import functools
import importlib.util
import re
import sys
import typing
from abc import ABC, abstractmethod
from collections.abc import Hashable, Sequence
from decimal import Decimal
from enum import Enum, auto
from typing import (
    Annotated,
    Any,
    Callable,
    ForwardRef,
    Generic,
    Literal,
    Optional,
    TypeVar,
    Union,
)

import pytest
from dirty_equals import HasRepr, IsStr
from pydantic_core import (
    CoreSchema,
    ErrorDetails,
    InitErrorDetails,
    PydanticSerializationError,
    PydanticUndefined,
    core_schema,
)
from typing_extensions import Self, TypeAliasType, TypedDict, get_args

from pydantic import (
    AfterValidator,
    BaseModel,
    ConfigDict,
    GetCoreSchemaHandler,
    PrivateAttr,
    PydanticDeprecatedSince20,
    PydanticSchemaGenerationError,
    PydanticUndefinedAnnotation,
    PydanticUserError,
    RootModel,
    TypeAdapter,
    ValidationError,
    constr,
    errors,
    field_validator,
    model_validator,
    root_validator,
    validator,
)
from pydantic._internal._model_construction import ModelMetaclass
from pydantic.fields import Field, computed_field
from pydantic.functional_serializers import (
    field_serializer,
    model_serializer,
)


def test_str_bytes():
    class Model(BaseModel):
        v: Union[str, bytes]

    m = Model(v='s')
    assert m.v == 's'
    assert repr(Model.model_fields['v']) == 'FieldInfo(annotation=Union[str, bytes], required=True)'

    m = Model(v=b'b')
    assert m.v == b'b'

    with pytest.raises(ValidationError) as exc_info:
        Model(v=None)
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {'type': 'string_type', 'loc': ('v', 'str'), 'msg': 'Input should be a valid string', 'input': None},
        {'type': 'bytes_type', 'loc': ('v', 'bytes'), 'msg': 'Input should be a valid bytes', 'input': None},
    ]


def test_str_bytes_none():
    class Model(BaseModel):
        v: Union[None, str, bytes] = ...

    m = Model(v='s')
    assert m.v == 's'

    m = Model(v=b'b')
    assert m.v == b'b'

    m = Model(v=None)
    assert m.v is None


def test_union_int_str():
    class Model(BaseModel):
        v: Union[int, str] = ...

    m = Model(v=123)
    assert m.v == 123

    m = Model(v='123')
    assert m.v == '123'

    m = Model(v=b'foobar')
    assert m.v == 'foobar'

    m = Model(v=12.0)
    assert m.v == 12

    with pytest.raises(ValidationError) as exc_info:
        Model(v=None)
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {'type': 'int_type', 'loc': ('v', 'int'), 'msg': 'Input should be a valid integer', 'input': None},
        {
            'type': 'string_type',
            'loc': ('v', 'str'),
            'msg': 'Input should be a valid string',
            'input': None,
        },
    ]


def test_union_int_any():
    class Model(BaseModel):
        v: Union[int, Any]

    m = Model(v=123)
    assert m.v == 123

    m = Model(v='123')
    assert m.v == '123'

    m = Model(v='foobar')
    assert m.v == 'foobar'

    m = Model(v=None)
    assert m.v is None


def test_typed_list():
    class Model(BaseModel):
        v: list[int] = ...

    m = Model(v=[1, 2, '3'])
    assert m.v == [1, 2, 3]

    with pytest.raises(ValidationError) as exc_info:
        Model(v=[1, 'x', 'y'])
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing',
            'loc': ('v', 1),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'x',
        },
        {
            'type': 'int_parsing',
            'loc': ('v', 2),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'y',
        },
    ]

    with pytest.raises(ValidationError) as exc_info:
        Model(v=1)
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {'type': 'list_type', 'loc': ('v',), 'msg': 'Input should be a valid list', 'input': 1}
    ]


def test_typed_set():
    class Model(BaseModel):
        v: set[int] = ...

    assert Model(v={1, 2, '3'}).v == {1, 2, 3}
    assert Model(v=[1, 2, '3']).v == {1, 2, 3}

    with pytest.raises(ValidationError) as exc_info:
        Model(v=[1, 'x'])
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing',
            'loc': ('v', 1),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'x',
        }
    ]


def test_dict_dict():
    class Model(BaseModel):
        v: dict[str, int] = ...

    assert Model(v={'foo': 1}).model_dump() == {'v': {'foo': 1}}


def test_none_list():
    class Model(BaseModel):
        v: list[None] = [None]

    assert Model.model_json_schema() == {
        'title': 'Model',
        'type': 'object',
        'properties': {'v': {'title': 'V', 'default': [None], 'type': 'array', 'items': {'type': 'null'}}},
    }


@pytest.mark.parametrize(
    'value,result',
    [
        ({'a': 2, 'b': 4}, {'a': 2, 'b': 4}),
        ({b'a': '2', 'b': 4}, {'a': 2, 'b': 4}),
        # ([('a', 2), ('b', 4)], {'a': 2, 'b': 4}),
    ],
)
def test_typed_dict(value, result):
    class Model(BaseModel):
        v: dict[str, int] = ...

    assert Model(v=value).v == result


@pytest.mark.parametrize(
    'value,errors',
    [
        (1, [{'type': 'dict_type', 'loc': ('v',), 'msg': 'Input should be a valid dictionary', 'input': 1}]),
        (
            {'a': 'b'},
            [
                {
                    'type': 'int_parsing',
                    'loc': ('v', 'a'),
                    'msg': 'Input should be a valid integer, unable to parse string as an integer',
                    'input': 'b',
                }
            ],
        ),
        (
            [1, 2, 3],
            [{'type': 'dict_type', 'loc': ('v',), 'msg': 'Input should be a valid dictionary', 'input': [1, 2, 3]}],
        ),
    ],
)
def test_typed_dict_error(value, errors):
    class Model(BaseModel):
        v: dict[str, int] = ...

    with pytest.raises(ValidationError) as exc_info:
        Model(v=value)
    assert exc_info.value.errors(include_url=False) == errors


def test_dict_key_error():
    class Model(BaseModel):
        v: dict[int, int] = ...

    assert Model(v={1: 2, '3': '4'}).v == {1: 2, 3: 4}

    with pytest.raises(ValidationError) as exc_info:
        Model(v={'foo': 2, '3': '4'})
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing',
            'loc': ('v', 'foo', '[key]'),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'foo',
        }
    ]


def test_tuple():
    class Model(BaseModel):
        v: tuple[int, float, bool]

    m = Model(v=['1.0', '2.2', 'true'])
    assert m.v == (1, 2.2, True)


def test_tuple_more():
    class Model(BaseModel):
        empty_tuple: tuple[()]
        simple_tuple: tuple = None
        tuple_of_different_types: tuple[int, float, str, bool] = None
        tuple_of_single_tuples: tuple[tuple[int], ...] = ()

    m = Model(
        empty_tuple=[],
        simple_tuple=[1, 2, 3, 4],
        tuple_of_different_types=[4, 3.1, 'str', 1],
        tuple_of_single_tuples=(('1',), (2,)),
    )
    assert m.model_dump() == {
        'empty_tuple': (),
        'simple_tuple': (1, 2, 3, 4),
        'tuple_of_different_types': (4, 3.1, 'str', True),
        'tuple_of_single_tuples': ((1,), (2,)),
    }


@pytest.mark.parametrize(
    'dict_cls,frozenset_cls,list_cls,set_cls,tuple_cls,type_cls',
    [
        (typing.Dict, typing.FrozenSet, typing.List, typing.Set, typing.Tuple, typing.Type),  # noqa: UP006
        (dict, frozenset, list, set, tuple, type),
    ],
)
def test_pep585_generic_types(dict_cls, frozenset_cls, list_cls, set_cls, tuple_cls, type_cls):
    class Type1:
        pass

    class Type2:
        pass

    class Model(BaseModel, arbitrary_types_allowed=True):
        a: dict_cls
        a1: dict_cls[str, int]
        b: frozenset_cls
        b1: frozenset_cls[int]
        c: list_cls
        c1: list_cls[int]
        d: set_cls
        d1: set_cls[int]
        e: tuple_cls
        e1: tuple_cls[int]
        e2: tuple_cls[int, ...]
        e3: tuple_cls[()]
        f: type_cls
        f1: type_cls[Type1]

    default_model_kwargs = dict(
        a={},
        a1={'a': '1'},
        b=[],
        b1=('1',),
        c=[],
        c1=('1',),
        d=[],
        d1=['1'],
        e=[],
        e1=['1'],
        e2=['1', '2'],
        e3=[],
        f=Type1,
        f1=Type1,
    )

    m = Model(**default_model_kwargs)
    assert m.a == {}
    assert m.a1 == {'a': 1}
    assert m.b == frozenset()
    assert m.b1 == frozenset({1})
    assert m.c == []
    assert m.c1 == [1]
    assert m.d == set()
    assert m.d1 == {1}
    assert m.e == ()
    assert m.e1 == (1,)
    assert m.e2 == (1, 2)
    assert m.e3 == ()
    assert m.f == Type1
    assert m.f1 == Type1

    with pytest.raises(ValidationError) as exc_info:
        Model(**{**default_model_kwargs, 'e3': (1,)})
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'too_long',
            'loc': ('e3',),
            'msg': 'Tuple should have at most 0 items after validation, not 1',
            'input': (1,),
            'ctx': {'field_type': 'Tuple', 'max_length': 0, 'actual_length': 1},
        }
    ]

    Model(**{**default_model_kwargs, 'f': Type2})

    with pytest.raises(ValidationError) as exc_info:
        Model(**{**default_model_kwargs, 'f1': Type2})
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'is_subclass_of',
            'loc': ('f1',),
            'msg': 'Input should be a subclass of test_pep585_generic_types.<locals>.Type1',
            'input': HasRepr(IsStr(regex=r".+\.Type2'>")),
            'ctx': {'class': 'test_pep585_generic_types.<locals>.Type1'},
        }
    ]


def test_tuple_length_error():
    class Model(BaseModel):
        v: tuple[int, float, bool]
        w: tuple[()]

    with pytest.raises(ValidationError) as exc_info:
        Model(v=[1, 2], w=[1])
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {'type': 'missing', 'loc': ('v', 2), 'msg': 'Field required', 'input': [1, 2]},
        {
            'type': 'too_long',
            'loc': ('w',),
            'msg': 'Tuple should have at most 0 items after validation, not 1',
            'input': [1],
            'ctx': {'field_type': 'Tuple', 'max_length': 0, 'actual_length': 1},
        },
    ]


def test_tuple_invalid():
    class Model(BaseModel):
        v: tuple[int, float, bool]

    with pytest.raises(ValidationError) as exc_info:
        Model(v='xxx')
    assert exc_info.value.errors(include_url=False) == [
        {'type': 'tuple_type', 'loc': ('v',), 'msg': 'Input should be a valid tuple', 'input': 'xxx'}
    ]


def test_tuple_value_error():
    class Model(BaseModel):
        v: tuple[int, float, Decimal]

    with pytest.raises(ValidationError) as exc_info:
        Model(v=['x', 'y', 'x'])
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing',
            'loc': ('v', 0),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'x',
        },
        {
            'type': 'float_parsing',
            'loc': ('v', 1),
            'msg': 'Input should be a valid number, unable to parse string as a number',
            'input': 'y',
        },
        {
            'type': 'decimal_parsing',
            'loc': ('v', 2),
            'msg': 'Input should be a valid decimal',
            'input': 'x',
        },
    ]


def test_recursive_list():
    class SubModel(BaseModel):
        name: str = ...
        count: int = None

    class Model(BaseModel):
        v: list[SubModel] = []

    m = Model(v=[])
    assert m.v == []

    m = Model(v=[{'name': 'testing', 'count': 4}])
    assert repr(m) == "Model(v=[SubModel(name='testing', count=4)])"
    assert m.v[0].name == 'testing'
    assert m.v[0].count == 4
    assert m.model_dump() == {'v': [{'count': 4, 'name': 'testing'}]}

    with pytest.raises(ValidationError) as exc_info:
        Model(v=['x'])
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'model_type',
            'loc': ('v', 0),
            'msg': 'Input should be a valid dictionary or instance of SubModel',
            'input': 'x',
            'ctx': {'class_name': 'SubModel'},
        }
    ]


def test_recursive_list_error():
    class SubModel(BaseModel):
        name: str = ...
        count: int = None

    class Model(BaseModel):
        v: list[SubModel] = []

    with pytest.raises(ValidationError) as exc_info:
        Model(v=[{}])
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('v', 0, 'name'), 'msg': 'Field required', 'type': 'missing'}
    ]


def test_list_unions():
    class Model(BaseModel):
        v: list[Union[int, str]]

    assert Model(v=[123, '456', 'foobar']).v == [123, '456', 'foobar']

    with pytest.raises(ValidationError) as exc_info:
        Model(v=[1, 2, None])

    # the reason that we need to do an unordered list comparison here is that previous tests use Union[str, int]
    # and Python's cache makes it such that the above Model has `v` associated with a list[Union[str, int]] instead
    # of the expected list[Union[int, str]]
    # for more info, see  https://github.com/python/cpython/issues/103749 and
    # https://github.com/pydantic/pydantic/pull/10244#issuecomment-2312796647
    errors = exc_info.value.errors(include_url=False)
    expected_errors = [
        {'input': None, 'loc': ('v', 2, 'int'), 'msg': 'Input should be a valid integer', 'type': 'int_type'},
        {'input': None, 'loc': ('v', 2, 'str'), 'msg': 'Input should be a valid string', 'type': 'string_type'},
    ]
    assert sorted(errors, key=str) == sorted(expected_errors, key=str)


def test_recursive_lists():
    class Model(BaseModel):
        v: list[list[Union[int, float]]] = ...

    assert Model(v=[[1, 2], [3, '4', '4.1']]).v == [[1, 2], [3, 4, 4.1]]
    assert Model.model_fields['v'].annotation == list[list[Union[int, float]]]
    assert Model.model_fields['v'].is_required()


class StrEnum(str, Enum):
    a = 'a10'
    b = 'b10'


def test_str_enum():
    class Model(BaseModel):
        v: StrEnum = ...

    assert Model(v='a10').v is StrEnum.a

    with pytest.raises(ValidationError):
        Model(v='different')


def test_any_dict():
    class Model(BaseModel):
        v: dict[int, Any] = ...

    assert Model(v={1: 'foobar'}).model_dump() == {'v': {1: 'foobar'}}
    assert Model(v={123: 456}).model_dump() == {'v': {123: 456}}
    assert Model(v={2: [1, 2, 3]}).model_dump() == {'v': {2: [1, 2, 3]}}


def test_success_values_include():
    class Model(BaseModel):
        a: int = 1
        b: int = 2
        c: int = 3

    m = Model()
    assert m.model_dump() == {'a': 1, 'b': 2, 'c': 3}
    assert m.model_dump(include={'a'}) == {'a': 1}
    assert m.model_dump(exclude={'a'}) == {'b': 2, 'c': 3}
    assert m.model_dump(include={'a', 'b'}, exclude={'a'}) == {'b': 2}


def test_include_exclude_unset():
    class Model(BaseModel):
        a: int
        b: int
        c: int = 3
        d: int = 4
        e: int = 5
        f: int = 6

    m = Model(a=1, b=2, e=5, f=7)
    assert m.model_dump() == {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 7}
    assert m.model_fields_set == {'a', 'b', 'e', 'f'}
    assert m.model_dump(exclude_unset=True) == {'a': 1, 'b': 2, 'e': 5, 'f': 7}

    assert m.model_dump(include={'a'}, exclude_unset=True) == {'a': 1}
    assert m.model_dump(include={'c'}, exclude_unset=True) == {}

    assert m.model_dump(exclude={'a'}, exclude_unset=True) == {'b': 2, 'e': 5, 'f': 7}
    assert m.model_dump(exclude={'c'}, exclude_unset=True) == {'a': 1, 'b': 2, 'e': 5, 'f': 7}

    assert m.model_dump(include={'a', 'b', 'c'}, exclude={'b'}, exclude_unset=True) == {'a': 1}
    assert m.model_dump(include={'a', 'b', 'c'}, exclude={'a', 'c'}, exclude_unset=True) == {'b': 2}


def test_include_exclude_defaults():
    class Model(BaseModel):
        a: int
        b: int
        c: int = 3
        d: int = 4
        e: int = 5
        f: int = 6

    m = Model(a=1, b=2, e=5, f=7)
    assert m.model_dump() == {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 7}
    assert m.model_fields_set == {'a', 'b', 'e', 'f'}
    assert m.model_dump(exclude_defaults=True) == {'a': 1, 'b': 2, 'f': 7}

    assert m.model_dump(include={'a'}, exclude_defaults=True) == {'a': 1}
    assert m.model_dump(include={'c'}, exclude_defaults=True) == {}

    assert m.model_dump(exclude={'a'}, exclude_defaults=True) == {'b': 2, 'f': 7}
    assert m.model_dump(exclude={'c'}, exclude_defaults=True) == {'a': 1, 'b': 2, 'f': 7}

    assert m.model_dump(include={'a', 'b', 'c'}, exclude={'b'}, exclude_defaults=True) == {'a': 1}
    assert m.model_dump(include={'a', 'b', 'c'}, exclude={'a', 'c'}, exclude_defaults=True) == {'b': 2}

    assert m.model_dump(include={'a': 1}.keys()) == {'a': 1}
    assert m.model_dump(exclude={'a': 1}.keys()) == {'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 7}

    assert m.model_dump(include={'a': 1}.keys(), exclude_unset=True) == {'a': 1}
    assert m.model_dump(exclude={'a': 1}.keys(), exclude_unset=True) == {'b': 2, 'e': 5, 'f': 7}

    assert m.model_dump(include=['a']) == {'a': 1}
    assert m.model_dump(exclude=['a']) == {'b': 2, 'c': 3, 'd': 4, 'e': 5, 'f': 7}

    assert m.model_dump(include=['a'], exclude_unset=True) == {'a': 1}
    assert m.model_dump(exclude=['a'], exclude_unset=True) == {'b': 2, 'e': 5, 'f': 7}


def test_advanced_exclude():
    class SubSubModel(BaseModel):
        a: str
        b: str

    class SubModel(BaseModel):
        c: str
        d: list[SubSubModel]

    class Model(BaseModel):
        e: str
        f: SubModel

    m = Model(e='e', f=SubModel(c='foo', d=[SubSubModel(a='a', b='b'), SubSubModel(a='c', b='e')]))

    assert m.model_dump(exclude={'f': {'c': ..., 'd': {-1: {'a'}}}}) == {
        'e': 'e',
        'f': {'d': [{'a': 'a', 'b': 'b'}, {'b': 'e'}]},
    }
    assert m.model_dump(exclude={'e': ..., 'f': {'d'}}) == {'f': {'c': 'foo'}}


def test_advanced_exclude_by_alias():
    class SubSubModel(BaseModel):
        a: str
        aliased_b: str = Field(alias='b_alias')

    class SubModel(BaseModel):
        aliased_c: str = Field(alias='c_alias')
        aliased_d: list[SubSubModel] = Field(alias='d_alias')

    class Model(BaseModel):
        aliased_e: str = Field(alias='e_alias')
        aliased_f: SubModel = Field(alias='f_alias')

    m = Model(
        e_alias='e',
        f_alias=SubModel(c_alias='foo', d_alias=[SubSubModel(a='a', b_alias='b'), SubSubModel(a='c', b_alias='e')]),
    )

    excludes = {'aliased_f': {'aliased_c': ..., 'aliased_d': {-1: {'a'}}}}
    assert m.model_dump(exclude=excludes, by_alias=True) == {
        'e_alias': 'e',
        'f_alias': {'d_alias': [{'a': 'a', 'b_alias': 'b'}, {'b_alias': 'e'}]},
    }

    excludes = {'aliased_e': ..., 'aliased_f': {'aliased_d'}}
    assert m.model_dump(exclude=excludes, by_alias=True) == {'f_alias': {'c_alias': 'foo'}}


def test_advanced_value_include():
    class SubSubModel(BaseModel):
        a: str
        b: str

    class SubModel(BaseModel):
        c: str
        d: list[SubSubModel]

    class Model(BaseModel):
        e: str
        f: SubModel

    m = Model(e='e', f=SubModel(c='foo', d=[SubSubModel(a='a', b='b'), SubSubModel(a='c', b='e')]))

    assert m.model_dump(include={'f'}) == {'f': {'c': 'foo', 'd': [{'a': 'a', 'b': 'b'}, {'a': 'c', 'b': 'e'}]}}
    assert m.model_dump(include={'e'}) == {'e': 'e'}
    assert m.model_dump(include={'f': {'d': {0: ..., -1: {'b'}}}}) == {'f': {'d': [{'a': 'a', 'b': 'b'}, {'b': 'e'}]}}


def test_advanced_value_exclude_include():
    class SubSubModel(BaseModel):
        a: str
        b: str

    class SubModel(BaseModel):
        c: str
        d: list[SubSubModel]

    class Model(BaseModel):
        e: str
        f: SubModel

    m = Model(e='e', f=SubModel(c='foo', d=[SubSubModel(a='a', b='b'), SubSubModel(a='c', b='e')]))

    assert m.model_dump(exclude={'f': {'c': ..., 'd': {-1: {'a'}}}}, include={'f'}) == {
        'f': {'d': [{'a': 'a', 'b': 'b'}, {'b': 'e'}]}
    }
    assert m.model_dump(exclude={'e': ..., 'f': {'d'}}, include={'e', 'f'}) == {'f': {'c': 'foo'}}

    assert m.model_dump(exclude={'f': {'d': {-1: {'a'}}}}, include={'f': {'d'}}) == {
        'f': {'d': [{'a': 'a', 'b': 'b'}, {'b': 'e'}]}
    }


@pytest.mark.parametrize(
    'exclude,expected',
    [
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{'j': 1}, {'j': 2}]}, {'k': 2, 'subsubs': [{'j': 3}]}]},
            id='Normal nested __all__',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}}}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{}, {}]}, {'k': 2, 'subsubs': [{'j': 3}]}]},
            id='Merge sub dicts 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': ...}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1}, {'i': 2}]}, {'k': 2}]},
            # {'subs': [{'k': 1                                 }, {'k': 2}]}
            id='Merge sub sets 2',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'j'}}}, 0: {'subsubs': ...}}},
            {'subs': [{'k': 1}, {'k': 2, 'subsubs': [{'i': 3}]}]},
            id='Merge sub sets 3',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {0}}, 0: {'subsubs': {1}}}},
            {'subs': [{'k': 1, 'subsubs': []}, {'k': 2, 'subsubs': []}]},
            id='Merge sub sets 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {0: {'i'}}}, 0: {'subsubs': {1}}}},
            {'subs': [{'k': 1, 'subsubs': [{'j': 1}]}, {'k': 2, 'subsubs': [{'j': 3}]}]},
            id='Merge sub dict-set',
        ),
        pytest.param({'subs': {'__all__': {'subsubs'}, 0: {'k'}}}, {'subs': [{}, {'k': 2}]}, id='Different keys 1'),
        pytest.param(
            {'subs': {'__all__': {'subsubs': ...}, 0: {'k'}}}, {'subs': [{}, {'k': 2}]}, id='Different keys 2'
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs'}, 0: {'k': ...}}}, {'subs': [{}, {'k': 2}]}, id='Different keys 3'
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}, 0: {'j'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{}, {'j': 2}]}, {'k': 2, 'subsubs': [{}]}]},
            id='Nested different keys 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i': ...}, 0: {'j'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{}, {'j': 2}]}, {'k': 2, 'subsubs': [{}]}]},
            id='Nested different keys 2',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}, 0: {'j': ...}}}}},
            {'subs': [{'k': 1, 'subsubs': [{}, {'j': 2}]}, {'k': 2, 'subsubs': [{}]}]},
            id='Nested different keys 3',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs'}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1}, {'i': 2}]}, {'k': 2}]},
            id='Ignore __all__ for index with defined exclude 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'j'}}}, 0: ...}},
            {'subs': [{'k': 2, 'subsubs': [{'i': 3}]}]},
            id='Ignore __all__ for index with defined exclude 2',
        ),
        pytest.param(
            {'subs': {'__all__': ..., 0: {'subsubs'}}},
            {'subs': [{'k': 1}]},
            id='Ignore __all__ for index with defined exclude 3',
        ),
    ],
)
def test_advanced_exclude_nested_lists(exclude, expected):
    class SubSubModel(BaseModel):
        i: int
        j: int

    class SubModel(BaseModel):
        k: int
        subsubs: list[SubSubModel]

    class Model(BaseModel):
        subs: list[SubModel]

    m = Model(subs=[dict(k=1, subsubs=[dict(i=1, j=1), dict(i=2, j=2)]), dict(k=2, subsubs=[dict(i=3, j=3)])])

    assert m.model_dump(exclude=exclude) == expected


@pytest.mark.parametrize(
    'include,expected',
    [
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}}}}},
            {'subs': [{'subsubs': [{'i': 1}, {'i': 2}]}, {'subsubs': [{'i': 3}]}]},
            id='Normal nested __all__',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}}}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3}]}]},
            id='Merge sub dicts 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': ...}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'subsubs': [{'j': 1}, {'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Merge sub dicts 2',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'j'}}}, 0: {'subsubs': ...}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'j': 3}]}]},
            id='Merge sub dicts 3',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {0}}, 0: {'subsubs': {1}}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Merge sub sets',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {0: {'i'}}}, 0: {'subsubs': {1}}}},
            {'subs': [{'subsubs': [{'i': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3}]}]},
            id='Merge sub dict-set',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs'}, 0: {'k'}}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': ...}, 0: {'k'}}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 2',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs'}, 0: {'k': ...}}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 3',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}, 0: {'j'}}}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i': ...}, 0: {'j'}}}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 2',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'i'}, 0: {'j': ...}}}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Nested different keys 3',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs'}, 0: {'subsubs': {'__all__': {'j'}}}}},
            {'subs': [{'subsubs': [{'j': 1}, {'j': 2}]}, {'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Ignore __all__ for index with defined include 1',
        ),
        pytest.param(
            {'subs': {'__all__': {'subsubs': {'__all__': {'j'}}}, 0: ...}},
            {'subs': [{'k': 1, 'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'subsubs': [{'j': 3}]}]},
            id='Ignore __all__ for index with defined include 2',
        ),
        pytest.param(
            {'subs': {'__all__': ..., 0: {'subsubs'}}},
            {'subs': [{'subsubs': [{'i': 1, 'j': 1}, {'i': 2, 'j': 2}]}, {'k': 2, 'subsubs': [{'i': 3, 'j': 3}]}]},
            id='Ignore __all__ for index with defined include 3',
        ),
    ],
)
def test_advanced_include_nested_lists(include, expected):
    class SubSubModel(BaseModel):
        i: int
        j: int

    class SubModel(BaseModel):
        k: int
        subsubs: list[SubSubModel]

    class Model(BaseModel):
        subs: list[SubModel]

    m = Model(subs=[dict(k=1, subsubs=[dict(i=1, j=1), dict(i=2, j=2)]), dict(k=2, subsubs=[dict(i=3, j=3)])])

    assert m.model_dump(include=include) == expected


def test_field_set_ignore_extra():
    class Model(BaseModel):
        model_config = ConfigDict(extra='ignore')
        a: int
        b: int
        c: int = 3

    m = Model(a=1, b=2)
    assert m.model_dump() == {'a': 1, 'b': 2, 'c': 3}
    assert m.model_fields_set == {'a', 'b'}
    assert m.model_dump(exclude_unset=True) == {'a': 1, 'b': 2}

    m2 = Model(a=1, b=2, d=4)
    assert m2.model_dump() == {'a': 1, 'b': 2, 'c': 3}
    assert m2.model_fields_set == {'a', 'b'}
    assert m2.model_dump(exclude_unset=True) == {'a': 1, 'b': 2}


def test_field_set_allow_extra():
    class Model(BaseModel):
        model_config = ConfigDict(extra='allow')
        a: int
        b: int
        c: int = 3

    m = Model(a=1, b=2)
    assert m.model_dump() == {'a': 1, 'b': 2, 'c': 3}
    assert m.model_fields_set == {'a', 'b'}
    assert m.model_dump(exclude_unset=True) == {'a': 1, 'b': 2}

    m2 = Model(a=1, b=2, d=4)
    assert m2.model_dump() == {'a': 1, 'b': 2, 'c': 3, 'd': 4}
    assert m2.model_fields_set == {'a', 'b', 'd'}
    assert m2.model_dump(exclude_unset=True) == {'a': 1, 'b': 2, 'd': 4}


def test_field_set_field_name():
    class Model(BaseModel):
        a: int
        field_set: int
        b: int = 3

    assert Model(a=1, field_set=2).model_dump() == {'a': 1, 'field_set': 2, 'b': 3}
    assert Model(a=1, field_set=2).model_dump(exclude_unset=True) == {'a': 1, 'field_set': 2}
    assert Model.model_construct(a=1, field_set=3).model_dump() == {'a': 1, 'field_set': 3, 'b': 3}


def test_values_order():
    class Model(BaseModel):
        a: int = 1
        b: int = 2
        c: int = 3

    m = Model(c=30, b=20, a=10)
    assert list(m) == [('a', 10), ('b', 20), ('c', 30)]


def test_inheritance():
    class Foo(BaseModel):
        a: float = ...

    with pytest.raises(
        PydanticUserError,
        match=(
            "Field 'a' defined on a base class was overridden by a non-annotated attribute. "
            'All field definitions, including overrides, require a type annotation.'
        ),
    ):

        class Bar(Foo):
            x: float = 12.3
            a = 123.0

    class Bar2(Foo):
        x: float = 12.3
        a: float = 123.0

    assert Bar2().model_dump() == {'x': 12.3, 'a': 123.0}

    class Bar3(Foo):
        x: float = 12.3
        a: float = Field(default=123.0)

    assert Bar3().model_dump() == {'x': 12.3, 'a': 123.0}


def test_inheritance_subclass_default():
    class MyStr(str):
        pass

    # Confirm hint supports a subclass default
    class Simple(BaseModel):
        x: str = MyStr('test')

        model_config = dict(arbitrary_types_allowed=True)

    # Confirm hint on a base can be overridden with a subclass default on a subclass
    class Base(BaseModel):
        x: str
        y: str

    class Sub(Base):
        x: str = MyStr('test')
        y: MyStr = MyStr('test')  # force subtype

        model_config = dict(arbitrary_types_allowed=True)

    assert Sub.model_fields['x'].annotation == str
    assert Sub.model_fields['y'].annotation == MyStr


def test_invalid_type():
    with pytest.raises(PydanticSchemaGenerationError) as exc_info:

        class Model(BaseModel):
            x: 43 = 123

    assert 'Unable to generate pydantic-core schema for 43' in exc_info.value.args[0]


class CustomStr(str):
    def foobar(self):
        return 7


@pytest.mark.parametrize(
    'value,expected',
    [
        ('a string', 'a string'),
        (b'some bytes', 'some bytes'),
        (bytearray('foobar', encoding='utf8'), 'foobar'),
        (StrEnum.a, 'a10'),
        (CustomStr('whatever'), 'whatever'),
    ],
)
def test_valid_string_types(value, expected):
    class Model(BaseModel):
        v: str

    assert Model(v=value).v == expected


@pytest.mark.parametrize(
    'value,errors',
    [
        (
            {'foo': 'bar'},
            [{'input': {'foo': 'bar'}, 'loc': ('v',), 'msg': 'Input should be a valid string', 'type': 'string_type'}],
        ),
        (
            [1, 2, 3],
            [{'input': [1, 2, 3], 'loc': ('v',), 'msg': 'Input should be a valid string', 'type': 'string_type'}],
        ),
    ],
)
def test_invalid_string_types(value, errors):
    class Model(BaseModel):
        v: str

    with pytest.raises(ValidationError) as exc_info:
        Model(v=value)
    assert exc_info.value.errors(include_url=False) == errors


def test_inheritance_config():
    class Parent(BaseModel):
        a: str

    class Child(Parent):
        model_config = ConfigDict(str_to_lower=True)
        b: str

    m1 = Parent(a='A')
    m2 = Child(a='A', b='B')
    assert repr(m1) == "Parent(a='A')"
    assert repr(m2) == "Child(a='a', b='b')"


def test_partial_inheritance_config():
    class Parent(BaseModel):
        a: int = Field(ge=0)

    class Child(Parent):
        b: int = Field(ge=0)

    Child(a=0, b=0)
    with pytest.raises(ValidationError) as exc_info:
        Child(a=-1, b=0)
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'ge': 0},
            'input': -1,
            'loc': ('a',),
            'msg': 'Input should be greater than or equal to 0',
            'type': 'greater_than_equal',
        }
    ]

    with pytest.raises(ValidationError) as exc_info:
        Child(a=0, b=-1)
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'ge': 0},
            'input': -1,
            'loc': ('b',),
            'msg': 'Input should be greater than or equal to 0',
            'type': 'greater_than_equal',
        }
    ]


def test_annotation_inheritance():
    class A(BaseModel):
        integer: int = 1

    class B(A):
        integer: int = 2

    assert B.model_fields['integer'].annotation == int

    class C(A):
        integer: str = 'G'

    assert C.__annotations__['integer'] == str
    assert C.model_fields['integer'].annotation == str

    with pytest.raises(
        PydanticUserError,
        match=(
            "Field 'integer' defined on a base class was overridden by a non-annotated attribute. "
            'All field definitions, including overrides, require a type annotation.'
        ),
    ):

        class D(A):
            integer = 'G'


def test_string_none():
    class Model(BaseModel):
        model_config = ConfigDict(extra='ignore')
        a: constr(min_length=20, max_length=1000) = ...

    with pytest.raises(ValidationError) as exc_info:
        Model(a=None)
    assert exc_info.value.errors(include_url=False) == [
        {'input': None, 'loc': ('a',), 'msg': 'Input should be a valid string', 'type': 'string_type'}
    ]


# def test_return_errors_ok():
#     class Model(BaseModel):
#         foo: int
#         bar: list[int]
#
#     assert validate_model(Model, {'foo': '123', 'bar': (1, 2, 3)}) == (
#         {'foo': 123, 'bar': [1, 2, 3]},
#         {'foo', 'bar'},
#         None,
#     )
#     d, f, e = validate_model(Model, {'foo': '123', 'bar': (1, 2, 3)}, False)
#     assert d == {'foo': 123, 'bar': [1, 2, 3]}
#     assert f == {'foo', 'bar'}
#     assert e is None


# def test_return_errors_error():
#     class Model(BaseModel):
#         foo: int
#         bar: list[int]
#
#     d, f, e = validate_model(Model, {'foo': '123', 'bar': (1, 2, 'x')}, False)
#     assert d == {'foo': 123}
#     assert f == {'foo', 'bar'}
#     assert e.errors() == [{'loc': ('bar', 2), 'msg': 'value is not a valid integer', 'type': 'type_error.integer'}]
#
#     d, f, e = validate_model(Model, {'bar': (1, 2, 3)}, False)
#     assert d == {'bar': [1, 2, 3]}
#     assert f == {'bar'}
#     assert e.errors() == [{'loc': ('foo',), 'msg': 'field required', 'type': 'value_error.missing'}]


def test_optional_required():
    class Model(BaseModel):
        bar: Optional[int]

    assert Model(bar=123).model_dump() == {'bar': 123}
    assert Model(bar=None).model_dump() == {'bar': None}

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('bar',), 'msg': 'Field required', 'type': 'missing'}
    ]


def test_unable_to_infer():
    with pytest.raises(
        errors.PydanticUserError,
        match=re.escape(
            'A non-annotated attribute was detected: `x = None`. All model fields require a type annotation; '
            'if `x` is not meant to be a field, you may be able to resolve this error by annotating it as a '
            "`ClassVar` or updating `model_config['ignored_types']`"
        ),
    ):

        class InvalidDefinitionModel(BaseModel):
            x = None


def test_multiple_errors():
    class Model(BaseModel):
        a: Union[None, int, float, Decimal]

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foobar')

    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing',
            'loc': ('a', 'int'),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'input': 'foobar',
        },
        {
            'type': 'float_parsing',
            'loc': ('a', 'float'),
            'msg': 'Input should be a valid number, unable to parse string as a number',
            'input': 'foobar',
        },
        {
            'type': 'decimal_parsing',
            'loc': ('a', 'decimal'),
            'msg': 'Input should be a valid decimal',
            'input': 'foobar',
        },
    ]

    assert Model(a=1.5).a == 1.5
    assert Model(a=None).a is None


def test_validate_default():
    class Model(BaseModel):
        model_config = ConfigDict(validate_default=True)
        a: int
        b: int

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('a',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {}, 'loc': ('b',), 'msg': 'Field required', 'type': 'missing'},
    ]


def test_force_extra():
    class Model(BaseModel):
        model_config = ConfigDict(extra='ignore')
        foo: int

    assert Model.model_config['extra'] == 'ignore'


def test_submodel_different_type():
    class Foo(BaseModel):
        a: int

    class Bar(BaseModel):
        b: int

    class Spam(BaseModel):
        c: Foo

    assert Spam(c={'a': '123'}).model_dump() == {'c': {'a': 123}}
    with pytest.raises(ValidationError):
        Spam(c={'b': '123'})

    assert Spam(c=Foo(a='123')).model_dump() == {'c': {'a': 123}}
    with pytest.raises(ValidationError):
        Spam(c=Bar(b='123'))


def test_self():
    class Model(BaseModel):
        self: str

    m = Model.model_validate(dict(self='some value'))
    assert m.model_dump() == {'self': 'some value'}
    assert m.self == 'some value'
    assert m.model_json_schema() == {
        'title': 'Model',
        'type': 'object',
        'properties': {'self': {'title': 'Self', 'type': 'string'}},
        'required': ['self'],
    }


def test_no_name_conflict_in_constructor():
    class Model(BaseModel):
        self: int

    m = Model(**{'__pydantic_self__': 4, 'self': 2})
    assert m.self == 2


def test_self_recursive():
    class SubModel(BaseModel):
        self: int

    class Model(BaseModel):
        sm: SubModel

    m = Model.model_validate({'sm': {'self': '123'}})
    assert m.model_dump() == {'sm': {'self': 123}}


def test_custom_init():
    class Model(BaseModel):
        x: int

        def __init__(self, x: int, y: int):
            if isinstance(y, str):
                y = len(y)
            super().__init__(x=x + int(y))

    assert Model(x=1, y=1).x == 2
    assert Model.model_validate({'x': 1, 'y': 1}).x == 2
    assert Model.model_validate_json('{"x": 1, "y": 2}').x == 3

    # For documentation purposes: type hints on __init__ are not currently used for validation:
    assert Model.model_validate({'x': 1, 'y': 'abc'}).x == 4


def test_custom_init_validate_strings() -> None:
    """https://github.com/pydantic/pydantic/issues/12718."""
    calls: list[dict[str, object]] = []

    class Model(BaseModel):
        x: int

        def __init__(self, **data: object) -> None:
            calls.append(data)
            super().__init__(**data)

    Model.model_validate_strings({'x': '1'})

    assert calls == [{'x': '1'}]


def test_nested_custom_init():
    class NestedModel(BaseModel):
        self: str
        modified_number: int = 1

        def __init__(someinit, **kwargs):
            super().__init__(**kwargs)
            someinit.modified_number += 1

    class TopModel(BaseModel):
        self: str
        nest: NestedModel

    m = TopModel.model_validate(dict(self='Top Model', nest=dict(self='Nested Model', modified_number=0)))
    assert m.self == 'Top Model'
    assert m.nest.self == 'Nested Model'
    assert m.nest.modified_number == 1


def test_init_inspection():
    calls = []

    class Foobar(BaseModel):
        x: int

        def __init__(self, **data) -> None:
            with pytest.raises(AttributeError):
                calls.append(data)
                assert self.x
            super().__init__(**data)

    Foobar(x=1)
    Foobar.model_validate({'x': 2})
    Foobar.model_validate_json('{"x": 3}')
    assert calls == [{'x': 1}, {'x': 2}, {'x': 3}]


def test_type_on_annotation():
    class FooBar:
        pass

    class Model(BaseModel):
        a: type[int]
        b: type[int] = int
        c: type[FooBar]
        d: type[FooBar] = FooBar
        e: Sequence[type[FooBar]] = [FooBar]
        f: Union[type[FooBar], Sequence[type[FooBar]]] = FooBar
        g: Union[type[FooBar], Sequence[type[FooBar]]] = [FooBar]

        model_config = {'arbitrary_types_allowed': True}

    assert Model.model_fields.keys() == set('abcdefg')


def test_type_union():
    class Model(BaseModel):
        a: type[Union[str, bytes]]
        b: type[Union[Any, str]]

    m = Model(a=bytes, b=int)
    assert m.model_dump() == {'a': bytes, 'b': int}
    assert m.a == bytes


def test_type_on_none():
    class Model(BaseModel):
        a: type[None]

    Model(a=type(None))

    with pytest.raises(ValidationError) as exc_info:
        Model(a=None)

    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'is_subclass_of',
            'loc': ('a',),
            'msg': 'Input should be a subclass of NoneType',
            'input': None,
            'ctx': {'class': 'NoneType'},
        }
    ]


def test_type_on_typealias():
    Float = TypeAliasType('Float', float)

    class MyFloat(float): ...

    adapter = TypeAdapter(type[Float])

    adapter.validate_python(float)
    adapter.validate_python(MyFloat)

    with pytest.raises(ValidationError) as exc_info:
        adapter.validate_python(str)

    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'is_subclass_of',
            'loc': (),
            'msg': 'Input should be a subclass of float',
            'input': str,
            'ctx': {'class': 'float'},
        }
    ]


def test_type_on_annotated():
    class Model(BaseModel):
        a: type[Annotated[int, ...]]

    Model(a=int)

    with pytest.raises(ValidationError) as exc_info:
        Model(a=str)

    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'is_subclass_of',
            'loc': ('a',),
            'msg': 'Input should be a subclass of int',
            'input': str,
            'ctx': {'class': 'int'},
        }
    ]


def test_type_on_generic_alias() -> None:
    error_msg = 'Instead of using type[list[int]], use type[list].'

    with pytest.raises(PydanticUserError) as exc_info:

        class Model(BaseModel):
            a: type[list[int]]

    assert error_msg in exc_info.value.message


def test_typing_type_on_generic_alias() -> None:
    error_msg = 'Instead of using type[typing.List[int]], use type[list].'

    with pytest.raises(PydanticUserError) as exc_info:
        # Note: this only works with typing.List, list behaves differently in Python 3.9 and sometimes 3.10,
        # so thus we use typing.List here.
        class Model(BaseModel):
            a: type[typing.List[int]]  # noqa: UP006

    assert error_msg in exc_info.value.message


def test_type_assign():
    class Parent:
        def echo(self):
            return 'parent'

    class Child(Parent):
        def echo(self):
            return 'child'

    class Different:
        def echo(self):
            return 'different'

    class Model(BaseModel):
        v: type[Parent] = Parent

    assert Model(v=Parent).v().echo() == 'parent'
    assert Model().v().echo() == 'parent'
    assert Model(v=Child).v().echo() == 'child'
    with pytest.raises(ValidationError) as exc_info:
        Model(v=Different)
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'class': Parent.__qualname__},
            'input': HasRepr(repr(Different)),
            'loc': ('v',),
            'msg': f'Input should be a subclass of {Parent.__qualname__}',
            'type': 'is_subclass_of',
        }
    ]


def test_optional_subfields():
    class Model(BaseModel):
        a: Optional[int]

    assert Model.model_fields['a'].annotation == Optional[int]

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foobar')
    assert exc_info.value.errors(include_url=False) == [
        {
            'input': 'foobar',
            'loc': ('a',),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'type': 'int_parsing',
        }
    ]

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('a',), 'msg': 'Field required', 'type': 'missing'}
    ]

    assert Model(a=None).a is None
    assert Model(a=12).a == 12


def test_validated_optional_subfields():
    class Model(BaseModel):
        a: Optional[int]

        @field_validator('a')
        @classmethod
        def check_a(cls, v):
            return v

    assert Model.model_fields['a'].annotation == Optional[int]

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foobar')
    assert exc_info.value.errors(include_url=False) == [
        {
            'input': 'foobar',
            'loc': ('a',),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'type': 'int_parsing',
        }
    ]

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('a',), 'msg': 'Field required', 'type': 'missing'}
    ]

    assert Model(a=None).a is None
    assert Model(a=12).a == 12


def test_optional_field_constraints():
    class MyModel(BaseModel):
        my_int: Optional[int] = Field(ge=3)

    with pytest.raises(ValidationError) as exc_info:
        MyModel(my_int=2)
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'ge': 3},
            'input': 2,
            'loc': ('my_int',),
            'msg': 'Input should be greater than or equal to 3',
            'type': 'greater_than_equal',
        }
    ]


def test_field_str_shape():
    class Model(BaseModel):
        a: list[int]

    assert repr(Model.model_fields['a']) == 'FieldInfo(annotation=list[int], required=True)'
    assert str(Model.model_fields['a']) == 'annotation=list[int] required=True'


T1 = TypeVar('T1')
T2 = TypeVar('T2')


class DisplayGen(Generic[T1, T2]):
    def __init__(self, t1: T1, t2: T2):
        self.t1 = t1
        self.t2 = t2


@pytest.mark.parametrize(
    'type_,expected',
    [
        (int, 'int'),
        (Optional[int], 'Union[int, NoneType]'),
        (Union[None, int, str], 'Union[NoneType, int, str]'),
        (Union[int, str, bytes], 'Union[int, str, bytes]'),
        (list[int], 'list[int]'),
        (tuple[int, str, bytes], 'tuple[int, str, bytes]'),
        (Union[list[int], set[bytes]], 'Union[list[int], set[bytes]]'),
        (list[tuple[int, int]], 'list[tuple[int, int]]'),
        (dict[int, str], 'dict[int, str]'),
        (frozenset[int], 'frozenset[int]'),
        (tuple[int, ...], 'tuple[int, ...]'),
        (Optional[list[int]], 'Union[list[int], NoneType]'),
        (dict, 'dict'),
        pytest.param(
            DisplayGen[bool, str],
            'tests.test_edge_cases.DisplayGen[bool, str]',
            marks=pytest.mark.skipif(sys.version_info[:2] > (3, 9), reason='difference in __name__ between versions'),
        ),
    ],
)
def test_field_type_display(type_, expected):
    class Model(BaseModel):
        a: type_

        model_config = dict(arbitrary_types_allowed=True)

    assert re.search(rf'\(annotation={re.escape(expected)},', str(Model.model_fields))


def test_any_none():
    class MyModel(BaseModel):
        foo: Any

    m = MyModel(foo=None)
    assert dict(m) == {'foo': None}


def test_type_var_any():
    Foobar = TypeVar('Foobar')

    class MyModel(BaseModel):
        foo: Foobar

    assert MyModel.model_json_schema() == {
        'properties': {'foo': {'title': 'Foo'}},
        'required': ['foo'],
        'title': 'MyModel',
        'type': 'object',
    }
    assert MyModel(foo=None).foo is None
    assert MyModel(foo='x').foo == 'x'
    assert MyModel(foo=123).foo == 123


def test_type_var_constraint():
    Foobar = TypeVar('Foobar', int, str)

    class MyModel(BaseModel):
        foo: Foobar

    assert MyModel.model_json_schema() == {
        'title': 'MyModel',
        'type': 'object',
        'properties': {'foo': {'title': 'Foo', 'anyOf': [{'type': 'integer'}, {'type': 'string'}]}},
        'required': ['foo'],
    }
    with pytest.raises(ValidationError) as exc_info:
        MyModel(foo=None)
    assert exc_info.value.errors(include_url=False) == [
        {'input': None, 'loc': ('foo', 'int'), 'msg': 'Input should be a valid integer', 'type': 'int_type'},
        {'input': None, 'loc': ('foo', 'str'), 'msg': 'Input should be a valid string', 'type': 'string_type'},
    ]

    with pytest.raises(ValidationError):
        MyModel(foo=[1, 2, 3])
    assert exc_info.value.errors(include_url=False) == [
        {'input': None, 'loc': ('foo', 'int'), 'msg': 'Input should be a valid integer', 'type': 'int_type'},
        {'input': None, 'loc': ('foo', 'str'), 'msg': 'Input should be a valid string', 'type': 'string_type'},
    ]

    assert MyModel(foo='x').foo == 'x'
    assert MyModel(foo=123).foo == 123


def test_type_var_bound():
    Foobar = TypeVar('Foobar', bound=int)

    class MyModel(BaseModel):
        foo: Foobar

    assert MyModel.model_json_schema() == {
        'title': 'MyModel',
        'type': 'object',
        'properties': {'foo': {'title': 'Foo', 'type': 'integer'}},
        'required': ['foo'],
    }
    with pytest.raises(ValidationError) as exc_info:
        MyModel(foo=None)
    assert exc_info.value.errors(include_url=False) == [
        {'input': None, 'loc': ('foo',), 'msg': 'Input should be a valid integer', 'type': 'int_type'}
    ]

    with pytest.raises(ValidationError):
        MyModel(foo='x')
    assert exc_info.value.errors(include_url=False) == [
        {'input': None, 'loc': ('foo',), 'msg': 'Input should be a valid integer', 'type': 'int_type'}
    ]
    assert MyModel(foo=123).foo == 123


def test_dict_bare():
    class MyModel(BaseModel):
        foo: dict

    m = MyModel(foo={'x': 'a', 'y': None})
    assert m.foo == {'x': 'a', 'y': None}


def test_list_bare():
    class MyModel(BaseModel):
        foo: list

    m = MyModel(foo=[1, 2, None])
    assert m.foo == [1, 2, None]


def test_dict_any():
    class MyModel(BaseModel):
        foo: dict[str, Any]

    m = MyModel(foo={'x': 'a', 'y': None})
    assert m.foo == {'x': 'a', 'y': None}


def test_modify_fields():
    class Foo(BaseModel):
        foo: list[list[int]]

        @field_validator('foo')
        @classmethod
        def check_something(cls, value):
            return value

    class Bar(Foo):
        pass

    assert repr(Foo.model_fields['foo']) == 'FieldInfo(annotation=list[list[int]], required=True)'
    assert repr(Bar.model_fields['foo']) == 'FieldInfo(annotation=list[list[int]], required=True)'
    assert Foo(foo=[[0, 1]]).foo == [[0, 1]]
    assert Bar(foo=[[0, 1]]).foo == [[0, 1]]


def test_exclude_none():
    class MyModel(BaseModel):
        a: Optional[int] = None
        b: int = 2

    m = MyModel(a=5)
    assert m.model_dump(exclude_none=True) == {'a': 5, 'b': 2}

    m = MyModel(b=3)
    assert m.model_dump(exclude_none=True) == {'b': 3}
    assert m.model_dump_json(exclude_none=True) == '{"b":3}'


def test_exclude_none_recursive():
    class ModelA(BaseModel):
        a: Optional[int] = None
        b: int = 1

    class ModelB(BaseModel):
        c: int
        d: int = 2
        e: ModelA
        f: Optional[str] = None

    m = ModelB(c=5, e={'a': 0})
    assert m.model_dump() == {'c': 5, 'd': 2, 'e': {'a': 0, 'b': 1}, 'f': None}
    assert m.model_dump(exclude_none=True) == {'c': 5, 'd': 2, 'e': {'a': 0, 'b': 1}}
    assert dict(m) == {'c': 5, 'd': 2, 'e': ModelA(a=0), 'f': None}

    m = ModelB(c=5, e={'b': 20}, f='test')
    assert m.model_dump() == {'c': 5, 'd': 2, 'e': {'a': None, 'b': 20}, 'f': 'test'}
    assert m.model_dump(exclude_none=True) == {'c': 5, 'd': 2, 'e': {'b': 20}, 'f': 'test'}
    assert dict(m) == {'c': 5, 'd': 2, 'e': ModelA(b=20), 'f': 'test'}


def test_exclude_none_with_extra():
    class MyModel(BaseModel):
        model_config = ConfigDict(extra='allow')
        a: str = 'default'
        b: Optional[str] = None

    m = MyModel(a='a', c='c')

    assert m.model_dump(exclude_none=True) == {'a': 'a', 'c': 'c'}
    assert m.model_dump() == {'a': 'a', 'b': None, 'c': 'c'}

    m = MyModel(a='a', b='b', c=None)

    assert m.model_dump(exclude_none=True) == {'a': 'a', 'b': 'b'}
    assert m.model_dump() == {'a': 'a', 'b': 'b', 'c': None}


def test_str_method_inheritance():
    import pydantic

    class Foo(pydantic.BaseModel):
        x: int = 3
        y: int = 4

        def __str__(self):
            return str(self.y + self.x)

    class Bar(Foo):
        z: bool = False

    assert str(Foo()) == '7'
    assert str(Bar()) == '7'


def test_repr_method_inheritance():
    import pydantic

    class Foo(pydantic.BaseModel):
        x: int = 3
        y: int = 4

        def __repr__(self):
            return repr(self.y + self.x)

    class Bar(Foo):
        z: bool = False

    assert repr(Foo()) == '7'
    assert repr(Bar()) == '7'


def test_optional_validator():
    val_calls = []

    class Model(BaseModel):
        something: Optional[str]

        @field_validator('something')
        @classmethod
        def check_something(cls, v):
            val_calls.append(v)
            return v

    with pytest.raises(ValidationError) as exc_info:
        assert Model().model_dump() == {'something': None}
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('something',), 'msg': 'Field required', 'type': 'missing'}
    ]

    assert Model(something=None).model_dump() == {'something': None}
    assert Model(something='hello').model_dump() == {'something': 'hello'}
    assert val_calls == [None, 'hello']


def test_required_optional():
    class Model(BaseModel):
        nullable1: Optional[int] = ...
        nullable2: Optional[int] = Field(...)

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('nullable1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {}, 'loc': ('nullable2',), 'msg': 'Field required', 'type': 'missing'},
    ]
    with pytest.raises(ValidationError) as exc_info:
        Model(nullable1=1)
    assert exc_info.value.errors(include_url=False) == [
        {'input': {'nullable1': 1}, 'loc': ('nullable2',), 'msg': 'Field required', 'type': 'missing'}
    ]
    with pytest.raises(ValidationError) as exc_info:
        Model(nullable2=2)
    assert exc_info.value.errors(include_url=False) == [
        {'input': {'nullable2': 2}, 'loc': ('nullable1',), 'msg': 'Field required', 'type': 'missing'}
    ]
    assert Model(nullable1=None, nullable2=None).model_dump() == {'nullable1': None, 'nullable2': None}
    assert Model(nullable1=1, nullable2=2).model_dump() == {'nullable1': 1, 'nullable2': 2}
    with pytest.raises(ValidationError) as exc_info:
        Model(nullable1='some text')
    assert exc_info.value.errors(include_url=False) == [
        {
            'input': 'some text',
            'loc': ('nullable1',),
            'msg': 'Input should be a valid integer, unable to parse string as an integer',
            'type': 'int_parsing',
        },
        {'input': {'nullable1': 'some text'}, 'loc': ('nullable2',), 'msg': 'Field required', 'type': 'missing'},
    ]


def test_ellipsis_forward_ref_annotated() -> None:
    """This previously resulted in the ellipsis being used as a default value."""

    class Model(BaseModel):
        f: 'Forward'

    Forward = Annotated[int, Field(...)]

    assert Model.model_fields['f'].default is PydanticUndefined


def test_private_attr_ellipsis() -> None:
    class Model(BaseModel):
        _a: int = PrivateAttr(...)

    assert not hasattr(Model(), '_a')


def test_required_any():
    class Model(BaseModel):
        optional1: Any
        optional2: Any = None
        optional3: Optional[Any] = None
        nullable1: Any = ...
        nullable2: Any = Field(...)
        nullable3: Optional[Any]

    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('optional1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {}, 'loc': ('nullable1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {}, 'loc': ('nullable2',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {}, 'loc': ('nullable3',), 'msg': 'Field required', 'type': 'missing'},
    ]
    with pytest.raises(ValidationError) as exc_info:
        Model(nullable1='a')
    assert exc_info.value.errors(include_url=False) == [
        {'input': {'nullable1': 'a'}, 'loc': ('optional1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {'nullable1': 'a'}, 'loc': ('nullable2',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {'nullable1': 'a'}, 'loc': ('nullable3',), 'msg': 'Field required', 'type': 'missing'},
    ]
    with pytest.raises(ValidationError) as exc_info:
        Model(nullable2=False)
    assert exc_info.value.errors(include_url=False) == [
        {'input': {'nullable2': False}, 'loc': ('optional1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {'nullable2': False}, 'loc': ('nullable1',), 'msg': 'Field required', 'type': 'missing'},
        {'input': {'nullable2': False}, 'loc': ('nullable3',), 'msg': 'Field required', 'type': 'missing'},
    ]
    with pytest.raises(ValidationError) as exc_info:
        assert Model(nullable1=None, nullable2=None).model_dump() == {
            'optional1': None,
            'optional2': None,
            'nullable1': None,
            'nullable2': None,
        }
    assert exc_info.value.errors(include_url=False) == [
        {
            'input': {'nullable1': None, 'nullable2': None},
            'loc': ('optional1',),
            'msg': 'Field required',
            'type': 'missing',
        },
        {
            'input': {'nullable1': None, 'nullable2': None},
            'loc': ('nullable3',),
            'msg': 'Field required',
            'type': 'missing',
        },
    ]
    assert Model(optional1=None, nullable1=1, nullable2='two', nullable3=None).model_dump() == {
        'optional1': None,
        'optional2': None,
        'optional3': None,
        'nullable1': 1,
        'nullable2': 'two',
        'nullable3': None,
    }
    assert Model(optional1='op1', optional2=False, nullable1=1, nullable2='two', nullable3='three').model_dump() == {
        'optional1': 'op1',
        'optional2': False,
        'optional3': None,
        'nullable1': 1,
        'nullable2': 'two',
        'nullable3': 'three',
    }


def test_custom_generic_validators():
    T1 = TypeVar('T1')
    T2 = TypeVar('T2')

    class MyGen(Generic[T1, T2]):
        def __init__(self, t1: T1, t2: T2):
            self.t1 = t1
            self.t2 = t2

        @classmethod
        def __get_pydantic_core_schema__(cls, source: Any, handler: GetCoreSchemaHandler):
            schema = core_schema.is_instance_schema(cls)

            args = get_args(source)
            if not args:
                return schema

            t1_f = TypeAdapter(args[0]).validate_python
            t2_f = TypeAdapter(args[1]).validate_python

            def convert_to_init_error(e: ErrorDetails, loc: str) -> InitErrorDetails:
                init_e = {'type': e['type'], 'loc': e['loc'] + (loc,), 'input': e['input']}
                if 'ctx' in e:
                    init_e['ctx'] = e['ctx']
                return init_e

            def validate(v, _info):
                if not args:
                    return v
                try:
                    v.t1 = t1_f(v.t1)
                except ValidationError as exc:
                    raise ValidationError.from_exception_data(
                        exc.title, [convert_to_init_error(e, 't1') for e in exc.errors()]
                    ) from exc
                try:
                    v.t2 = t2_f(v.t2)
                except ValidationError as exc:
                    raise ValidationError.from_exception_data(
                        exc.title, [convert_to_init_error(e, 't2') for e in exc.errors()]
                    ) from exc
                return v

            return core_schema.with_info_after_validator_function(validate, schema)

    class Model(BaseModel):
        a: str
        gen: MyGen[str, bool]
        gen2: MyGen

        model_config = dict(arbitrary_types_allowed=True)

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foo', gen='invalid', gen2='invalid')
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'class': 'test_custom_generic_validators.<locals>.MyGen'},
            'input': 'invalid',
            'loc': ('gen',),
            'msg': 'Input should be an instance of test_custom_generic_validators.<locals>.MyGen',
            'type': 'is_instance_of',
        },
        {
            'ctx': {'class': 'test_custom_generic_validators.<locals>.MyGen'},
            'input': 'invalid',
            'loc': ('gen2',),
            'msg': 'Input should be an instance of test_custom_generic_validators.<locals>.MyGen',
            'type': 'is_instance_of',
        },
    ]

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foo', gen=MyGen(t1='bar', t2='baz'), gen2=MyGen(t1='bar', t2='baz'))
    assert exc_info.value.errors(include_url=False) == [
        {
            'input': 'baz',
            'loc': ('gen', 't2'),
            'msg': 'Input should be a valid boolean, unable to interpret input',
            'type': 'bool_parsing',
        }
    ]

    m = Model(a='foo', gen=MyGen(t1='bar', t2=True), gen2=MyGen(t1=1, t2=2))
    assert m.a == 'foo'
    assert m.gen.t1 == 'bar'
    assert m.gen.t2 is True
    assert m.gen2.t1 == 1
    assert m.gen2.t2 == 2


def test_custom_generic_arbitrary_allowed():
    T1 = TypeVar('T1')
    T2 = TypeVar('T2')

    class MyGen(Generic[T1, T2]):
        def __init__(self, t1: T1, t2: T2):
            self.t1 = t1
            self.t2 = t2

    class Model(BaseModel):
        a: str
        gen: MyGen[str, bool]

        model_config = dict(arbitrary_types_allowed=True)

    with pytest.raises(ValidationError) as exc_info:
        Model(a='foo', gen='invalid')
    assert exc_info.value.errors(include_url=False) == [
        {
            'ctx': {'class': 'test_custom_generic_arbitrary_allowed.<locals>.MyGen'},
            'input': 'invalid',
            'loc': ('gen',),
            'msg': 'Input should be an instance of test_custom_generic_arbitrary_allowed.<locals>.MyGen',
            'type': 'is_instance_of',
        }
    ]

    # No validation, no exception
    m = Model(a='foo', gen=MyGen(t1='bar', t2='baz'))
    assert m.a == 'foo'
    assert m.gen.t1 == 'bar'
    assert m.gen.t2 == 'baz'

    m = Model(a='foo', gen=MyGen(t1='bar', t2=True))
    assert m.a == 'foo'
    assert m.gen.t1 == 'bar'
    assert m.gen.t2 is True


def test_custom_generic_disallowed():
    T1 = TypeVar('T1')
    T2 = TypeVar('T2')

    class MyGen(Generic[T1, T2]):
        def __init__(self, t1: T1, t2: T2):
            self.t1 = t1
            self.t2 = t2

    match = (
        r'Unable to generate pydantic-core schema for (.*)MyGen\[str, bool\](.*). '
        r'Set `arbitrary_types_allowed=True` in the model_config to ignore this error'
    )
    with pytest.raises(PydanticUserError, match=match):

        class Model(BaseModel):
            a: str
            gen: MyGen[str, bool]


def test_hashable_required():
    class Model(BaseModel):
        v: Hashable

    Model(v=None)
    with pytest.raises(ValidationError) as exc_info:
        Model(v=[])
    assert exc_info.value.errors(include_url=False) == [
        {'input': [], 'loc': ('v',), 'msg': 'Input should be hashable', 'type': 'is_hashable'}
    ]
    with pytest.raises(ValidationError) as exc_info:
        Model()
    assert exc_info.value.errors(include_url=False) == [
        {'input': {}, 'loc': ('v',), 'msg': 'Field required', 'type': 'missing'}
    ]


@pytest.mark.parametrize('default', [1, None])
def test_hashable_optional(default):
    class Model(BaseModel):
        v: Hashable = default

    Model(v=None)
    Model()


def test_hashable_serialization():
    class Model(BaseModel):
        v: Hashable

    class HashableButNotSerializable:
        def __hash__(self):
            return 0

    assert Model(v=(1,)).model_dump_json() == '{"v":[1]}'
    m = Model(v=HashableButNotSerializable())
    with pytest.raises(
        PydanticSerializationError, match='Unable to serialize unknown type:.*HashableButNotSerializable'
    ):
        m.model_dump_json()


def test_hashable_validate_json():
    class Model(BaseModel):
        v: Hashable

    ta = TypeAdapter(Model)

    # Test a large nested dict
    for validate in (Model.model_validate_json, ta.validate_json):
        for testcase in (
            '{"v": "a"}',
            '{"v": 1}',
            '{"v": 1.0}',
            '{"v": true}',
            '{"v": null}',
        ):
            assert hash(validate(testcase).v) == hash(validate(testcase).v)


@pytest.mark.parametrize(
    'non_hashable',
    [
        '{"v": []}',
        '{"v": {"a": 0}}',
    ],
)
def test_hashable_invalid_json(non_hashable) -> None:
    """This is primarily included in order to document the behavior / limitations of the `Hashable` type's validation logic.

    Specifically, we don't do any coercions to arrays / dicts when loading from JSON, and thus they are not considered hashable.
    This would be different if we, for example, coerced arrays to tuples.
    """

    class Model(BaseModel):
        v: Hashable

    with pytest.raises(ValidationError):
        Model.model_validate_json(non_hashable)


def test_hashable_json_schema():
    class Model(BaseModel):
        v: Hashable

    assert Model.model_json_schema() == {
        'properties': {'v': {'title': 'V'}},
        'required': ['v'],
        'title': 'Model',
        'type': 'object',
    }


def test_default_factory_called_once():
    """It should never call `default_factory` more than once even when `validate_all` is set"""

    v = 0

    def factory() -> int:
        nonlocal v
        v += 1
        return v

    class MyModel(BaseModel):
        model_config = ConfigDict(validate_default=True)
        id: int = Field(default_factory=factory)

    m1 = MyModel()
    assert m1.id == 1

    class MyBadModel(BaseModel):
        model_config = ConfigDict(validate_default=True)
        id: list[str] = Field(default_factory=factory)

    with pytest.raises(ValidationError) as exc_info:
        MyBadModel()
    assert v == 2  # `factory` has been called to run validation
    assert exc_info.value.errors(include_url=False) == [
        {'input': 2, 'loc': ('id',), 'msg': 'Input should be a valid list', 'type': 'list_type'}
    ]


def test_default_factory_validator_child():
    class Parent(BaseModel):
        foo: list[str] = Field(default_factory=list)

        @field_validator('foo', mode='before')
        @classmethod
        def mutate_foo(cls, v):
            return [f'{x}-1' for x in v]

    assert Parent(foo=['a', 'b']).foo == ['a-1', 'b-1']

    class Child(Parent):
        pass

    assert Child(foo=['a', 'b']).foo == ['a-1', 'b-1']


def test_resolve_annotations_module_missing(tmp_path):
    # see https://github.com/pydantic/pydantic/issues/2363
    file_path = tmp_path / 'module_to_load.py'
    # language=Python
    file_path.write_text(
        """
from pydantic import BaseModel
class User(BaseModel):
    id: int
    name: str = 'Jane Doe'
"""
    )

    spec = importlib.util.spec_from_file_location('my_test_module', file_path)
    module = importlib.util.module_from_spec(spec)
    spec.loader.exec_module(module)
    assert module.User(id=12).model_dump() == {'id': 12, 'name': 'Jane Doe'}


def test_iter_coverage():
    class MyModel(BaseModel):
        x: int = 1
        y: str = 'a'

    with pytest.warns(
        PydanticDeprecatedSince20, match='The private method `_iter` will be removed and should no longer be used.'
    ):
        assert list(MyModel()._iter(by_alias=True)) == [('x', 1), ('y', 'a')]


def test_frozen_config_and_field():
    class Foo(BaseModel):
        model_config = ConfigDict(frozen=False, validate_assignment=True)
        a: str

    assert Foo.model_fields['a'].metadata == []

    f = Foo(a='x')
    f.a = 'y'
    assert f.model_dump() == {'a': 'y'}

    class Bar(BaseModel):
        model_config = ConfigDict(validate_assignment=True)
        a: str = Field(frozen=True)
        c: Annotated[str, Field(frozen=True)]

    assert Bar.model_fields['a'].frozen

    b = Bar(a='x', c='z')
    with pytest.raises(ValidationError) as exc_info:
        b.a = 'y'
    assert exc_info.value.errors(include_url=False) == [
        {'input': 'y', 'loc': ('a',), 'msg': 'Field is frozen', 'type': 'frozen_field'}
    ]

    with pytest.raises(ValidationError) as exc_info:
        b.c = 'y'
    assert exc_info.value.errors(include_url=False) == [
        {'input': 'y', 'loc': ('c',), 'msg': 'Field is frozen', 'type': 'frozen_field'}
    ]

    assert b.model_dump() == {'a': 'x', 'c': 'z'}


def test_arbitrary_types_allowed_custom_eq():
    class Foo:
        def __eq__(self, other):
            if other.__class__ is not Foo:
                raise TypeError(f'Cannot interpret {other.__class__.__name__!r} as a valid type')
            return True

    class Model(BaseModel):
        model_config = ConfigDict(arbitrary_types_allowed=True)
        x: Foo = Foo()

    assert Model().x == Foo()


def test_bytes_subclass():
    class MyModel(BaseModel):
        my_bytes: bytes

    class BytesSubclass(bytes):
        def __new__(cls, data: bytes):
            self = bytes.__new__(cls, data)
            return self

    m = MyModel(my_bytes=BytesSubclass(b'foobar'))
    assert m.my_bytes.__class__ == BytesSubclass


def test_int_subclass():
    class MyModel(BaseModel):
        my_int: int

    class IntSubclass(int):
        def __new__(cls, data: int):
            self = int.__new__(cls, data)
            return self

    m = MyModel(my_int=IntSubclass(123))
    # This is expected behavior in `V2` because in pydantic-core we cast the value to a rust i64,
    # so the sub-type information is lost."
    # (more detail about how to handle this in: https://github.com/pydantic/pydantic/pull/5151#discussion_r1130691036)
    assert m.my_int.__class__ != IntSubclass
    assert isinstance(m.my_int, int)


def test_model_issubclass():
    assert not issubclass(int, BaseModel)

    class MyModel(BaseModel):
        x: int

    assert issubclass(MyModel, BaseModel)

    class Custom:
        __fields__ = True

    assert not issubclass(Custom, BaseModel)


def test_long_int():
    """
    see https://github.com/pydantic/pydantic/issues/1477 and in turn, https://github.com/python/cpython/issues/95778
    """

    class Model(BaseModel):
        x: int

    assert Model(x='1' * 4_300).x == int('1' * 4_300)

    too_long = '1' * 4_301
    with pytest.raises(ValidationError) as exc_info:
        Model(x=too_long)

    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'int_parsing_size',
            'loc': ('x',),
            'msg': 'Unable to parse input string as an integer, exceeded maximum size',
            'input': too_long,
        }
    ]

    # this used to hang indefinitely
    with pytest.raises(ValidationError):
        Model(x='1' * (10**7))


def test_parent_field_with_default():
    class Parent(BaseModel):
        a: int = 1
        b: int = Field(2)

    class Child(Parent):
        c: int = 3

    c = Child()
    assert c.a == 1
    assert c.b == 2
    assert c.c == 3


@pytest.mark.skipif(sys.version_info < (3, 12), reason='error message different on older versions')
@pytest.mark.parametrize(
    'bases',
    [
        (BaseModel, ABC),
        (ABC, BaseModel),
        (BaseModel,),
    ],
)
def test_abstractmethod_missing_for_all_decorators(bases):
    class AbstractSquare(*bases):
        side: float

        @field_validator('side')
        @classmethod
        @abstractmethod
        def my_field_validator(cls, v):
            raise NotImplementedError

        @model_validator(mode='wrap')
        @classmethod
        @abstractmethod
        def my_model_validator(cls, values, handler, info):
            raise NotImplementedError

        with pytest.warns(PydanticDeprecatedSince20):

            @root_validator(skip_on_failure=True)
            @classmethod
            @abstractmethod
            def my_root_validator(cls, values):
                raise NotImplementedError

        with pytest.warns(PydanticDeprecatedSince20):

            @validator('side')
            @classmethod
            @abstractmethod
            def my_validator(cls, value, **kwargs):
                raise NotImplementedError

        @model_serializer(mode='wrap')
        @abstractmethod
        def my_model_serializer(self, handler, info):
            raise NotImplementedError

        @field_serializer('side')
        @abstractmethod
        def my_serializer(self, v, _info):
            raise NotImplementedError

        @computed_field
        @property
        @abstractmethod
        def my_computed_field(self) -> Any:
            raise NotImplementedError

    class Square(AbstractSquare):
        pass

    with pytest.raises(
        TypeError,
        match=(
            "Can't instantiate abstract class Square without an implementation for abstract methods"
            " 'my_computed_field',"
            " 'my_field_validator',"
            " 'my_model_serializer',"
            " 'my_model_validator',"
            " 'my_root_validator',"
            " 'my_serializer',"
            " 'my_validator'"
        ),
    ):
        Square(side=1.0)


def test_generic_wrapped_forwardref():
    class Operation(BaseModel):
        callbacks: 'list[PathItem]'

    class PathItem(BaseModel):
        pass

    Operation.model_rebuild()

    Operation.model_validate({'callbacks': [PathItem()]})
    with pytest.raises(ValidationError) as exc_info:
        Operation.model_validate({'callbacks': [1]})
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'model_type',
            'loc': ('callbacks', 0),
            'msg': 'Input should be a valid dictionary or instance of PathItem',
            'input': 1,
            'ctx': {'class_name': 'PathItem'},
        }
    ]


def test_plain_basemodel_field():
    class Model(BaseModel):
        x: BaseModel

    class Model2(BaseModel):
        pass

    assert Model(x=Model2()).x == Model2()
    with pytest.raises(ValidationError) as exc_info:
        Model(x=1)
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'model_type',
            'loc': ('x',),
            'msg': 'Input should be a valid dictionary or instance of BaseModel',
            'input': 1,
            'ctx': {'class_name': 'BaseModel'},
        }
    ]


def test_invalid_forward_ref_model():
    """
    This test is to document the fact that forward refs to a type with the same name as that of a field
    can cause problems, and to demonstrate a way to work around this.
    """
    # The problem:
    if sys.version_info >= (3, 11):
        # See PR #8243, this was a RecursionError raised by Python, but is now caught on the Pydantic side
        error = errors.PydanticUserError
    else:
        error = TypeError
    with pytest.raises(error):

        class M(BaseModel):
            B: ForwardRef('B') = Field(default=None)

    # The solution:
    class A(BaseModel):
        B: ForwardRef('__types["B"]') = Field()  # F821

    assert A.model_fields['B'].annotation == ForwardRef('__types["B"]')  # F821
    A.model_rebuild(raise_errors=False)
    assert A.model_fields['B'].annotation == ForwardRef('__types["B"]')  # F821

    class B(BaseModel):
        pass

    class C(BaseModel):
        pass

    assert not A.__pydantic_complete__
    types = {'B': B}
    A.model_rebuild(_types_namespace={'__types': types})
    assert A.__pydantic_complete__

    assert A(B=B()).B == B()
    with pytest.raises(ValidationError) as exc_info:
        A(B=C())
    # insert_assert(exc_info.value.errors(include_url=False))
    assert exc_info.value.errors(include_url=False) == [
        {
            'type': 'model_type',
            'loc': ('B',),
            'msg': 'Input should be a valid dictionary or instance of B',
            'input': C(),
            'ctx': {'class_name': 'B'},
        }
    ]


def test_incomplete_superclass() -> None:
    class MyModel(BaseModel):
        sub_model: 'SubModel'

    assert not MyModel.__pydantic_fields_complete__
    assert not MyModel.__pydantic_complete__

    with pytest.raises(PydanticUndefinedAnnotation, match="name 'SubModel' is not defined"):
        MyModel.model_rebuild()

    class SubModel(MyModel):
        pass

    # SubModel is complete because it reinterprets the superclass's fields and finds 'SubModel' to match itself
    assert SubModel.__pydantic_fields_complete__
    assert SubModel.__pydantic_complete__

    # MyModel is still incomplete until it's rebuilt
    assert not MyModel.__pydantic_fields_complete__
    assert not MyModel.__pydantic_complete__

    MyModel.model_rebuild()

    assert MyModel.__pydantic_fields_complete__
    assert MyModel.__pydantic_complete__


@pytest.mark.parametrize(
    ('sequence_type', 'input_data', 'expected_error_type', 'expected_error_msg', 'expected_error_ctx'),
    [
        pytest.param(list[str], '1bc', 'list_type', 'Input should be a valid list', None, id='list[str]'),
        pytest.param(
            Sequence[str],
            '1bc',
            'sequence_str',
            "'str' instances are not allowed as a Sequence value",
            {'type_name': 'str'},
            id='Sequence[str]',
        ),
        pytest.param(
            Sequence[bytes],
            b'1bc',
            'sequence_str',
            "'bytes' instances are not allowed as a Sequence value",
            {'type_name': 'bytes'},
            id='Sequence[bytes]',
        ),
    ],
)
def test_sequences_str(sequence_type, input_data, expected_error_type, expected_error_msg, expected_error_ctx):
    input_sequence = [input_data[:1], input_data[1:]]
    expected_error = {
        'type': expected_error_type,
        'input': input_data,
        'loc': ('str_sequence',),
        'msg': expected_error_msg,
    }
    if expected_error_ctx is not None:
        expected_error.update(ctx=expected_error_ctx)

    class Model(BaseModel):
        str_sequence: sequence_type

    assert Model(str_sequence=input_sequence).str_sequence == input_sequence

    with pytest.raises(ValidationError) as e:
        Model(str_sequence=input_data)

    assert e.value.errors(include_url=False) == [expected_error]


def test_multiple_enums():
    """See https://github.com/pydantic/pydantic/issues/6270"""

    class MyEnum(Enum):
        a = auto()

    class MyModel(TypedDict):
        a: Optional[MyEnum]
        b: Optional[MyEnum]

    ta = TypeAdapter(MyModel)
    assert ta.validate_json('{"a": 1, "b": 1}') == {'a': MyEnum.a, 'b': MyEnum.a}


@pytest.mark.parametrize(
    ('literal_type', 'other_type', 'data', 'json_value', 'data_reversed', 'json_value_reversed'),
    [
        (Literal[False], str, False, 'false', False, 'false'),
        (Literal[True], str, True, 'true', True, 'true'),
        (Literal[False], str, 'abc', '"abc"', 'abc', '"abc"'),
        (Literal[False], int, False, 'false', False, 'false'),
        (Literal[True], int, True, 'true', True, 'true'),
        (Literal[False], int, 42, '42', 42, '42'),
    ],
)
def test_union_literal_with_other_type(literal_type, other_type, data, json_value, data_reversed, json_value_reversed):
    class Model(BaseModel):
        value: Union[literal_type, other_type]
        value_types_reversed: Union[other_type, literal_type]

    m = Model(value=data, value_types_reversed=data)
    assert m.model_dump() == {'value': data, 'value_types_reversed': data_reversed}
    assert m.model_dump_json() == f'{{"value":{json_value},"value_types_reversed":{json_value_reversed}}}'


def test_model_repr_before_validation():
    log = []

    class MyModel(BaseModel):
        x: int

        def __init__(self, **kwargs):
            log.append(f'before={self!r}')
            super().__init__(**kwargs)
            log.append(f'after={self!r}')

    m = MyModel(x='10')
    assert m.x == 10
    # insert_assert(log)
    assert log == ['before=MyModel()', 'after=MyModel(x=10)']


def test_custom_exception_handler():
    from traceback import TracebackException

    from pydantic import BaseModel

    traceback_exceptions = []

    class MyModel(BaseModel):
        name: str

    class CustomErrorCatcher:
        def __enter__(self):
            return None

        def __exit__(self, _exception_type, exception, exception_traceback):
            if exception is not None:
                traceback_exceptions.append(
                    TracebackException(
                        exc_type=type(exception),
                        exc_value=exception,
                        exc_traceback=exception_traceback,
                        capture_locals=True,
                    )
                )

                return True
            return False

    with CustomErrorCatcher():
        data = {'age': 'John Doe'}
        MyModel(**data)

    assert len(traceback_exceptions) == 1


def test_recursive_walk_fails_on_double_diamond_composition():
    class A(BaseModel):
        pass

    class B(BaseModel):
        a_1: A
        a_2: A

    class C(BaseModel):
        b: B

    class D(BaseModel):
        c_1: C
        c_2: C

    class E(BaseModel):
        c: C

    # This is just to check that above model contraption doesn't fail
    assert E(c=C(b=B(a_1=A(), a_2=A()))).model_dump() == {'c': {'b': {'a_1': {}, 'a_2': {}}}}


def test_recursive_root_models_in_discriminated_union():
    class Model1(BaseModel):
        kind: Literal['1'] = '1'
        two: Optional['Model2']

    class Model2(BaseModel):
        kind: Literal['2'] = '2'
        one: Optional[Model1]

    class Root1(RootModel[Model1]):
        @property
        def kind(self):
            # Ensures discriminated union validation works even with model instances
            return self.root.kind

    class Root2(RootModel[Model2]):
        @property
        def kind(self):
            # Ensures discriminated union validation works even with model instances
            return self.root.kind

    class Outer(BaseModel):
        a: Annotated[Union[Root1, Root2], Field(discriminator='kind')]
        b: Annotated[Union[Root1, Root2], Field(discriminator='kind')]

    validated = Outer.model_validate({'a': {'kind': '1', 'two': None}, 'b': {'kind': '2', 'one': None}})
    assert validated == Outer(a=Root1(root=Model1(two=None)), b=Root2(root=Model2(one=None)))

    # insert_assert(Outer.model_json_schema())
    assert Outer.model_json_schema() == {
        '$defs': {
            'Model1': {
                'properties': {
                    'kind': {'const': '1', 'default': '1', 'title': 'Kind', 'type': 'string'},
                    'two': {'anyOf': [{'$ref': '#/$defs/Model2'}, {'type': 'null'}]},
                },
                'required': ['two'],
                'title': 'Model1',
                'type': 'object',
            },
            'Model2': {
                'properties': {
                    'kind': {'const': '2', 'default': '2', 'title': 'Kind', 'type': 'string'},
                    'one': {'anyOf': [{'$ref': '#/$defs/Model1'}, {'type': 'null'}]},
                },
                'required': ['one'],
                'title': 'Model2',
                'type': 'object',
            },
            'Root1': {'$ref': '#/$defs/Model1', 'title': 'Root1'},
            'Root2': {'$ref': '#/$defs/Model2', 'title': 'Root2'},
        },
        'properties': {
            'a': {
                'discriminator': {'mapping': {'1': '#/$defs/Root1', '2': '#/$defs/Root2'}, 'propertyName': 'kind'},
                'oneOf': [{'$ref': '#/$defs/Root1'}, {'$ref': '#/$defs/Root2'}],
                'title': 'A',
            },
            'b': {
                'discriminator': {'mapping': {'1': '#/$defs/Root1', '2': '#/$defs/Root2'}, 'propertyName': 'kind'},
                'oneOf': [{'$ref': '#/$defs/Root1'}, {'$ref': '#/$defs/Root2'}],
                'title': 'B',
            },
        },
        'required': ['a', 'b'],
        'title': 'Outer',
        'type': 'object',
    }


def test_eq_with_cached_property():
    """
    Test BaseModel.__eq__ compatibility with functools.cached_property

    See GH-7444: https://github.com/pydantic/pydantic/issues/7444
    Previously, pydantic BaseModel.__eq__ compared the full __dict__ of
    model instances. This is not compatible with e.g. functools.cached_property,
    which caches the computed values in the instance's __dict__
    """

    class Model(BaseModel):
        attr: int

        @functools.cached_property
        def cached(self) -> int:
            return 0

    obj1 = Model(attr=1)
    obj2 = Model(attr=1)
    # ensure the instances are indeed equal before __dict__ mutations
    assert obj1 == obj2
    # This access to the cached_property has the side-effect of modifying obj1.__dict__
    # See functools.cached_property documentation and source code
    obj1.cached
    # Ensure the objects still compare equals after caching a property
    assert obj1 == obj2


def test_model_metaclass_on_other_class() -> None:
    """Test that `ModelMetaclass` can be used as a metaclass on an unrelated class.

    This is done by some libraries to offer compatibility between Pydantic versions.
    """

    class OtherClass(metaclass=ModelMetaclass):
        pass


@pytest.mark.skipif(sys.version_info < (3, 12), reason='requires Python 3.12+')
def test_nested_type_statement():
    # https://docs.python.org/3/reference/simple_stmts.html#type

    globs = {}
    exec(
        """
from pydantic import BaseModel
class A(BaseModel):
    type Int = int
    a: Int
""",
        globs,
    )
    A = globs['A']
    assert A(a=1).a == 1


def test_method_descriptors_default() -> None:
    class SomeModel(BaseModel):
        @staticmethod
        def default_int_factory() -> int: ...

        int_factory: Callable[[], int] = Field(default=default_int_factory)

    assert SomeModel.model_fields['int_factory'].default is SomeModel.default_int_factory


def test_setattr_handler_memo_does_not_inherit() -> None:
    class Model1(BaseModel):
        a: int

    class Model2(Model1):
        a: int

    m1 = Model1(a=1)
    m2 = Model2(a=10)

    assert not Model1.__pydantic_setattr_handlers__
    assert not Model2.__pydantic_setattr_handlers__

    m2.a = 11
    assert not Model1.__pydantic_setattr_handlers__
    assert 'a' in Model2.__pydantic_setattr_handlers__
    handler2 = Model2.__pydantic_setattr_handlers__['a']

    m1.a = 2
    assert 'a' in Model1.__pydantic_setattr_handlers__
    assert Model1.__pydantic_setattr_handlers__['a'] is handler2
    assert Model2.__pydantic_setattr_handlers__['a'] is handler2
    assert m1.a == 2 and m2.a == 11


def test_setattr_handler_does_not_memoize_unknown_field() -> None:
    class Model(BaseModel):
        a: int

    m = Model(a=1)
    with pytest.raises(ValueError, match='object has no field "unknown"'):
        m.unknown = 'x'
    assert not Model.__pydantic_setattr_handlers__
    m.a = 2
    assert 'a' in Model.__pydantic_setattr_handlers__


def test_setattr_handler_does_not_memoize_unknown_private_field() -> None:
    class Model(BaseModel):
        a: int
        _p: str

    m = Model(a=1)
    assert not Model.__pydantic_setattr_handlers__
    m.a = 2
    assert len(Model.__pydantic_setattr_handlers__) == 1
    m._unknown = 'x'
    assert len(Model.__pydantic_setattr_handlers__) == 1
    m._p = 'y'
    assert len(Model.__pydantic_setattr_handlers__) == 2


def test_setattr_handler_does_not_memoize_on_validate_assignment_field_failure() -> None:
    class Model(BaseModel, validate_assignment=True):
        a: int

    m = Model(a=1)
    with pytest.raises(ValidationError):
        m.unknown = 'x'
    with pytest.raises(ValidationError):
        m.a = 'y'
    assert not Model.__pydantic_setattr_handlers__
    m.a = 2
    assert 'a' in Model.__pydantic_setattr_handlers__


# The following 3 tests define a `__get_pydantic_core_schema__()` method on Pydantic models.
# This isn't explicitly supported and can lead to unexpected side effects, but are here
# to prevent potential regressions:


def test_get_pydantic_core_schema_on_referenceable_type() -> None:
    # This ensures that even if you define the method, it won't actually
    # be called twice and the cached definition will be used instead.
    # Note that what is important here is that the `Test` definition does
    # not raise a `LookupError` when calling the `handler` (see
    # `CallbackGetCoreSchemaHandler.__call__` calling `resolve_ref_schema`).
    counter = 0

    class Model(BaseModel):
        @classmethod
        def __get_pydantic_core_schema__(
            cls, source: type[BaseModel], handler: GetCoreSchemaHandler, /
        ) -> core_schema.CoreSchema:
            rv = handler(source)
            nonlocal counter
            counter += 1
            return rv

    counter = 0  # reset the counter to only account for the `Test` definition

    class Test(Model):
        t: 'Test'

    assert counter == 1


def test_repeated_custom_type() -> None:
    class Numeric(BaseModel):
        value: float

        @classmethod
        def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler) -> CoreSchema:
            return core_schema.no_info_before_validator_function(cls._validate, handler(source_type))

        @classmethod
        def _validate(cls, v: Any) -> Union[dict[str, Any], Self]:
            if isinstance(v, (str, float, int)):
                return cls(value=v)
            if isinstance(v, Numeric):
                return v
            if isinstance(v, dict):
                return v
            raise ValueError(f'Invalid value for {cls}: {v}')

    def is_positive(value: Numeric):
        assert value.value > 0.0, 'Must be positive'

    class OuterModel(BaseModel):
        x: Numeric
        y: Numeric
        z: Annotated[Numeric, AfterValidator(is_positive)]

    assert OuterModel(x=2, y=-1, z=1)

    with pytest.raises(ValidationError):
        OuterModel(x=2, y=-1, z=-1)


def test_get_pydantic_core_schema_noop() -> None:
    """https://github.com/pydantic/pydantic/issues/12096"""

    class Metadata(BaseModel):
        foo: int = 100

        @classmethod
        def __get_pydantic_core_schema__(cls, source_type, handler: GetCoreSchemaHandler) -> CoreSchema:
            return handler(source_type)

    class Model1(BaseModel):
        f: Annotated[str, Metadata()]

    assert isinstance(Model1.model_fields['f'].metadata[0], Metadata)
    assert Model1(f='test').f == 'test'

    class Model2(BaseModel):
        f1: Annotated[str, Metadata()]
        f2: Annotated[str, Metadata()] = 'f2'

    m2 = Model2(f1='f1')
    assert m2.f1 == 'f1'
    assert m2.f2 == 'f2'


def test_validator_and_serializer_not_reused_during_rebuild() -> None:
    # Make sure validators and serializers are deleted before model rebuild,
    # so that they don't end up being reused in pydantic-core (since we look
    # for `cls.__pydantic_validator/serializer__`).
    # This test makes the assertion on the serialization behavior.
    class Model(BaseModel):
        a: int

    Model.model_fields['a'].exclude = True
    Model.model_rebuild(force=True)

    m = Model(a=1)
    assert m.model_dump() == {}


@pytest.mark.filterwarnings('ignore:.*`__get_validators__`.*:DeprecationWarning')
def test_get_schema_on_classes_with_both_v1_and_v2_apis() -> None:
    class Model(BaseModel):
        a: int

        @model_validator(mode='after')
        def my_model_validator(self):
            return self

        @classmethod
        def __get_validators__(cls):
            raise AssertionError('This should not be called')


def test_model_fields_set_includes_extra_after_assignment():
    """Regression test for https://github.com/pydantic/pydantic/issues/11134.

    Extra fields set after initialization should be included in model_fields_set.
    """
    from pydantic import BaseModel, ConfigDict

    class Model(BaseModel):
        model_config = ConfigDict(extra='allow')
        field: int

    m = Model.model_validate({'field': 1, 'extra_at_init': 2})
    assert m.model_fields_set == {'field', 'extra_at_init'}

    m.extra_after_init = 3
    assert m.model_fields_set == {'field', 'extra_at_init', 'extra_after_init'}
    assert m.model_extra == {'extra_at_init': 2, 'extra_after_init': 3}
