Files
pydantic/tests/test_generics.py
T
Samuel Colvin c3098a30cf Consistent __repr__ and __str__ methods for all types (#884)
* Consistent __repr__ and __str__ methods for all types

* add change description

* devtools integration and feedback on repr methods

* fix Color repr

* tests for truncate

* add devtools section to docs

* tests for devtools

* ValidationError inheriting from Representation

* fix imports

* tweaks

* tweak docs

* exec_examples.py integration with __repr__ changes
2019-10-14 17:37:04 +01:00

441 lines
12 KiB
Python

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_must_be_typevar():
T = TypeVar('T')
with pytest.raises(TypeError) as exc_info:
class Result(GenericModel[T]):
pass
assert str(exc_info.value) == f'Type parameters should be placed on typing.Generic, not GenericModel'
@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)'