, 63),
+    'pink': (255, 192, 203),
+    'plum': (221, 160, 221),
+    'powderblue': (176, 224, 230),
+    'purple': (128, 0, 128),
+    'red': (255, 0, 0),
+    'rosybrown': (188, 143, 143),
+    'royalblue': (65, 105, 225),
+    'saddlebrown': (139, 69, 19),
+    'salmon': (250, 128, 114),
+    'sandybrown': (244, 164, 96),
+    'seagreen': (46, 139, 87),
+    'seashell': (255, 245, 238),
+    'sienna': (160, 82, 45),
+    'silver': (192, 192, 192),
+    'skyblue': (135, 206, 235),
+    'slateblue': (106, 90, 205),
+    'slategray': (112, 128, 144),
+    'slategrey': (112, 128, 144),
+    'snow': (255, 250, 250),
+    'springgreen': (0, 255, 127),
+    'steelblue': (70, 130, 180),
+    'tan': (210, 180, 140),
+    'teal': (0, 128, 128),
+    'thistle': (216, 191, 216),
+    'tomato': (255, 99, 71),
+    'turquoise': (64, 224, 208),
+    'violet': (238, 130, 238),
+    'wheat': (245, 222, 179),
+    'white': (255, 255, 255),
+    'whitesmoke': (245, 245, 245),
+    'yellow': (255, 255, 0),
+    'yellowgreen': (154, 205, 50),
+}
+
+COLORS_BY_VALUE = {v: k for k, v in COLORS_BY_NAME.items()}

infer_4_37_2/lib/python3.10/site-packages/pydantic/errors.py

@@ -0,0 +1,162 @@
+"""Pydantic-specific errors."""
+
+from __future__ import annotations as _annotations
+
+import re
+
+from typing_extensions import Literal, Self
+
+from ._migration import getattr_migration
+from .version import version_short
+
+__all__ = (
+    'PydanticUserError',
+    'PydanticUndefinedAnnotation',
+    'PydanticImportError',
+    'PydanticSchemaGenerationError',
+    'PydanticInvalidForJsonSchema',
+    'PydanticErrorCodes',
+)
+
+# We use this URL to allow for future flexibility about how we host the docs, while allowing for Pydantic
+# code in the while with "old" URLs to still work.
+# 'u' refers to "user errors" - e.g. errors caused by developers using pydantic, as opposed to validation errors.
+DEV_ERROR_DOCS_URL = f'https://errors.pydantic.dev/{version_short()}/u/'
+PydanticErrorCodes = Literal[
+    'class-not-fully-defined',
+    'custom-json-schema',
+    'decorator-missing-field',
+    'discriminator-no-field',
+    'discriminator-alias-type',
+    'discriminator-needs-literal',
+    'discriminator-alias',
+    'discriminator-validator',
+    'callable-discriminator-no-tag',
+    'typed-dict-version',
+    'model-field-overridden',
+    'model-field-missing-annotation',
+    'config-both',
+    'removed-kwargs',
+    'circular-reference-schema',
+    'invalid-for-json-schema',
+    'json-schema-already-used',
+    'base-model-instantiated',
+    'undefined-annotation',
+    'schema-for-unknown-type',
+    'import-error',
+    'create-model-field-definitions',
+    'create-model-config-base',
+    'validator-no-fields',
+    'validator-invalid-fields',
+    'validator-instance-method',
+    'validator-input-type',
+    'root-validator-pre-skip',
+    'model-serializer-instance-method',
+    'validator-field-config-info',
+    'validator-v1-signature',
+    'validator-signature',
+    'field-serializer-signature',
+    'model-serializer-signature',
+    'multiple-field-serializers',
+    'invalid-annotated-type',
+    'type-adapter-config-unused',
+    'root-model-extra',
+    'unevaluable-type-annotation',
+    'dataclass-init-false-extra-allow',
+    'clashing-init-and-init-var',
+    'model-config-invalid-field-name',
+    'with-config-on-model',
+    'dataclass-on-model',
+    'validate-call-type',
+    'unpack-typed-dict',
+    'overlapping-unpack-typed-dict',
+    'invalid-self-type',
+]
+
+
+class PydanticErrorMixin:
+    """A mixin class for common functionality shared by all Pydantic-specific errors.
+
+    Attributes:
+        message: A message describing the error.
+        code: An optional error code from PydanticErrorCodes enum.
+    """
+
+    def __init__(self, message: str, *, code: PydanticErrorCodes | None) -> None:
+        self.message = message
+        self.code = code
+
+    def __str__(self) -> str:
+        if self.code is None:
+            return self.message
+        else:
+            return f'{self.message}\n\nFor further information visit {DEV_ERROR_DOCS_URL}{self.code}'
+
+
+class PydanticUserError(PydanticErrorMixin, TypeError):
+    """An error raised due to incorrect use of Pydantic."""
+
+
+class PydanticUndefinedAnnotation(PydanticErrorMixin, NameError):
+    """A subclass of `NameError` raised when handling undefined annotations during `CoreSchema` generation.
+
+    Attributes:
+        name: Name of the error.
+        message: Description of the error.
+    """
+
+    def __init__(self, name: str, message: str) -> None:
+        self.name = name
+        super().__init__(message=message, code='undefined-annotation')
+
+    @classmethod
+    def from_name_error(cls, name_error: NameError) -> Self:
+        """Convert a `NameError` to a `PydanticUndefinedAnnotation` error.
+
+        Args:
+            name_error: `NameError` to be converted.
+
+        Returns:
+            Converted `PydanticUndefinedAnnotation` error.
+        """
+        try:
+            name = name_error.name  # type: ignore  # python > 3.10
+        except AttributeError:
+            name = re.search(r".*'(.+?)'", str(name_error)).group(1)  # type: ignore[union-attr]
+        return cls(name=name, message=str(name_error))
+
+
+class PydanticImportError(PydanticErrorMixin, ImportError):
+    """An error raised when an import fails due to module changes between V1 and V2.
+
+    Attributes:
+        message: Description of the error.
+    """
+
+    def __init__(self, message: str) -> None:
+        super().__init__(message, code='import-error')
+
+
+class PydanticSchemaGenerationError(PydanticUserError):
+    """An error raised during failures to generate a `CoreSchema` for some type.
+
+    Attributes:
+        message: Description of the error.
+    """
+
+    def __init__(self, message: str) -> None:
+        super().__init__(message, code='schema-for-unknown-type')
+
+
+class PydanticInvalidForJsonSchema(PydanticUserError):
+    """An error raised during failures to generate a JSON schema for some `CoreSchema`.
+
+    Attributes:
+        message: Description of the error.
+    """
+
+    def __init__(self, message: str) -> None:
+        super().__init__(message, code='invalid-for-json-schema')
+
+
+__getattr__ = getattr_migration(__name__)

infer_4_37_2/lib/python3.10/site-packages/pydantic/generics.py

@@ -0,0 +1,5 @@
+"""The `generics` module is a backport module from V1."""
+
+from ._migration import getattr_migration
+
+__getattr__ = getattr_migration(__name__)

infer_4_37_2/lib/python3.10/site-packages/pydantic/mypy.py

@@ -0,0 +1,1320 @@
+"""This module includes classes and functions designed specifically for use with the mypy plugin."""
+
+from __future__ import annotations
+
+import sys
+from configparser import ConfigParser
+from typing import Any, Callable, Iterator
+
+from mypy.errorcodes import ErrorCode
+from mypy.expandtype import expand_type, expand_type_by_instance
+from mypy.nodes import (
+    ARG_NAMED,
+    ARG_NAMED_OPT,
+    ARG_OPT,
+    ARG_POS,
+    ARG_STAR2,
+    INVARIANT,
+    MDEF,
+    Argument,
+    AssignmentStmt,
+    Block,
+    CallExpr,
+    ClassDef,
+    Context,
+    Decorator,
+    DictExpr,
+    EllipsisExpr,
+    Expression,
+    FuncDef,
+    IfStmt,
+    JsonDict,
+    MemberExpr,
+    NameExpr,
+    PassStmt,
+    PlaceholderNode,
+    RefExpr,
+    Statement,
+    StrExpr,
+    SymbolTableNode,
+    TempNode,
+    TypeAlias,
+    TypeInfo,
+    Var,
+)
+from mypy.options import Options
+from mypy.plugin import (
+    CheckerPluginInterface,
+    ClassDefContext,
+    MethodContext,
+    Plugin,
+    ReportConfigContext,
+    SemanticAnalyzerPluginInterface,
+)
+from mypy.plugins.common import (
+    deserialize_and_fixup_type,
+)
+from mypy.semanal import set_callable_name
+from mypy.server.trigger import make_wildcard_trigger
+from mypy.state import state
+from mypy.typeops import map_type_from_supertype
+from mypy.types import (
+    AnyType,
+    CallableType,
+    Instance,
+    NoneType,
+    Type,
+    TypeOfAny,
+    TypeType,
+    TypeVarType,
+    UnionType,
+    get_proper_type,
+)
+from mypy.typevars import fill_typevars
+from mypy.util import get_unique_redefinition_name
+from mypy.version import __version__ as mypy_version
+
+from pydantic._internal import _fields
+from pydantic.version import parse_mypy_version
+
+CONFIGFILE_KEY = 'pydantic-mypy'
+METADATA_KEY = 'pydantic-mypy-metadata'
+BASEMODEL_FULLNAME = 'pydantic.main.BaseModel'
+BASESETTINGS_FULLNAME = 'pydantic_settings.main.BaseSettings'
+ROOT_MODEL_FULLNAME = 'pydantic.root_model.RootModel'
+MODEL_METACLASS_FULLNAME = 'pydantic._internal._model_construction.ModelMetaclass'
+FIELD_FULLNAME = 'pydantic.fields.Field'
+DATACLASS_FULLNAME = 'pydantic.dataclasses.dataclass'
+MODEL_VALIDATOR_FULLNAME = 'pydantic.functional_validators.model_validator'
+DECORATOR_FULLNAMES = {
+    'pydantic.functional_validators.field_validator',
+    'pydantic.functional_validators.model_validator',
+    'pydantic.functional_serializers.serializer',
+    'pydantic.functional_serializers.model_serializer',
+    'pydantic.deprecated.class_validators.validator',
+    'pydantic.deprecated.class_validators.root_validator',
+}
+
+
+MYPY_VERSION_TUPLE = parse_mypy_version(mypy_version)
+BUILTINS_NAME = 'builtins'
+
+# Increment version if plugin changes and mypy caches should be invalidated
+__version__ = 2
+
+
+def plugin(version: str) -> type[Plugin]:
+    """`version` is the mypy version string.
+
+    We might want to use this to print a warning if the mypy version being used is
+    newer, or especially older, than we expect (or need).
+
+    Args:
+        version: The mypy version string.
+
+    Return:
+        The Pydantic mypy plugin type.
+    """
+    return PydanticPlugin
+
+
+class PydanticPlugin(Plugin):
+    """The Pydantic mypy plugin."""
+
+    def __init__(self, options: Options) -> None:
+        self.plugin_config = PydanticPluginConfig(options)
+        self._plugin_data = self.plugin_config.to_data()
+        super().__init__(options)
+
+    def get_base_class_hook(self, fullname: str) -> Callable[[ClassDefContext], None] | None:
+        """Update Pydantic model class."""
+        sym = self.lookup_fully_qualified(fullname)
+        if sym and isinstance(sym.node, TypeInfo):  # pragma: no branch
+            # No branching may occur if the mypy cache has not been cleared
+            if any(base.fullname == BASEMODEL_FULLNAME for base in sym.node.mro):
+                return self._pydantic_model_class_maker_callback
+        return None
+
+    def get_metaclass_hook(self, fullname: str) -> Callable[[ClassDefContext], None] | None:
+        """Update Pydantic `ModelMetaclass` definition."""
+        if fullname == MODEL_METACLASS_FULLNAME:
+            return self._pydantic_model_metaclass_marker_callback
+        return None
+
+    def get_method_hook(self, fullname: str) -> Callable[[MethodContext], Type] | None:
+        """Adjust return type of `from_orm` method call."""
+        if fullname.endswith('.from_orm'):
+            return from_attributes_callback
+        return None
+
+    def report_config_data(self, ctx: ReportConfigContext) -> dict[str, Any]:
+        """Return all plugin config data.
+
+        Used by mypy to determine if cache needs to be discarded.
+        """
+        return self._plugin_data
+
+    def _pydantic_model_class_maker_callback(self, ctx: ClassDefContext) -> None:
+        transformer = PydanticModelTransformer(ctx.cls, ctx.reason, ctx.api, self.plugin_config)
+        transformer.transform()
+
+    def _pydantic_model_metaclass_marker_callback(self, ctx: ClassDefContext) -> None:
+        """Reset dataclass_transform_spec attribute of ModelMetaclass.
+
+        Let the plugin handle it. This behavior can be disabled
+        if 'debug_dataclass_transform' is set to True', for testing purposes.
+        """
+        if self.plugin_config.debug_dataclass_transform:
+            return
+        info_metaclass = ctx.cls.info.declared_metaclass
+        assert info_metaclass, "callback not passed from 'get_metaclass_hook'"
+        if getattr(info_metaclass.type, 'dataclass_transform_spec', None):
+            info_metaclass.type.dataclass_transform_spec = None
+
+
+class PydanticPluginConfig:
+    """A Pydantic mypy plugin config holder.
+
+    Attributes:
+        init_forbid_extra: Whether to add a `**kwargs` at the end of the generated `__init__` signature.
+        init_typed: Whether to annotate fields in the generated `__init__`.
+        warn_required_dynamic_aliases: Whether to raise required dynamic aliases error.
+        debug_dataclass_transform: Whether to not reset `dataclass_transform_spec` attribute
+            of `ModelMetaclass` for testing purposes.
+    """
+
+    __slots__ = (
+        'init_forbid_extra',
+        'init_typed',
+        'warn_required_dynamic_aliases',
+        'debug_dataclass_transform',
+    )
+    init_forbid_extra: bool
+    init_typed: bool
+    warn_required_dynamic_aliases: bool
+    debug_dataclass_transform: bool  # undocumented
+
+    def __init__(self, options: Options) -> None:
+        if options.config_file is None:  # pragma: no cover
+            return
+
+        toml_config = parse_toml(options.config_file)
+        if toml_config is not None:
+            config = toml_config.get('tool', {}).get('pydantic-mypy', {})
+            for key in self.__slots__:
+                setting = config.get(key, False)
+                if not isinstance(setting, bool):
+                    raise ValueError(f'Configuration value must be a boolean for key: {key}')
+                setattr(self, key, setting)
+        else:
+            plugin_config = ConfigParser()
+            plugin_config.read(options.config_file)
+            for key in self.__slots__:
+                setting = plugin_config.getboolean(CONFIGFILE_KEY, key, fallback=False)
+                setattr(self, key, setting)
+
+    def to_data(self) -> dict[str, Any]:
+        """Returns a dict of config names to their values."""
+        return {key: getattr(self, key) for key in self.__slots__}
+
+
+def from_attributes_callback(ctx: MethodContext) -> Type:
+    """Raise an error if from_attributes is not enabled."""
+    model_type: Instance
+    ctx_type = ctx.type
+    if isinstance(ctx_type, TypeType):
+        ctx_type = ctx_type.item
+    if isinstance(ctx_type, CallableType) and isinstance(ctx_type.ret_type, Instance):
+        model_type = ctx_type.ret_type  # called on the class
+    elif isinstance(ctx_type, Instance):
+        model_type = ctx_type  # called on an instance (unusual, but still valid)
+    else:  # pragma: no cover
+        detail = f'ctx.type: {ctx_type} (of type {ctx_type.__class__.__name__})'
+        error_unexpected_behavior(detail, ctx.api, ctx.context)
+        return ctx.default_return_type
+    pydantic_metadata = model_type.type.metadata.get(METADATA_KEY)
+    if pydantic_metadata is None:
+        return ctx.default_return_type
+    if not any(base.fullname == BASEMODEL_FULLNAME for base in model_type.type.mro):
+        # not a Pydantic v2 model
+        return ctx.default_return_type
+    from_attributes = pydantic_metadata.get('config', {}).get('from_attributes')
+    if from_attributes is not True:
+        error_from_attributes(model_type.type.name, ctx.api, ctx.context)
+    return ctx.default_return_type
+
+
+class PydanticModelField:
+    """Based on mypy.plugins.dataclasses.DataclassAttribute."""
+
+    def __init__(
+        self,
+        name: str,
+        alias: str | None,
+        is_frozen: bool,
+        has_dynamic_alias: bool,
+        has_default: bool,
+        strict: bool | None,
+        line: int,
+        column: int,
+        type: Type | None,
+        info: TypeInfo,
+    ):
+        self.name = name
+        self.alias = alias
+        self.is_frozen = is_frozen
+        self.has_dynamic_alias = has_dynamic_alias
+        self.has_default = has_default
+        self.strict = strict
+        self.line = line
+        self.column = column
+        self.type = type
+        self.info = info
+
+    def to_argument(
+        self,
+        current_info: TypeInfo,
+        typed: bool,
+        model_strict: bool,
+        force_optional: bool,
+        use_alias: bool,
+        api: SemanticAnalyzerPluginInterface,
+        force_typevars_invariant: bool,
+        is_root_model_root: bool,
+    ) -> Argument:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.to_argument."""
+        variable = self.to_var(current_info, api, use_alias, force_typevars_invariant)
+
+        strict = model_strict if self.strict is None else self.strict
+        if typed or strict:
+            type_annotation = self.expand_type(current_info, api)
+        else:
+            type_annotation = AnyType(TypeOfAny.explicit)
+
+        return Argument(
+            variable=variable,
+            type_annotation=type_annotation,
+            initializer=None,
+            kind=ARG_OPT
+            if is_root_model_root
+            else (ARG_NAMED_OPT if force_optional or self.has_default else ARG_NAMED),
+        )
+
+    def expand_type(
+        self, current_info: TypeInfo, api: SemanticAnalyzerPluginInterface, force_typevars_invariant: bool = False
+    ) -> Type | None:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.expand_type."""
+        if force_typevars_invariant:
+            # In some cases, mypy will emit an error "Cannot use a covariant type variable as a parameter"
+            # To prevent that, we add an option to replace typevars with invariant ones while building certain
+            # method signatures (in particular, `__init__`). There may be a better way to do this, if this causes
+            # us problems in the future, we should look into why the dataclasses plugin doesn't have this issue.
+            if isinstance(self.type, TypeVarType):
+                modified_type = self.type.copy_modified()
+                modified_type.variance = INVARIANT
+                self.type = modified_type
+
+        if self.type is not None and self.info.self_type is not None:
+            # In general, it is not safe to call `expand_type()` during semantic analysis,
+            # however this plugin is called very late, so all types should be fully ready.
+            # Also, it is tricky to avoid eager expansion of Self types here (e.g. because
+            # we serialize attributes).
+            with state.strict_optional_set(api.options.strict_optional):
+                filled_with_typevars = fill_typevars(current_info)
+                # Cannot be TupleType as current_info represents a Pydantic model:
+                assert isinstance(filled_with_typevars, Instance)
+                if force_typevars_invariant:
+                    for arg in filled_with_typevars.args:
+                        if isinstance(arg, TypeVarType):
+                            arg.variance = INVARIANT
+                return expand_type(self.type, {self.info.self_type.id: filled_with_typevars})
+        return self.type
+
+    def to_var(
+        self,
+        current_info: TypeInfo,
+        api: SemanticAnalyzerPluginInterface,
+        use_alias: bool,
+        force_typevars_invariant: bool = False,
+    ) -> Var:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.to_var."""
+        if use_alias and self.alias is not None:
+            name = self.alias
+        else:
+            name = self.name
+
+        return Var(name, self.expand_type(current_info, api, force_typevars_invariant))
+
+    def serialize(self) -> JsonDict:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.serialize."""
+        assert self.type
+        return {
+            'name': self.name,
+            'alias': self.alias,
+            'is_frozen': self.is_frozen,
+            'has_dynamic_alias': self.has_dynamic_alias,
+            'has_default': self.has_default,
+            'strict': self.strict,
+            'line': self.line,
+            'column': self.column,
+            'type': self.type.serialize(),
+        }
+
+    @classmethod
+    def deserialize(cls, info: TypeInfo, data: JsonDict, api: SemanticAnalyzerPluginInterface) -> PydanticModelField:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.deserialize."""
+        data = data.copy()
+        typ = deserialize_and_fixup_type(data.pop('type'), api)
+        return cls(type=typ, info=info, **data)
+
+    def expand_typevar_from_subtype(self, sub_type: TypeInfo, api: SemanticAnalyzerPluginInterface) -> None:
+        """Expands type vars in the context of a subtype when an attribute is inherited
+        from a generic super type.
+        """
+        if self.type is not None:
+            with state.strict_optional_set(api.options.strict_optional):
+                self.type = map_type_from_supertype(self.type, sub_type, self.info)
+
+
+class PydanticModelClassVar:
+    """Based on mypy.plugins.dataclasses.DataclassAttribute.
+
+    ClassVars are ignored by subclasses.
+
+    Attributes:
+        name: the ClassVar name
+    """
+
+    def __init__(self, name):
+        self.name = name
+
+    @classmethod
+    def deserialize(cls, data: JsonDict) -> PydanticModelClassVar:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.deserialize."""
+        data = data.copy()
+        return cls(**data)
+
+    def serialize(self) -> JsonDict:
+        """Based on mypy.plugins.dataclasses.DataclassAttribute.serialize."""
+        return {
+            'name': self.name,
+        }
+
+
+class PydanticModelTransformer:
+    """Transform the BaseModel subclass according to the plugin settings.
+
+    Attributes:
+        tracked_config_fields: A set of field configs that the plugin has to track their value.
+    """
+
+    tracked_config_fields: set[str] = {
+        'extra',
+        'frozen',
+        'from_attributes',
+        'populate_by_name',
+        'alias_generator',
+        'strict',
+    }
+
+    def __init__(
+        self,
+        cls: ClassDef,
+        reason: Expression | Statement,
+        api: SemanticAnalyzerPluginInterface,
+        plugin_config: PydanticPluginConfig,
+    ) -> None:
+        self._cls = cls
+        self._reason = reason
+        self._api = api
+
+        self.plugin_config = plugin_config
+
+    def transform(self) -> bool:
+        """Configures the BaseModel subclass according to the plugin settings.
+
+        In particular:
+
+        * determines the model config and fields,
+        * adds a fields-aware signature for the initializer and construct methods
+        * freezes the class if frozen = True
+        * stores the fields, config, and if the class is settings in the mypy metadata for access by subclasses
+        """
+        info = self._cls.info
+        is_root_model = any(ROOT_MODEL_FULLNAME in base.fullname for base in info.mro[:-1])
+        config = self.collect_config()
+        fields, class_vars = self.collect_fields_and_class_vars(config, is_root_model)
+        if fields is None or class_vars is None:
+            # Some definitions are not ready. We need another pass.
+            return False
+        for field in fields:
+            if field.type is None:
+                return False
+
+        is_settings = any(base.fullname == BASESETTINGS_FULLNAME for base in info.mro[:-1])
+        self.add_initializer(fields, config, is_settings, is_root_model)
+        self.add_model_construct_method(fields, config, is_settings, is_root_model)
+        self.set_frozen(fields, self._api, frozen=config.frozen is True)
+
+        self.adjust_decorator_signatures()
+
+        info.metadata[METADATA_KEY] = {
+            'fields': {field.name: field.serialize() for field in fields},
+            'class_vars': {class_var.name: class_var.serialize() for class_var in class_vars},
+            'config': config.get_values_dict(),
+        }
+
+        return True
+
+    def adjust_decorator_signatures(self) -> None:
+        """When we decorate a function `f` with `pydantic.validator(...)`, `pydantic.field_validator`
+        or `pydantic.serializer(...)`, mypy sees `f` as a regular method taking a `self` instance,
+        even though pydantic internally wraps `f` with `classmethod` if necessary.
+
+        Teach mypy this by marking any function whose outermost decorator is a `validator()`,
+        `field_validator()` or `serializer()` call as a `classmethod`.
+        """
+        for sym in self._cls.info.names.values():
+            if isinstance(sym.node, Decorator):
+                first_dec = sym.node.original_decorators[0]
+                if (
+                    isinstance(first_dec, CallExpr)
+                    and isinstance(first_dec.callee, NameExpr)
+                    and first_dec.callee.fullname in DECORATOR_FULLNAMES
+                    # @model_validator(mode="after") is an exception, it expects a regular method
+                    and not (
+                        first_dec.callee.fullname == MODEL_VALIDATOR_FULLNAME
+                        and any(
+                            first_dec.arg_names[i] == 'mode' and isinstance(arg, StrExpr) and arg.value == 'after'
+                            for i, arg in enumerate(first_dec.args)
+                        )
+                    )
+                ):
+                    # TODO: Only do this if the first argument of the decorated function is `cls`
+                    sym.node.func.is_class = True
+
+    def collect_config(self) -> ModelConfigData:  # noqa: C901 (ignore complexity)
+        """Collects the values of the config attributes that are used by the plugin, accounting for parent classes."""
+        cls = self._cls
+        config = ModelConfigData()
+
+        has_config_kwargs = False
+        has_config_from_namespace = False
+
+        # Handle `class MyModel(BaseModel, <name>=<expr>, ...):`
+        for name, expr in cls.keywords.items():
+            config_data = self.get_config_update(name, expr)
+            if config_data:
+                has_config_kwargs = True
+                config.update(config_data)
+
+        # Handle `model_config`
+        stmt: Statement | None = None
+        for stmt in cls.defs.body:
+            if not isinstance(stmt, (AssignmentStmt, ClassDef)):
+                continue
+
+            if isinstance(stmt, AssignmentStmt):
+                lhs = stmt.lvalues[0]
+                if not isinstance(lhs, NameExpr) or lhs.name != 'model_config':
+                    continue
+
+                if isinstance(stmt.rvalue, CallExpr):  # calls to `dict` or `ConfigDict`
+                    for arg_name, arg in zip(stmt.rvalue.arg_names, stmt.rvalue.args):
+                        if arg_name is None:
+                            continue
+                        config.update(self.get_config_update(arg_name, arg, lax_extra=True))
+                elif isinstance(stmt.rvalue, DictExpr):  # dict literals
+                    for key_expr, value_expr in stmt.rvalue.items:
+                        if not isinstance(key_expr, StrExpr):
+                            continue
+                        config.update(self.get_config_update(key_expr.value, value_expr))
+
+            elif isinstance(stmt, ClassDef):
+                if stmt.name != 'Config':  # 'deprecated' Config-class
+                    continue
+                for substmt in stmt.defs.body:
+                    if not isinstance(substmt, AssignmentStmt):
+                        continue
+                    lhs = substmt.lvalues[0]
+                    if not isinstance(lhs, NameExpr):
+                        continue
+                    config.update(self.get_config_update(lhs.name, substmt.rvalue))
+
+            if has_config_kwargs:
+                self._api.fail(
+                    'Specifying config in two places is ambiguous, use either Config attribute or class kwargs',
+                    cls,
+                )
+                break
+
+            has_config_from_namespace = True
+
+        if has_config_kwargs or has_config_from_namespace:
+            if (
+                stmt
+                and config.has_alias_generator
+                and not config.populate_by_name
+                and self.plugin_config.warn_required_dynamic_aliases
+            ):
+                error_required_dynamic_aliases(self._api, stmt)
+
+        for info in cls.info.mro[1:]:  # 0 is the current class
+            if METADATA_KEY not in info.metadata:
+                continue
+
+            # Each class depends on the set of fields in its ancestors
+            self._api.add_plugin_dependency(make_wildcard_trigger(info.fullname))
+            for name, value in info.metadata[METADATA_KEY]['config'].items():
+                config.setdefault(name, value)
+        return config
+
+    def collect_fields_and_class_vars(
+        self, model_config: ModelConfigData, is_root_model: bool
+    ) -> tuple[list[PydanticModelField] | None, list[PydanticModelClassVar] | None]:
+        """Collects the fields for the model, accounting for parent classes."""
+        cls = self._cls
+
+        # First, collect fields and ClassVars belonging to any class in the MRO, ignoring duplicates.
+        #
+        # We iterate through the MRO in reverse because attrs defined in the parent must appear
+        # earlier in the attributes list than attrs defined in the child. See:
+        # https://docs.python.org/3/library/dataclasses.html#inheritance
+        #
+        # However, we also want fields defined in the subtype to override ones defined
+        # in the parent. We can implement this via a dict without disrupting the attr order
+        # because dicts preserve insertion order in Python 3.7+.
+        found_fields: dict[str, PydanticModelField] = {}
+        found_class_vars: dict[str, PydanticModelClassVar] = {}
+        for info in reversed(cls.info.mro[1:-1]):  # 0 is the current class, -2 is BaseModel, -1 is object
+            # if BASEMODEL_METADATA_TAG_KEY in info.metadata and BASEMODEL_METADATA_KEY not in info.metadata:
+            #     # We haven't processed the base class yet. Need another pass.
+            #     return None, None
+            if METADATA_KEY not in info.metadata:
+                continue
+
+            # Each class depends on the set of attributes in its dataclass ancestors.
+            self._api.add_plugin_dependency(make_wildcard_trigger(info.fullname))
+
+            for name, data in info.metadata[METADATA_KEY]['fields'].items():
+                field = PydanticModelField.deserialize(info, data, self._api)
+                # (The following comment comes directly from the dataclasses plugin)
+                # TODO: We shouldn't be performing type operations during the main
+                #       semantic analysis pass, since some TypeInfo attributes might
+                #       still be in flux. This should be performed in a later phase.
+                field.expand_typevar_from_subtype(cls.info, self._api)
+                found_fields[name] = field
+
+                sym_node = cls.info.names.get(name)
+                if sym_node and sym_node.node and not isinstance(sym_node.node, Var):
+                    self._api.fail(
+                        'BaseModel field may only be overridden by another field',
+                        sym_node.node,
+                    )
+            # Collect ClassVars
+            for name, data in info.metadata[METADATA_KEY]['class_vars'].items():
+                found_class_vars[name] = PydanticModelClassVar.deserialize(data)
+
+        # Second, collect fields and ClassVars belonging to the current class.
+        current_field_names: set[str] = set()
+        current_class_vars_names: set[str] = set()
+        for stmt in self._get_assignment_statements_from_block(cls.defs):
+            maybe_field = self.collect_field_or_class_var_from_stmt(stmt, model_config, found_class_vars)
+            if maybe_field is None:
+                continue
+
+            lhs = stmt.lvalues[0]
+            assert isinstance(lhs, NameExpr)  # collect_field_or_class_var_from_stmt guarantees this
+            if isinstance(maybe_field, PydanticModelField):
+                if is_root_model and lhs.name != 'root':
+                    error_extra_fields_on_root_model(self._api, stmt)
+                else:
+                    current_field_names.add(lhs.name)
+                    found_fields[lhs.name] = maybe_field
+            elif isinstance(maybe_field, PydanticModelClassVar):
+                current_class_vars_names.add(lhs.name)
+                found_class_vars[lhs.name] = maybe_field
+
+        return list(found_fields.values()), list(found_class_vars.values())
+
+    def _get_assignment_statements_from_if_statement(self, stmt: IfStmt) -> Iterator[AssignmentStmt]:
+        for body in stmt.body:
+            if not body.is_unreachable:
+                yield from self._get_assignment_statements_from_block(body)
+        if stmt.else_body is not None and not stmt.else_body.is_unreachable:
+            yield from self._get_assignment_statements_from_block(stmt.else_body)
+
+    def _get_assignment_statements_from_block(self, block: Block) -> Iterator[AssignmentStmt]:
+        for stmt in block.body:
+            if isinstance(stmt, AssignmentStmt):
+                yield stmt
+            elif isinstance(stmt, IfStmt):
+                yield from self._get_assignment_statements_from_if_statement(stmt)
+
+    def collect_field_or_class_var_from_stmt(  # noqa C901
+        self, stmt: AssignmentStmt, model_config: ModelConfigData, class_vars: dict[str, PydanticModelClassVar]
+    ) -> PydanticModelField | PydanticModelClassVar | None:
+        """Get pydantic model field from statement.
+
+        Args:
+            stmt: The statement.
+            model_config: Configuration settings for the model.
+            class_vars: ClassVars already known to be defined on the model.
+
+        Returns:
+            A pydantic model field if it could find the field in statement. Otherwise, `None`.
+        """
+        cls = self._cls
+
+        lhs = stmt.lvalues[0]
+        if not isinstance(lhs, NameExpr) or not _fields.is_valid_field_name(lhs.name) or lhs.name == 'model_config':
+            return None
+
+        if not stmt.new_syntax:
+            if (
+                isinstance(stmt.rvalue, CallExpr)
+                and isinstance(stmt.rvalue.callee, CallExpr)
+                and isinstance(stmt.rvalue.callee.callee, NameExpr)
+                and stmt.rvalue.callee.callee.fullname in DECORATOR_FULLNAMES
+            ):
+                # This is a (possibly-reused) validator or serializer, not a field
+                # In particular, it looks something like: my_validator = validator('my_field')(f)
+                # Eventually, we may want to attempt to respect model_config['ignored_types']
+                return None
+
+            if lhs.name in class_vars:
+                # Class vars are not fields and are not required to be annotated
+                return None
+
+            # The assignment does not have an annotation, and it's not anything else we recognize
+            error_untyped_fields(self._api, stmt)
+            return None
+
+        lhs = stmt.lvalues[0]
+        if not isinstance(lhs, NameExpr):
+            return None
+
+        if not _fields.is_valid_field_name(lhs.name) or lhs.name == 'model_config':
+            return None
+
+        sym = cls.info.names.get(lhs.name)
+        if sym is None:  # pragma: no cover
+            # This is likely due to a star import (see the dataclasses plugin for a more detailed explanation)
+            # This is the same logic used in the dataclasses plugin
+            return None
+
+        node = sym.node
+        if isinstance(node, PlaceholderNode):  # pragma: no cover
+            # See the PlaceholderNode docstring for more detail about how this can occur
+            # Basically, it is an edge case when dealing with complex import logic
+
+            # The dataclasses plugin now asserts this cannot happen, but I'd rather not error if it does..
+            return None
+
+        if isinstance(node, TypeAlias):
+            self._api.fail(
+                'Type aliases inside BaseModel definitions are not supported at runtime',
+                node,
+            )
+            # Skip processing this node. This doesn't match the runtime behaviour,
+            # but the only alternative would be to modify the SymbolTable,
+            # and it's a little hairy to do that in a plugin.
+            return None
+
+        if not isinstance(node, Var):  # pragma: no cover
+            # Don't know if this edge case still happens with the `is_valid_field` check above
+            # but better safe than sorry
+
+            # The dataclasses plugin now asserts this cannot happen, but I'd rather not error if it does..
+            return None
+
+        # x: ClassVar[int] is not a field
+        if node.is_classvar:
+            return PydanticModelClassVar(lhs.name)
+
+        # x: InitVar[int] is not supported in BaseModel
+        node_type = get_proper_type(node.type)
+        if isinstance(node_type, Instance) and node_type.type.fullname == 'dataclasses.InitVar':
+            self._api.fail(
+                'InitVar is not supported in BaseModel',
+                node,
+            )
+
+        has_default = self.get_has_default(stmt)
+        strict = self.get_strict(stmt)
+
+        if sym.type is None and node.is_final and node.is_inferred:
+            # This follows the logic from the dataclasses plugin. The following comment is taken verbatim:
+            #
+            # This is a special case, assignment like x: Final = 42 is classified
+            # annotated above, but mypy strips the `Final` turning it into x = 42.
+            # We do not support inferred types in dataclasses, so we can try inferring
+            # type for simple literals, and otherwise require an explicit type
+            # argument for Final[...].
+            typ = self._api.analyze_simple_literal_type(stmt.rvalue, is_final=True)
+            if typ:
+                node.type = typ
+            else:
+                self._api.fail(
+                    'Need type argument for Final[...] with non-literal default in BaseModel',
+                    stmt,
+                )
+                node.type = AnyType(TypeOfAny.from_error)
+
+        alias, has_dynamic_alias = self.get_alias_info(stmt)
+        if has_dynamic_alias and not model_config.populate_by_name and self.plugin_config.warn_required_dynamic_aliases:
+            error_required_dynamic_aliases(self._api, stmt)
+        is_frozen = self.is_field_frozen(stmt)
+
+        init_type = self._infer_dataclass_attr_init_type(sym, lhs.name, stmt)
+        return PydanticModelField(
+            name=lhs.name,
+            has_dynamic_alias=has_dynamic_alias,
+            has_default=has_default,
+            strict=strict,
+            alias=alias,
+            is_frozen=is_frozen,
+            line=stmt.line,
+            column=stmt.column,
+            type=init_type,
+            info=cls.info,
+        )
+
+    def _infer_dataclass_attr_init_type(self, sym: SymbolTableNode, name: str, context: Context) -> Type | None:
+        """Infer __init__ argument type for an attribute.
+
+        In particular, possibly use the signature of __set__.
+        """
+        default = sym.type
+        if sym.implicit:
+            return default
+        t = get_proper_type(sym.type)
+
+        # Perform a simple-minded inference from the signature of __set__, if present.
+        # We can't use mypy.checkmember here, since this plugin runs before type checking.
+        # We only support some basic scanerios here, which is hopefully sufficient for
+        # the vast majority of use cases.
+        if not isinstance(t, Instance):
+            return default
+        setter = t.type.get('__set__')
+        if setter:
+            if isinstance(setter.node, FuncDef):
+                super_info = t.type.get_containing_type_info('__set__')
+                assert super_info
+                if setter.type:
+                    setter_type = get_proper_type(map_type_from_supertype(setter.type, t.type, super_info))
+                else:
+                    return AnyType(TypeOfAny.unannotated)
+                if isinstance(setter_type, CallableType) and setter_type.arg_kinds == [
+                    ARG_POS,
+                    ARG_POS,
+                    ARG_POS,
+                ]:
+                    return expand_type_by_instance(setter_type.arg_types[2], t)
+                else:
+                    self._api.fail(f'Unsupported signature for "__set__" in "{t.type.name}"', context)
+            else:
+                self._api.fail(f'Unsupported "__set__" in "{t.type.name}"', context)
+
+        return default
+
+    def add_initializer(
+        self, fields: list[PydanticModelField], config: ModelConfigData, is_settings: bool, is_root_model: bool
+    ) -> None:
+        """Adds a fields-aware `__init__` method to the class.
+
+        The added `__init__` will be annotated with types vs. all `Any` depending on the plugin settings.
+        """
+        if '__init__' in self._cls.info.names and not self._cls.info.names['__init__'].plugin_generated:
+            return  # Don't generate an __init__ if one already exists
+
+        typed = self.plugin_config.init_typed
+        model_strict = bool(config.strict)
+        use_alias = config.populate_by_name is not True
+        requires_dynamic_aliases = bool(config.has_alias_generator and not config.populate_by_name)
+        args = self.get_field_arguments(
+            fields,
+            typed=typed,
+            model_strict=model_strict,
+            requires_dynamic_aliases=requires_dynamic_aliases,
+            use_alias=use_alias,
+            is_settings=is_settings,
+            is_root_model=is_root_model,
+            force_typevars_invariant=True,
+        )
+
+        if is_settings:
+            base_settings_node = self._api.lookup_fully_qualified(BASESETTINGS_FULLNAME).node
+            assert isinstance(base_settings_node, TypeInfo)
+            if '__init__' in base_settings_node.names:
+                base_settings_init_node = base_settings_node.names['__init__'].node
+                assert isinstance(base_settings_init_node, FuncDef)
+                if base_settings_init_node is not None and base_settings_init_node.type is not None:
+                    func_type = base_settings_init_node.type
+                    assert isinstance(func_type, CallableType)
+                    for arg_idx, arg_name in enumerate(func_type.arg_names):
+                        if arg_name is None or arg_name.startswith('__') or not arg_name.startswith('_'):
+                            continue
+                        analyzed_variable_type = self._api.anal_type(func_type.arg_types[arg_idx])
+                        variable = Var(arg_name, analyzed_variable_type)
+                        args.append(Argument(variable, analyzed_variable_type, None, ARG_OPT))
+
+        if not self.should_init_forbid_extra(fields, config):
+            var = Var('kwargs')
+            args.append(Argument(var, AnyType(TypeOfAny.explicit), None, ARG_STAR2))
+
+        add_method(self._api, self._cls, '__init__', args=args, return_type=NoneType())
+
+    def add_model_construct_method(
+        self,
+        fields: list[PydanticModelField],
+        config: ModelConfigData,
+        is_settings: bool,
+        is_root_model: bool,
+    ) -> None:
+        """Adds a fully typed `model_construct` classmethod to the class.
+
+        Similar to the fields-aware __init__ method, but always uses the field names (not aliases),
+        and does not treat settings fields as optional.
+        """
+        set_str = self._api.named_type(f'{BUILTINS_NAME}.set', [self._api.named_type(f'{BUILTINS_NAME}.str')])
+        optional_set_str = UnionType([set_str, NoneType()])
+        fields_set_argument = Argument(Var('_fields_set', optional_set_str), optional_set_str, None, ARG_OPT)
+        with state.strict_optional_set(self._api.options.strict_optional):
+            args = self.get_field_arguments(
+                fields,
+                typed=True,
+                model_strict=bool(config.strict),
+                requires_dynamic_aliases=False,
+                use_alias=False,
+                is_settings=is_settings,
+                is_root_model=is_root_model,
+            )
+        if not self.should_init_forbid_extra(fields, config):
+            var = Var('kwargs')
+            args.append(Argument(var, AnyType(TypeOfAny.explicit), None, ARG_STAR2))
+
+        args = args + [fields_set_argument] if is_root_model else [fields_set_argument] + args
+
+        add_method(
+            self._api,
+            self._cls,
+            'model_construct',
+            args=args,
+            return_type=fill_typevars(self._cls.info),
+            is_classmethod=True,
+        )
+
+    def set_frozen(self, fields: list[PydanticModelField], api: SemanticAnalyzerPluginInterface, frozen: bool) -> None:
+        """Marks all fields as properties so that attempts to set them trigger mypy errors.
+
+        This is the same approach used by the attrs and dataclasses plugins.
+        """
+        info = self._cls.info
+        for field in fields:
+            sym_node = info.names.get(field.name)
+            if sym_node is not None:
+                var = sym_node.node
+                if isinstance(var, Var):
+                    var.is_property = frozen or field.is_frozen
+                elif isinstance(var, PlaceholderNode) and not self._api.final_iteration:
+                    # See https://github.com/pydantic/pydantic/issues/5191 to hit this branch for test coverage
+                    self._api.defer()
+                else:  # pragma: no cover
+                    # I don't know whether it's possible to hit this branch, but I've added it for safety
+                    try:
+                        var_str = str(var)
+                    except TypeError:
+                        # This happens for PlaceholderNode; perhaps it will happen for other types in the future..
+                        var_str = repr(var)
+                    detail = f'sym_node.node: {var_str} (of type {var.__class__})'
+                    error_unexpected_behavior(detail, self._api, self._cls)
+            else:
+                var = field.to_var(info, api, use_alias=False)
+                var.info = info
+                var.is_property = frozen
+                var._fullname = info.fullname + '.' + var.name
+                info.names[var.name] = SymbolTableNode(MDEF, var)
+
+    def get_config_update(self, name: str, arg: Expression, lax_extra: bool = False) -> ModelConfigData | None:
+        """Determines the config update due to a single kwarg in the ConfigDict definition.
+
+        Warns if a tracked config attribute is set to a value the plugin doesn't know how to interpret (e.g., an int)
+        """
+        if name not in self.tracked_config_fields:
+            return None
+        if name == 'extra':
+            if isinstance(arg, StrExpr):
+                forbid_extra = arg.value == 'forbid'
+            elif isinstance(arg, MemberExpr):
+                forbid_extra = arg.name == 'forbid'
+            else:
+                if not lax_extra:
+                    # Only emit an error for other types of `arg` (e.g., `NameExpr`, `ConditionalExpr`, etc.) when
+                    # reading from a config class, etc. If a ConfigDict is used, then we don't want to emit an error
+                    # because you'll get type checking from the ConfigDict itself.
+                    #
+                    # It would be nice if we could introspect the types better otherwise, but I don't know what the API
+                    # is to evaluate an expr into its type and then check if that type is compatible with the expected
+                    # type. Note that you can still get proper type checking via: `model_config = ConfigDict(...)`, just
+                    # if you don't use an explicit string, the plugin won't be able to infer whether extra is forbidden.
+                    error_invalid_config_value(name, self._api, arg)
+                return None
+            return ModelConfigData(forbid_extra=forbid_extra)
+        if name == 'alias_generator':
+            has_alias_generator = True
+            if isinstance(arg, NameExpr) and arg.fullname == 'builtins.None':
+                has_alias_generator = False
+            return ModelConfigData(has_alias_generator=has_alias_generator)
+        if isinstance(arg, NameExpr) and arg.fullname in ('builtins.True', 'builtins.False'):
+            return ModelConfigData(**{name: arg.fullname == 'builtins.True'})
+        error_invalid_config_value(name, self._api, arg)
+        return None
+
+    @staticmethod
+    def get_has_default(stmt: AssignmentStmt) -> bool:
+        """Returns a boolean indicating whether the field defined in `stmt` is a required field."""
+        expr = stmt.rvalue
+        if isinstance(expr, TempNode):
+            # TempNode means annotation-only, so has no default
+            return False
+        if isinstance(expr, CallExpr) and isinstance(expr.callee, RefExpr) and expr.callee.fullname == FIELD_FULLNAME:
+            # The "default value" is a call to `Field`; at this point, the field has a default if and only if:
+            # * there is a positional argument that is not `...`
+            # * there is a keyword argument named "default" that is not `...`
+            # * there is a "default_factory" that is not `None`
+            for arg, name in zip(expr.args, expr.arg_names):
+                # If name is None, then this arg is the default because it is the only positional argument.
+                if name is None or name == 'default':
+                    return arg.__class__ is not EllipsisExpr
+                if name == 'default_factory':
+                    return not (isinstance(arg, NameExpr) and arg.fullname == 'builtins.None')
+            return False
+        # Has no default if the "default value" is Ellipsis (i.e., `field_name: Annotation = ...`)
+        return not isinstance(expr, EllipsisExpr)
+
+    @staticmethod
+    def get_strict(stmt: AssignmentStmt) -> bool | None:
+        """Returns a the `strict` value of a field if defined, otherwise `None`."""
+        expr = stmt.rvalue
+        if isinstance(expr, CallExpr) and isinstance(expr.callee, RefExpr) and expr.callee.fullname == FIELD_FULLNAME:
+            for arg, name in zip(expr.args, expr.arg_names):
+                if name != 'strict':
+                    continue
+                if isinstance(arg, NameExpr):
+                    if arg.fullname == 'builtins.True':
+                        return True
+                    elif arg.fullname == 'builtins.False':
+                        return False
+                return None
+        return None
+
+    @staticmethod
+    def get_alias_info(stmt: AssignmentStmt) -> tuple[str | None, bool]:
+        """Returns a pair (alias, has_dynamic_alias), extracted from the declaration of the field defined in `stmt`.
+
+        `has_dynamic_alias` is True if and only if an alias is provided, but not as a string literal.
+        If `has_dynamic_alias` is True, `alias` will be None.
+        """
+        expr = stmt.rvalue
+        if isinstance(expr, TempNode):
+            # TempNode means annotation-only
+            return None, False
+
+        if not (
+            isinstance(expr, CallExpr) and isinstance(expr.callee, RefExpr) and expr.callee.fullname == FIELD_FULLNAME
+        ):
+            # Assigned value is not a call to pydantic.fields.Field
+            return None, False
+
+        for i, arg_name in enumerate(expr.arg_names):
+            if arg_name != 'alias':
+                continue
+            arg = expr.args[i]
+            if isinstance(arg, StrExpr):
+                return arg.value, False
+            else:
+                return None, True
+        return None, False
+
+    @staticmethod
+    def is_field_frozen(stmt: AssignmentStmt) -> bool:
+        """Returns whether the field is frozen, extracted from the declaration of the field defined in `stmt`.
+
+        Note that this is only whether the field was declared to be frozen in a `<field_name> = Field(frozen=True)`
+        sense; this does not determine whether the field is frozen because the entire model is frozen; that is
+        handled separately.
+        """
+        expr = stmt.rvalue
+        if isinstance(expr, TempNode):
+            # TempNode means annotation-only
+            return False
+
+        if not (
+            isinstance(expr, CallExpr) and isinstance(expr.callee, RefExpr) and expr.callee.fullname == FIELD_FULLNAME
+        ):
+            # Assigned value is not a call to pydantic.fields.Field
+            return False
+
+        for i, arg_name in enumerate(expr.arg_names):
+            if arg_name == 'frozen':
+                arg = expr.args[i]
+                return isinstance(arg, NameExpr) and arg.fullname == 'builtins.True'
+        return False
+
+    def get_field_arguments(
+        self,
+        fields: list[PydanticModelField],
+        typed: bool,
+        model_strict: bool,
+        use_alias: bool,
+        requires_dynamic_aliases: bool,
+        is_settings: bool,
+        is_root_model: bool,
+        force_typevars_invariant: bool = False,
+    ) -> list[Argument]:
+        """Helper function used during the construction of the `__init__` and `model_construct` method signatures.
+
+        Returns a list of mypy Argument instances for use in the generated signatures.
+        """
+        info = self._cls.info
+        arguments = [
+            field.to_argument(
+                info,
+                typed=typed,
+                model_strict=model_strict,
+                force_optional=requires_dynamic_aliases or is_settings,
+                use_alias=use_alias,
+                api=self._api,
+                force_typevars_invariant=force_typevars_invariant,
+                is_root_model_root=is_root_model and field.name == 'root',
+            )
+            for field in fields
+            if not (use_alias and field.has_dynamic_alias)
+        ]
+        return arguments
+
+    def should_init_forbid_extra(self, fields: list[PydanticModelField], config: ModelConfigData) -> bool:
+        """Indicates whether the generated `__init__` should get a `**kwargs` at the end of its signature.
+
+        We disallow arbitrary kwargs if the extra config setting is "forbid", or if the plugin config says to,
+        *unless* a required dynamic alias is present (since then we can't determine a valid signature).
+        """
+        if not config.populate_by_name:
+            if self.is_dynamic_alias_present(fields, bool(config.has_alias_generator)):
+                return False
+        if config.forbid_extra:
+            return True
+        return self.plugin_config.init_forbid_extra
+
+    @staticmethod
+    def is_dynamic_alias_present(fields: list[PydanticModelField], has_alias_generator: bool) -> bool:
+        """Returns whether any fields on the model have a "dynamic alias", i.e., an alias that cannot be
+        determined during static analysis.
+        """
+        for field in fields:
+            if field.has_dynamic_alias:
+                return True
+        if has_alias_generator:
+            for field in fields:
+                if field.alias is None:
+                    return True
+        return False
+
+
+class ModelConfigData:
+    """Pydantic mypy plugin model config class."""
+
+    def __init__(
+        self,
+        forbid_extra: bool | None = None,
+        frozen: bool | None = None,
+        from_attributes: bool | None = None,
+        populate_by_name: bool | None = None,
+        has_alias_generator: bool | None = None,
+        strict: bool | None = None,
+    ):
+        self.forbid_extra = forbid_extra
+        self.frozen = frozen
+        self.from_attributes = from_attributes
+        self.populate_by_name = populate_by_name
+        self.has_alias_generator = has_alias_generator
+        self.strict = strict
+
+    def get_values_dict(self) -> dict[str, Any]:
+        """Returns a dict of Pydantic model config names to their values.
+
+        It includes the config if config value is not `None`.
+        """
+        return {k: v for k, v in self.__dict__.items() if v is not None}
+
+    def update(self, config: ModelConfigData | None) -> None:
+        """Update Pydantic model config values."""
+        if config is None:
+            return
+        for k, v in config.get_values_dict().items():
+            setattr(self, k, v)
+
+    def setdefault(self, key: str, value: Any) -> None:
+        """Set default value for Pydantic model config if config value is `None`."""
+        if getattr(self, key) is None:
+            setattr(self, key, value)
+
+
+ERROR_ORM = ErrorCode('pydantic-orm', 'Invalid from_attributes call', 'Pydantic')
+ERROR_CONFIG = ErrorCode('pydantic-config', 'Invalid config value', 'Pydantic')
+ERROR_ALIAS = ErrorCode('pydantic-alias', 'Dynamic alias disallowed', 'Pydantic')
+ERROR_UNEXPECTED = ErrorCode('pydantic-unexpected', 'Unexpected behavior', 'Pydantic')
+ERROR_UNTYPED = ErrorCode('pydantic-field', 'Untyped field disallowed', 'Pydantic')
+ERROR_FIELD_DEFAULTS = ErrorCode('pydantic-field', 'Invalid Field defaults', 'Pydantic')
+ERROR_EXTRA_FIELD_ROOT_MODEL = ErrorCode('pydantic-field', 'Extra field on RootModel subclass', 'Pydantic')
+
+
+def error_from_attributes(model_name: str, api: CheckerPluginInterface, context: Context) -> None:
+    """Emits an error when the model does not have `from_attributes=True`."""
+    api.fail(f'"{model_name}" does not have from_attributes=True', context, code=ERROR_ORM)
+
+
+def error_invalid_config_value(name: str, api: SemanticAnalyzerPluginInterface, context: Context) -> None:
+    """Emits an error when the config value is invalid."""
+    api.fail(f'Invalid value for "Config.{name}"', context, code=ERROR_CONFIG)
+
+
+def error_required_dynamic_aliases(api: SemanticAnalyzerPluginInterface, context: Context) -> None:
+    """Emits required dynamic aliases error.
+
+    This will be called when `warn_required_dynamic_aliases=True`.
+    """
+    api.fail('Required dynamic aliases disallowed', context, code=ERROR_ALIAS)
+
+
+def error_unexpected_behavior(
+    detail: str, api: CheckerPluginInterface | SemanticAnalyzerPluginInterface, context: Context
+) -> None:  # pragma: no cover
+    """Emits unexpected behavior error."""
+    # Can't think of a good way to test this, but I confirmed it renders as desired by adding to a non-error path
+    link = 'https://github.com/pydantic/pydantic/issues/new/choose'
+    full_message = f'The pydantic mypy plugin ran into unexpected behavior: {detail}\n'
+    full_message += f'Please consider reporting this bug at {link} so we can try to fix it!'
+    api.fail(full_message, context, code=ERROR_UNEXPECTED)
+
+
+def error_untyped_fields(api: SemanticAnalyzerPluginInterface, context: Context) -> None:
+    """Emits an error when there is an untyped field in the model."""
+    api.fail('Untyped fields disallowed', context, code=ERROR_UNTYPED)
+
+
+def error_extra_fields_on_root_model(api: CheckerPluginInterface, context: Context) -> None:
+    """Emits an error when there is more than just a root field defined for a subclass of RootModel."""
+    api.fail('Only `root` is allowed as a field of a `RootModel`', context, code=ERROR_EXTRA_FIELD_ROOT_MODEL)
+
+
+def add_method(
+    api: SemanticAnalyzerPluginInterface | CheckerPluginInterface,
+    cls: ClassDef,
+    name: str,
+    args: list[Argument],
+    return_type: Type,
+    self_type: Type | None = None,
+    tvar_def: TypeVarType | None = None,
+    is_classmethod: bool = False,
+) -> None:
+    """Very closely related to `mypy.plugins.common.add_method_to_class`, with a few pydantic-specific changes."""
+    info = cls.info
+
+    # First remove any previously generated methods with the same name
+    # to avoid clashes and problems in the semantic analyzer.
+    if name in info.names:
+        sym = info.names[name]
+        if sym.plugin_generated and isinstance(sym.node, FuncDef):
+            cls.defs.body.remove(sym.node)  # pragma: no cover
+
+    if isinstance(api, SemanticAnalyzerPluginInterface):
+        function_type = api.named_type('builtins.function')
+    else:
+        function_type = api.named_generic_type('builtins.function', [])
+
+    if is_classmethod:
+        self_type = self_type or TypeType(fill_typevars(info))
+        first = [Argument(Var('_cls'), self_type, None, ARG_POS, True)]
+    else:
+        self_type = self_type or fill_typevars(info)
+        # `self` is positional *ONLY* here, but this can't be expressed
+        # fully in the mypy internal API. ARG_POS is the closest we can get.
+        # Using ARG_POS will, however, give mypy errors if a `self` field
+        # is present on a model:
+        #
+        #     Name "self" already defined (possibly by an import)  [no-redef]
+        #
+        # As a workaround, we give this argument a name that will
+        # never conflict. By its positional nature, this name will not
+        # be used or exposed to users.
+        first = [Argument(Var('__pydantic_self__'), self_type, None, ARG_POS)]
+    args = first + args
+
+    arg_types, arg_names, arg_kinds = [], [], []
+    for arg in args:
+        assert arg.type_annotation, 'All arguments must be fully typed.'
+        arg_types.append(arg.type_annotation)
+        arg_names.append(arg.variable.name)
+        arg_kinds.append(arg.kind)
+
+    signature = CallableType(arg_types, arg_kinds, arg_names, return_type, function_type)
+    if tvar_def:
+        signature.variables = [tvar_def]
+
+    func = FuncDef(name, args, Block([PassStmt()]))
+    func.info = info
+    func.type = set_callable_name(signature, func)
+    func.is_class = is_classmethod
+    func._fullname = info.fullname + '.' + name
+    func.line = info.line
+
+    # NOTE: we would like the plugin generated node to dominate, but we still
+    # need to keep any existing definitions so they get semantically analyzed.
+    if name in info.names:
+        # Get a nice unique name instead.
+        r_name = get_unique_redefinition_name(name, info.names)
+        info.names[r_name] = info.names[name]
+
+    # Add decorator for is_classmethod
+    # The dataclasses plugin claims this is unnecessary for classmethods, but not including it results in a
+    # signature incompatible with the superclass, which causes mypy errors to occur for every subclass of BaseModel.
+    if is_classmethod:
+        func.is_decorated = True
+        v = Var(name, func.type)
+        v.info = info
+        v._fullname = func._fullname
+        v.is_classmethod = True
+        dec = Decorator(func, [NameExpr('classmethod')], v)
+        dec.line = info.line
+        sym = SymbolTableNode(MDEF, dec)
+    else:
+        sym = SymbolTableNode(MDEF, func)
+    sym.plugin_generated = True
+    info.names[name] = sym
+
+    info.defn.defs.body.append(func)
+
+
+def parse_toml(config_file: str) -> dict[str, Any] | None:
+    """Returns a dict of config keys to values.
+
+    It reads configs from toml file and returns `None` if the file is not a toml file.
+    """
+    if not config_file.endswith('.toml'):
+        return None
+
+    if sys.version_info >= (3, 11):
+        import tomllib as toml_
+    else:
+        try:
+            import tomli as toml_
+        except ImportError:  # pragma: no cover
+            import warnings
+
+            warnings.warn('No TOML parser installed, cannot read configuration from `pyproject.toml`.')
+            return None
+
+    with open(config_file, 'rb') as rf:
+        return toml_.load(rf)

infer_4_37_2/lib/python3.10/site-packages/pydantic/parse.py

@@ -0,0 +1,5 @@
+"""The `parse` module is a backport module from V1."""
+
+from ._migration import getattr_migration
+
+__getattr__ = getattr_migration(__name__)

infer_4_37_2/lib/python3.10/site-packages/pydantic/validators.py

@@ -0,0 +1,5 @@
+"""The `validators` module is a backport module from V1."""
+
+from ._migration import getattr_migration
+
+__getattr__ = getattr_migration(__name__)