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from enum import Enum
from typing import Any, Dict, FrozenSet, List, Literal, Optional, Set, Tuple, get_args
import pytest
from annotated_types import Len
from typing_extensions import Annotated
from pydantic import BaseModel
from pydantic.dataclasses import dataclass
from polyfactory.factories import DataclassFactory
from polyfactory.factories.pydantic_factory import ModelFactory
MIN_MAX_PARAMETERS = ((10, 15), (20, 25), (30, 40), (40, 50))
@pytest.mark.parametrize("type_", (List[int], Dict[int, int]))
@pytest.mark.parametrize("length", range(1, 10))
def test_annotated_type_collection_length(type_: type, length: int) -> None:
class Foo(BaseModel):
foo: Annotated[type_, Len(length)] # type: ignore
class FooFactory(ModelFactory):
__model__ = Foo
for _ in range(10):
foo = FooFactory.build()
assert len(foo.foo) == length, len(foo.foo)
@pytest.mark.parametrize("type_", (List, Set))
@pytest.mark.parametrize(("min_val", "max_val"), MIN_MAX_PARAMETERS)
def test_collection_length_with_list(min_val: int, max_val: int, type_: type) -> None:
@dataclass
class Foo:
foo: type_[int] # type: ignore
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__randomize_collection_length__ = True
__min_collection_length__ = min_val
__max_collection_length__ = max_val
foo = FooFactory.build()
assert len(foo.foo) >= min_val, len(foo.foo)
assert len(foo.foo) <= max_val, len(foo.foo)
def test_collection_length_with_set_collision() -> None:
@dataclass
class Foo:
foo: Set[int]
provider_int_values_reversed = (list(range(9)) + list(range(7, 15)))[::-1]
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__randomize_collection_length__ = True
__min_collection_length__ = 10
__max_collection_length__ = 10
@classmethod
def get_provider_map(cls) -> Dict[Any, Any]:
providers_map = super().get_provider_map()
providers_map[int] = lambda: provider_int_values_reversed.pop()
return providers_map
foo = FooFactory.build()
assert len(foo.foo) >= 10, len(foo.foo)
assert len(foo.foo) <= 15, len(foo.foo)
@pytest.mark.parametrize(("min_val", "max_val"), MIN_MAX_PARAMETERS)
def test_collection_length_with_tuple(min_val: int, max_val: int) -> None:
@dataclass
class Foo:
foo: Tuple[int, ...]
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__randomize_collection_length__ = True
__min_collection_length__ = min_val
__max_collection_length__ = max_val
foo = FooFactory.build()
assert len(foo.foo) >= min_val, len(foo.foo)
assert len(foo.foo) <= max_val, len(foo.foo)
@pytest.mark.parametrize(("min_val", "max_val"), MIN_MAX_PARAMETERS)
def test_collection_length_with_dict(min_val: int, max_val: int) -> None:
@dataclass
class Foo:
foo: Dict[int, int]
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__randomize_collection_length__ = True
__min_collection_length__ = min_val
__max_collection_length__ = max_val
foo = FooFactory.build()
assert len(foo.foo) >= min_val, len(foo.foo)
assert len(foo.foo) <= max_val, len(foo.foo)
@pytest.mark.parametrize(("min_val", "max_val"), MIN_MAX_PARAMETERS)
def test_collection_length_with_optional_not_allowed(min_val: int, max_val: int) -> None:
@dataclass
class Foo:
foo: Optional[List[int]]
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__allow_none_optionals__ = False
__randomize_collection_length__ = True
__min_collection_length__ = min_val
__max_collection_length__ = max_val
foo = FooFactory.build()
assert foo.foo is not None
assert len(foo.foo) >= min_val, len(foo.foo)
assert len(foo.foo) <= max_val, len(foo.foo)
@pytest.mark.parametrize(("min_val", "max_val"), MIN_MAX_PARAMETERS)
def test_collection_length_with_optional_allowed(min_val: int, max_val: int) -> None:
@dataclass
class Foo:
foo: Optional[List[int]]
class FooFactory(DataclassFactory[Foo]):
__model__ = Foo
__randomize_collection_length__ = True
__min_collection_length__ = min_val
__max_collection_length__ = max_val
for _ in range(10):
foo = FooFactory.build()
if foo.foo is None:
continue
assert len(foo.foo) >= min_val, len(foo.foo)
assert len(foo.foo) <= max_val, len(foo.foo)
@pytest.mark.parametrize("type_", (List, FrozenSet, Set))
@pytest.mark.parametrize("min_items", (0, 2, 4))
@pytest.mark.parametrize("max_inc", (0, 1, 4))
def test_collection_length_with_literal(type_: type, min_items: int, max_inc: int) -> None:
max_items = min_items + max_inc
literal_type = Literal["Dog", "Cat", "Monkey"]
@dataclass
class MyModel:
animal_collection: type_[literal_type] # type: ignore
class MyFactory(DataclassFactory):
__model__ = MyModel
__randomize_collection_length__ = True
__min_collection_length__ = min_items
__max_collection_length__ = max_items
result = MyFactory.build()
assert len(result.animal_collection) >= min(min_items, len(get_args(literal_type)))
assert len(result.animal_collection) <= max_items
@pytest.mark.parametrize("type_", (List, FrozenSet, Set))
@pytest.mark.parametrize("min_items", (0, 2, 4))
@pytest.mark.parametrize("max_inc", (0, 1, 4))
def test_collection_length_with_enum(type_: type, min_items: int, max_inc: int) -> None:
max_items = min_items + max_inc
class Animal(str, Enum):
DOG = "Dog"
CAT = "Cat"
MONKEY = "Monkey"
class MyModel(BaseModel):
animal_collection: type_[Animal] # type: ignore
class MyFactory(ModelFactory):
__model__ = MyModel
__randomize_collection_length__ = True
__min_collection_length__ = min_items
__max_collection_length__ = max_items
result = MyFactory.build()
assert len(result.animal_collection) >= min(min_items, len(Animal))
assert len(result.animal_collection) <= max_items
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