pydantic/tests/test_generics.py

import sys
from enum import Enum
from typing import Any, ClassVar, Dict, Generic, List, Optional, Tuple, Type, TypeVar, Union

import pytest

from pydantic import BaseModel, Field, ValidationError, root_validator, validator
from pydantic.generics import GenericModel, _generic_types_cache

skip_36 = pytest.mark.skipif(sys.version_info < (3, 7), reason='generics only supported for python 3.7 and above')


@skip_36
def test_generic_name():
    data_type = TypeVar('data_type')

    class Result(GenericModel, Generic[data_type]):
        data: data_type

    assert Result[List[int]].__name__ == 'Result[typing.List[int]]'


@skip_36
def test_double_parameterize_error():
    data_type = TypeVar('data_type')

    class Result(GenericModel, Generic[data_type]):
        data: data_type

    with pytest.raises(TypeError) as exc_info:
        Result[int][int]

    assert str(exc_info.value) == 'Cannot parameterize a concrete instantiation of a generic model'


@skip_36
def test_value_validation():
    T = TypeVar('T')

    class Response(GenericModel, Generic[T]):
        data: T

        @validator('data', each_item=True)
        def validate_value_nonzero(cls, v):
            if v == 0:
                raise ValueError('value is zero')
            return v

        @root_validator()
        def validate_sum(cls, values):
            if sum(values.get('data', {}).values()) > 5:
                raise ValueError('sum too large')
            return values

    assert Response[Dict[int, int]](data={1: '4'}).dict() == {'data': {1: 4}}
    with pytest.raises(ValidationError) as exc_info:
        Response[Dict[int, int]](data={1: 'a'})
    assert exc_info.value.errors() == [
        {'loc': ('data', 1), 'msg': 'value is not a valid integer', 'type': 'type_error.integer'}
    ]

    with pytest.raises(ValidationError) as exc_info:
        Response[Dict[int, int]](data={1: 0})
    assert exc_info.value.errors() == [{'loc': ('data', 1), 'msg': 'value is zero', 'type': 'value_error'}]

    with pytest.raises(ValidationError) as exc_info:
        Response[Dict[int, int]](data={1: 3, 2: 6})
    assert exc_info.value.errors() == [{'loc': ('__root__',), 'msg': 'sum too large', 'type': 'value_error'}]


@skip_36
def test_methods_are_inherited():
    class CustomGenericModel(GenericModel):
        def method(self):
            return self.data

    T = TypeVar('T')

    class Model(CustomGenericModel, Generic[T]):
        data: T

    instance = Model[int](data=1)

    assert instance.method() == 1


@skip_36
def test_config_is_inherited():
    class CustomGenericModel(GenericModel):
        class Config:
            allow_mutation = False

    T = TypeVar('T')

    class Model(CustomGenericModel, Generic[T]):
        data: T

    instance = Model[int](data=1)

    with pytest.raises(TypeError) as exc_info:
        instance.data = 2

    assert str(exc_info.value) == '"Model[int]" is immutable and does not support item assignment'


@skip_36
def test_default_argument():
    T = TypeVar('T')

    class Result(GenericModel, Generic[T]):
        data: T
        other: bool = True

    result = Result[int](data=1)
    assert result.other is True


@skip_36
def test_default_argument_for_typevar():
    T = TypeVar('T')

    class Result(GenericModel, Generic[T]):
        data: T = 4

    result = Result[int]()
    assert result.data == 4

    result = Result[float]()
    assert result.data == 4

    result = Result[int](data=1)
    assert result.data == 1


@skip_36
def test_classvar():
    T = TypeVar('T')

    class Result(GenericModel, Generic[T]):
        data: T
        other: ClassVar[int] = 1

    assert Result.other == 1
    assert Result[int].other == 1
    assert Result[int](data=1).other == 1
    assert 'other' not in Result.__fields__


@skip_36
def test_non_annotated_field():
    T = TypeVar('T')

    class Result(GenericModel, Generic[T]):
        data: T
        other = True

    assert 'other' in Result.__fields__
    assert 'other' in Result[int].__fields__

    result = Result[int](data=1)
    assert result.other is True


@skip_36
def test_must_inherit_from_generic():
    with pytest.raises(TypeError) as exc_info:

        class Result(GenericModel):
            pass

        Result[int]

    assert str(exc_info.value) == f'Type Result must inherit from typing.Generic before being parameterized'


@skip_36
def test_parameters_placed_on_generic():
    T = TypeVar('T')
    with pytest.raises(TypeError, match='Type parameters should be placed on typing.Generic, not GenericModel'):

        class Result(GenericModel[T]):
            pass


@skip_36
def test_parameters_must_be_typevar():
    with pytest.raises(TypeError, match='Type GenericModel must inherit from typing.Generic before being '):

        class Result(GenericModel[int]):
            pass


@skip_36
def test_subclass_can_be_genericized():
    T = TypeVar('T')

    class Result(GenericModel, Generic[T]):
        pass

    Result[T]


@skip_36
def test_parameter_count():
    T = TypeVar('T')
    S = TypeVar('S')

    class Model(GenericModel, Generic[T, S]):
        x: T
        y: S

    with pytest.raises(TypeError) as exc_info:
        Model[int, int, int]
    assert str(exc_info.value) == 'Too many parameters for Model; actual 3, expected 2'

    with pytest.raises(TypeError) as exc_info:
        Model[int]
    assert str(exc_info.value) == 'Too few parameters for Model; actual 1, expected 2'


@skip_36
def test_cover_cache():
    cache_size = len(_generic_types_cache)
    T = TypeVar('T')

    class Model(GenericModel, Generic[T]):
        x: T

    Model[int]  # adds both with-tuple and without-tuple version to cache
    assert len(_generic_types_cache) == cache_size + 2
    Model[int]  # uses the cache
    assert len(_generic_types_cache) == cache_size + 2


@skip_36
def test_generic_config():
    data_type = TypeVar('data_type')

    class Result(GenericModel, Generic[data_type]):
        data: data_type

        class Config:
            allow_mutation = False

    result = Result[int](data=1)
    assert result.data == 1
    with pytest.raises(TypeError):
        result.data = 2


@skip_36
def test_generic_instantiation_error():
    with pytest.raises(TypeError) as exc_info:
        GenericModel()
    assert str(exc_info.value) == 'Type GenericModel cannot be used without generic parameters, e.g. GenericModel[T]'


@skip_36
def test_parameterized_generic_instantiation_error():
    data_type = TypeVar('data_type')

    class Result(GenericModel, Generic[data_type]):
        data: data_type

    with pytest.raises(TypeError) as exc_info:
        Result(data=1)
    assert str(exc_info.value) == 'Type Result cannot be used without generic parameters, e.g. Result[T]'


@skip_36
def test_deep_generic():
    T = TypeVar('T')
    S = TypeVar('S')
    R = TypeVar('R')

    class OuterModel(GenericModel, Generic[T, S, R]):
        a: Dict[R, Optional[List[T]]]
        b: Optional[Union[S, R]]
        c: R
        d: float

    class InnerModel(GenericModel, Generic[T, R]):
        c: T
        d: R

    class NormalModel(BaseModel):
        e: int
        f: str

    inner_model = InnerModel[int, str]
    generic_model = OuterModel[inner_model, NormalModel, int]

    inner_models = [inner_model(c=1, d='a')]
    generic_model(a={1: inner_models, 2: None}, b=None, c=1, d=1.5)
    generic_model(a={}, b=NormalModel(e=1, f='a'), c=1, d=1.5)
    generic_model(a={}, b=1, c=1, d=1.5)


@skip_36
def test_enum_generic():
    T = TypeVar('T')

    class MyEnum(Enum):
        x = 1
        y = 2

    class Model(GenericModel, Generic[T]):
        enum: T

    Model[MyEnum](enum=MyEnum.x)
    Model[MyEnum](enum=2)


@skip_36
def test_generic():
    data_type = TypeVar('data_type')
    error_type = TypeVar('error_type')

    class Result(GenericModel, Generic[data_type, error_type]):
        data: Optional[List[data_type]]
        error: Optional[error_type]
        positive_number: int

        @validator('error', always=True)
        def validate_error(cls, v: Optional[error_type], values: Dict[str, Any]) -> Optional[error_type]:
            if values.get('data', None) is None and v is None:
                raise ValueError('Must provide data or error')
            if values.get('data', None) is not None and v is not None:
                raise ValueError('Must not provide both data and error')
            return v

        @validator('positive_number')
        def validate_positive_number(cls, v: int) -> int:
            if v < 0:
                raise ValueError
            return v

    class Error(BaseModel):
        message: str

    class Data(BaseModel):
        number: int
        text: str

    success1 = Result[Data, Error](data=[Data(number=1, text='a')], positive_number=1)
    assert success1.dict() == {'data': [{'number': 1, 'text': 'a'}], 'error': None, 'positive_number': 1}
    assert repr(success1) == "Result[Data, Error](data=[Data(number=1, text='a')], error=None, positive_number=1)"

    success2 = Result[Data, Error](error=Error(message='error'), positive_number=1)
    assert success2.dict() == {'data': None, 'error': {'message': 'error'}, 'positive_number': 1}
    assert repr(success2) == "Result[Data, Error](data=None, error=Error(message='error'), positive_number=1)"
    with pytest.raises(ValidationError) as exc_info:
        Result[Data, Error](error=Error(message='error'), positive_number=-1)
    assert exc_info.value.errors() == [{'loc': ('positive_number',), 'msg': '', 'type': 'value_error'}]

    with pytest.raises(ValidationError) as exc_info:
        Result[Data, Error](data=[Data(number=1, text='a')], error=Error(message='error'), positive_number=1)
    assert exc_info.value.errors() == [
        {'loc': ('error',), 'msg': 'Must not provide both data and error', 'type': 'value_error'}
    ]

    with pytest.raises(ValidationError) as exc_info:
        Result[Data, Error](data=[Data(number=1, text='a')], error=Error(message='error'), positive_number=1)
    assert exc_info.value.errors() == [
        {'loc': ('error',), 'msg': 'Must not provide both data and error', 'type': 'value_error'}
    ]


@skip_36
def test_alongside_concrete_generics():
    from pydantic.generics import GenericModel

    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        item: T
        metadata: Dict[str, Any]

    model = MyModel[int](item=1, metadata={})
    assert model.item == 1
    assert model.metadata == {}


@skip_36
def test_complex_nesting():
    from pydantic.generics import GenericModel

    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        item: List[Dict[Union[int, T], str]]

    item = [{1: 'a', 'a': 'a'}]
    model = MyModel[str](item=item)
    assert model.item == item


@skip_36
def test_required_value():
    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        a: int

    with pytest.raises(ValidationError) as exc_info:
        MyModel[int]()
    assert exc_info.value.errors() == [{'loc': ('a',), 'msg': 'field required', 'type': 'value_error.missing'}]


@skip_36
def test_optional_value():
    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        a: Optional[int] = 1

    model = MyModel[int]()
    assert model.dict() == {'a': 1}


@skip_36
def test_custom_schema():
    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        a: int = Field(1, description='Custom')

    schema = MyModel[int].schema()
    assert schema['properties']['a'].get('description') == 'Custom'


@skip_36
def test_custom_generic_naming():
    T = TypeVar('T')

    class MyModel(GenericModel, Generic[T]):
        value: Optional[T]

        @classmethod
        def __concrete_name__(cls: Type[Any], params: Tuple[Type[Any], ...]) -> str:
            param_names = [param.__name__ if hasattr(param, '__name__') else str(param) for param in params]
            title = param_names[0].title()
            return f'Optional{title}Wrapper'

    assert repr(MyModel[int](value=1)) == 'OptionalIntWrapper(value=1)'
    assert repr(MyModel[str](value=None)) == 'OptionalStrWrapper(value=None)'