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1017 lines (737 loc) · 28.8 KB
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import json
from typing import TYPE_CHECKING, Any, Dict, List, Union, Iterable, Optional, cast
from datetime import datetime, timezone
from collections import deque
from typing_extensions import Literal, Annotated, TypedDict, TypeAliasType
import pytest
import pydantic
from pydantic import Field
from unlayer._utils import PropertyInfo
from unlayer._compat import PYDANTIC_V1, parse_obj, model_dump, model_json
from unlayer._models import DISCRIMINATOR_CACHE, BaseModel, EagerIterable, construct_type
class BasicModel(BaseModel):
foo: str
@pytest.mark.parametrize("value", ["hello", 1], ids=["correct type", "mismatched"])
def test_basic(value: object) -> None:
m = BasicModel.construct(foo=value)
assert m.foo == value
def test_directly_nested_model() -> None:
class NestedModel(BaseModel):
nested: BasicModel
m = NestedModel.construct(nested={"foo": "Foo!"})
assert m.nested.foo == "Foo!"
# mismatched types
m = NestedModel.construct(nested="hello!")
assert cast(Any, m.nested) == "hello!"
def test_optional_nested_model() -> None:
class NestedModel(BaseModel):
nested: Optional[BasicModel]
m1 = NestedModel.construct(nested=None)
assert m1.nested is None
m2 = NestedModel.construct(nested={"foo": "bar"})
assert m2.nested is not None
assert m2.nested.foo == "bar"
# mismatched types
m3 = NestedModel.construct(nested={"foo"})
assert isinstance(cast(Any, m3.nested), set)
assert cast(Any, m3.nested) == {"foo"}
def test_list_nested_model() -> None:
class NestedModel(BaseModel):
nested: List[BasicModel]
m = NestedModel.construct(nested=[{"foo": "bar"}, {"foo": "2"}])
assert m.nested is not None
assert isinstance(m.nested, list)
assert len(m.nested) == 2
assert m.nested[0].foo == "bar"
assert m.nested[1].foo == "2"
# mismatched types
m = NestedModel.construct(nested=True)
assert cast(Any, m.nested) is True
m = NestedModel.construct(nested=[False])
assert cast(Any, m.nested) == [False]
def test_optional_list_nested_model() -> None:
class NestedModel(BaseModel):
nested: Optional[List[BasicModel]]
m1 = NestedModel.construct(nested=[{"foo": "bar"}, {"foo": "2"}])
assert m1.nested is not None
assert isinstance(m1.nested, list)
assert len(m1.nested) == 2
assert m1.nested[0].foo == "bar"
assert m1.nested[1].foo == "2"
m2 = NestedModel.construct(nested=None)
assert m2.nested is None
# mismatched types
m3 = NestedModel.construct(nested={1})
assert cast(Any, m3.nested) == {1}
m4 = NestedModel.construct(nested=[False])
assert cast(Any, m4.nested) == [False]
def test_list_optional_items_nested_model() -> None:
class NestedModel(BaseModel):
nested: List[Optional[BasicModel]]
m = NestedModel.construct(nested=[None, {"foo": "bar"}])
assert m.nested is not None
assert isinstance(m.nested, list)
assert len(m.nested) == 2
assert m.nested[0] is None
assert m.nested[1] is not None
assert m.nested[1].foo == "bar"
# mismatched types
m3 = NestedModel.construct(nested="foo")
assert cast(Any, m3.nested) == "foo"
m4 = NestedModel.construct(nested=[False])
assert cast(Any, m4.nested) == [False]
def test_list_mismatched_type() -> None:
class NestedModel(BaseModel):
nested: List[str]
m = NestedModel.construct(nested=False)
assert cast(Any, m.nested) is False
def test_raw_dictionary() -> None:
class NestedModel(BaseModel):
nested: Dict[str, str]
m = NestedModel.construct(nested={"hello": "world"})
assert m.nested == {"hello": "world"}
# mismatched types
m = NestedModel.construct(nested=False)
assert cast(Any, m.nested) is False
def test_nested_dictionary_model() -> None:
class NestedModel(BaseModel):
nested: Dict[str, BasicModel]
m = NestedModel.construct(nested={"hello": {"foo": "bar"}})
assert isinstance(m.nested, dict)
assert m.nested["hello"].foo == "bar"
# mismatched types
m = NestedModel.construct(nested={"hello": False})
assert cast(Any, m.nested["hello"]) is False
def test_unknown_fields() -> None:
m1 = BasicModel.construct(foo="foo", unknown=1)
assert m1.foo == "foo"
assert cast(Any, m1).unknown == 1
m2 = BasicModel.construct(foo="foo", unknown={"foo_bar": True})
assert m2.foo == "foo"
assert cast(Any, m2).unknown == {"foo_bar": True}
assert model_dump(m2) == {"foo": "foo", "unknown": {"foo_bar": True}}
def test_strict_validation_unknown_fields() -> None:
class Model(BaseModel):
foo: str
model = parse_obj(Model, dict(foo="hello!", user="Robert"))
assert model.foo == "hello!"
assert cast(Any, model).user == "Robert"
assert model_dump(model) == {"foo": "hello!", "user": "Robert"}
def test_aliases() -> None:
class Model(BaseModel):
my_field: int = Field(alias="myField")
m = Model.construct(myField=1)
assert m.my_field == 1
# mismatched types
m = Model.construct(myField={"hello": False})
assert cast(Any, m.my_field) == {"hello": False}
def test_repr() -> None:
model = BasicModel(foo="bar")
assert str(model) == "BasicModel(foo='bar')"
assert repr(model) == "BasicModel(foo='bar')"
def test_repr_nested_model() -> None:
class Child(BaseModel):
name: str
age: int
class Parent(BaseModel):
name: str
child: Child
model = Parent(name="Robert", child=Child(name="Foo", age=5))
assert str(model) == "Parent(name='Robert', child=Child(name='Foo', age=5))"
assert repr(model) == "Parent(name='Robert', child=Child(name='Foo', age=5))"
def test_optional_list() -> None:
class Submodel(BaseModel):
name: str
class Model(BaseModel):
items: Optional[List[Submodel]]
m = Model.construct(items=None)
assert m.items is None
m = Model.construct(items=[])
assert m.items == []
m = Model.construct(items=[{"name": "Robert"}])
assert m.items is not None
assert len(m.items) == 1
assert m.items[0].name == "Robert"
def test_nested_union_of_models() -> None:
class Submodel1(BaseModel):
bar: bool
class Submodel2(BaseModel):
thing: str
class Model(BaseModel):
foo: Union[Submodel1, Submodel2]
m = Model.construct(foo={"thing": "hello"})
assert isinstance(m.foo, Submodel2)
assert m.foo.thing == "hello"
def test_nested_union_of_mixed_types() -> None:
class Submodel1(BaseModel):
bar: bool
class Model(BaseModel):
foo: Union[Submodel1, Literal[True], Literal["CARD_HOLDER"]]
m = Model.construct(foo=True)
assert m.foo is True
m = Model.construct(foo="CARD_HOLDER")
assert m.foo == "CARD_HOLDER"
m = Model.construct(foo={"bar": False})
assert isinstance(m.foo, Submodel1)
assert m.foo.bar is False
def test_nested_union_multiple_variants() -> None:
class Submodel1(BaseModel):
bar: bool
class Submodel2(BaseModel):
thing: str
class Submodel3(BaseModel):
foo: int
class Model(BaseModel):
foo: Union[Submodel1, Submodel2, None, Submodel3]
m = Model.construct(foo={"thing": "hello"})
assert isinstance(m.foo, Submodel2)
assert m.foo.thing == "hello"
m = Model.construct(foo=None)
assert m.foo is None
m = Model.construct()
assert m.foo is None
m = Model.construct(foo={"foo": "1"})
assert isinstance(m.foo, Submodel3)
assert m.foo.foo == 1
def test_nested_union_invalid_data() -> None:
class Submodel1(BaseModel):
level: int
class Submodel2(BaseModel):
name: str
class Model(BaseModel):
foo: Union[Submodel1, Submodel2]
m = Model.construct(foo=True)
assert cast(bool, m.foo) is True
m = Model.construct(foo={"name": 3})
if PYDANTIC_V1:
assert isinstance(m.foo, Submodel2)
assert m.foo.name == "3"
else:
assert isinstance(m.foo, Submodel1)
assert m.foo.name == 3 # type: ignore
def test_list_of_unions() -> None:
class Submodel1(BaseModel):
level: int
class Submodel2(BaseModel):
name: str
class Model(BaseModel):
items: List[Union[Submodel1, Submodel2]]
m = Model.construct(items=[{"level": 1}, {"name": "Robert"}])
assert len(m.items) == 2
assert isinstance(m.items[0], Submodel1)
assert m.items[0].level == 1
assert isinstance(m.items[1], Submodel2)
assert m.items[1].name == "Robert"
m = Model.construct(items=[{"level": -1}, 156])
assert len(m.items) == 2
assert isinstance(m.items[0], Submodel1)
assert m.items[0].level == -1
assert cast(Any, m.items[1]) == 156
def test_union_of_lists() -> None:
class SubModel1(BaseModel):
level: int
class SubModel2(BaseModel):
name: str
class Model(BaseModel):
items: Union[List[SubModel1], List[SubModel2]]
# with one valid entry
m = Model.construct(items=[{"name": "Robert"}])
assert len(m.items) == 1
assert isinstance(m.items[0], SubModel2)
assert m.items[0].name == "Robert"
# with two entries pointing to different types
m = Model.construct(items=[{"level": 1}, {"name": "Robert"}])
assert len(m.items) == 2
assert isinstance(m.items[0], SubModel1)
assert m.items[0].level == 1
assert isinstance(m.items[1], SubModel1)
assert cast(Any, m.items[1]).name == "Robert"
# with two entries pointing to *completely* different types
m = Model.construct(items=[{"level": -1}, 156])
assert len(m.items) == 2
assert isinstance(m.items[0], SubModel1)
assert m.items[0].level == -1
assert cast(Any, m.items[1]) == 156
def test_dict_of_union() -> None:
class SubModel1(BaseModel):
name: str
class SubModel2(BaseModel):
foo: str
class Model(BaseModel):
data: Dict[str, Union[SubModel1, SubModel2]]
m = Model.construct(data={"hello": {"name": "there"}, "foo": {"foo": "bar"}})
assert len(list(m.data.keys())) == 2
assert isinstance(m.data["hello"], SubModel1)
assert m.data["hello"].name == "there"
assert isinstance(m.data["foo"], SubModel2)
assert m.data["foo"].foo == "bar"
# TODO: test mismatched type
def test_double_nested_union() -> None:
class SubModel1(BaseModel):
name: str
class SubModel2(BaseModel):
bar: str
class Model(BaseModel):
data: Dict[str, List[Union[SubModel1, SubModel2]]]
m = Model.construct(data={"foo": [{"bar": "baz"}, {"name": "Robert"}]})
assert len(m.data["foo"]) == 2
entry1 = m.data["foo"][0]
assert isinstance(entry1, SubModel2)
assert entry1.bar == "baz"
entry2 = m.data["foo"][1]
assert isinstance(entry2, SubModel1)
assert entry2.name == "Robert"
# TODO: test mismatched type
def test_union_of_dict() -> None:
class SubModel1(BaseModel):
name: str
class SubModel2(BaseModel):
foo: str
class Model(BaseModel):
data: Union[Dict[str, SubModel1], Dict[str, SubModel2]]
m = Model.construct(data={"hello": {"name": "there"}, "foo": {"foo": "bar"}})
assert len(list(m.data.keys())) == 2
assert isinstance(m.data["hello"], SubModel1)
assert m.data["hello"].name == "there"
assert isinstance(m.data["foo"], SubModel1)
assert cast(Any, m.data["foo"]).foo == "bar"
def test_iso8601_datetime() -> None:
class Model(BaseModel):
created_at: datetime
expected = datetime(2019, 12, 27, 18, 11, 19, 117000, tzinfo=timezone.utc)
if PYDANTIC_V1:
expected_json = '{"created_at": "2019-12-27T18:11:19.117000+00:00"}'
else:
expected_json = '{"created_at":"2019-12-27T18:11:19.117000Z"}'
model = Model.construct(created_at="2019-12-27T18:11:19.117Z")
assert model.created_at == expected
assert model_json(model) == expected_json
model = parse_obj(Model, dict(created_at="2019-12-27T18:11:19.117Z"))
assert model.created_at == expected
assert model_json(model) == expected_json
def test_does_not_coerce_int() -> None:
class Model(BaseModel):
bar: int
assert Model.construct(bar=1).bar == 1
assert Model.construct(bar=10.9).bar == 10.9
assert Model.construct(bar="19").bar == "19" # type: ignore[comparison-overlap]
assert Model.construct(bar=False).bar is False
def test_int_to_float_safe_conversion() -> None:
class Model(BaseModel):
float_field: float
m = Model.construct(float_field=10)
assert m.float_field == 10.0
assert isinstance(m.float_field, float)
m = Model.construct(float_field=10.12)
assert m.float_field == 10.12
assert isinstance(m.float_field, float)
# number too big
m = Model.construct(float_field=2**53 + 1)
assert m.float_field == 2**53 + 1
assert isinstance(m.float_field, int)
def test_deprecated_alias() -> None:
class Model(BaseModel):
resource_id: str = Field(alias="model_id")
@property
def model_id(self) -> str:
return self.resource_id
m = Model.construct(model_id="id")
assert m.model_id == "id"
assert m.resource_id == "id"
assert m.resource_id is m.model_id
m = parse_obj(Model, {"model_id": "id"})
assert m.model_id == "id"
assert m.resource_id == "id"
assert m.resource_id is m.model_id
def test_omitted_fields() -> None:
class Model(BaseModel):
resource_id: Optional[str] = None
m = Model.construct()
assert m.resource_id is None
assert "resource_id" not in m.model_fields_set
m = Model.construct(resource_id=None)
assert m.resource_id is None
assert "resource_id" in m.model_fields_set
m = Model.construct(resource_id="foo")
assert m.resource_id == "foo"
assert "resource_id" in m.model_fields_set
def test_to_dict() -> None:
class Model(BaseModel):
foo: Optional[str] = Field(alias="FOO", default=None)
m = Model(FOO="hello")
assert m.to_dict() == {"FOO": "hello"}
assert m.to_dict(use_api_names=False) == {"foo": "hello"}
m2 = Model()
assert m2.to_dict() == {}
assert m2.to_dict(exclude_unset=False) == {"FOO": None}
assert m2.to_dict(exclude_unset=False, exclude_none=True) == {}
assert m2.to_dict(exclude_unset=False, exclude_defaults=True) == {}
m3 = Model(FOO=None)
assert m3.to_dict() == {"FOO": None}
assert m3.to_dict(exclude_none=True) == {}
assert m3.to_dict(exclude_defaults=True) == {}
class Model2(BaseModel):
created_at: datetime
time_str = "2024-03-21T11:39:01.275859"
m4 = Model2.construct(created_at=time_str)
assert m4.to_dict(mode="python") == {"created_at": datetime.fromisoformat(time_str)}
assert m4.to_dict(mode="json") == {"created_at": time_str}
if PYDANTIC_V1:
with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"):
m.to_dict(warnings=False)
def test_forwards_compat_model_dump_method() -> None:
class Model(BaseModel):
foo: Optional[str] = Field(alias="FOO", default=None)
m = Model(FOO="hello")
assert m.model_dump() == {"foo": "hello"}
assert m.model_dump(include={"bar"}) == {}
assert m.model_dump(exclude={"foo"}) == {}
assert m.model_dump(by_alias=True) == {"FOO": "hello"}
m2 = Model()
assert m2.model_dump() == {"foo": None}
assert m2.model_dump(exclude_unset=True) == {}
assert m2.model_dump(exclude_none=True) == {}
assert m2.model_dump(exclude_defaults=True) == {}
m3 = Model(FOO=None)
assert m3.model_dump() == {"foo": None}
assert m3.model_dump(exclude_none=True) == {}
if PYDANTIC_V1:
with pytest.raises(ValueError, match="round_trip is only supported in Pydantic v2"):
m.model_dump(round_trip=True)
with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"):
m.model_dump(warnings=False)
def test_compat_method_no_error_for_warnings() -> None:
class Model(BaseModel):
foo: Optional[str]
m = Model(foo="hello")
assert isinstance(model_dump(m, warnings=False), dict)
def test_to_json() -> None:
class Model(BaseModel):
foo: Optional[str] = Field(alias="FOO", default=None)
m = Model(FOO="hello")
assert json.loads(m.to_json()) == {"FOO": "hello"}
assert json.loads(m.to_json(use_api_names=False)) == {"foo": "hello"}
if PYDANTIC_V1:
assert m.to_json(indent=None) == '{"FOO": "hello"}'
else:
assert m.to_json(indent=None) == '{"FOO":"hello"}'
m2 = Model()
assert json.loads(m2.to_json()) == {}
assert json.loads(m2.to_json(exclude_unset=False)) == {"FOO": None}
assert json.loads(m2.to_json(exclude_unset=False, exclude_none=True)) == {}
assert json.loads(m2.to_json(exclude_unset=False, exclude_defaults=True)) == {}
m3 = Model(FOO=None)
assert json.loads(m3.to_json()) == {"FOO": None}
assert json.loads(m3.to_json(exclude_none=True)) == {}
if PYDANTIC_V1:
with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"):
m.to_json(warnings=False)
def test_forwards_compat_model_dump_json_method() -> None:
class Model(BaseModel):
foo: Optional[str] = Field(alias="FOO", default=None)
m = Model(FOO="hello")
assert json.loads(m.model_dump_json()) == {"foo": "hello"}
assert json.loads(m.model_dump_json(include={"bar"})) == {}
assert json.loads(m.model_dump_json(include={"foo"})) == {"foo": "hello"}
assert json.loads(m.model_dump_json(by_alias=True)) == {"FOO": "hello"}
assert m.model_dump_json(indent=2) == '{\n "foo": "hello"\n}'
m2 = Model()
assert json.loads(m2.model_dump_json()) == {"foo": None}
assert json.loads(m2.model_dump_json(exclude_unset=True)) == {}
assert json.loads(m2.model_dump_json(exclude_none=True)) == {}
assert json.loads(m2.model_dump_json(exclude_defaults=True)) == {}
m3 = Model(FOO=None)
assert json.loads(m3.model_dump_json()) == {"foo": None}
assert json.loads(m3.model_dump_json(exclude_none=True)) == {}
if PYDANTIC_V1:
with pytest.raises(ValueError, match="round_trip is only supported in Pydantic v2"):
m.model_dump_json(round_trip=True)
with pytest.raises(ValueError, match="warnings is only supported in Pydantic v2"):
m.model_dump_json(warnings=False)
def test_type_compat() -> None:
# our model type can be assigned to Pydantic's model type
def takes_pydantic(model: pydantic.BaseModel) -> None: # noqa: ARG001
...
class OurModel(BaseModel):
foo: Optional[str] = None
takes_pydantic(OurModel())
def test_annotated_types() -> None:
class Model(BaseModel):
value: str
m = construct_type(
value={"value": "foo"},
type_=cast(Any, Annotated[Model, "random metadata"]),
)
assert isinstance(m, Model)
assert m.value == "foo"
def test_discriminated_unions_invalid_data() -> None:
class A(BaseModel):
type: Literal["a"]
data: str
class B(BaseModel):
type: Literal["b"]
data: int
m = construct_type(
value={"type": "b", "data": "foo"},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, B)
assert m.type == "b"
assert m.data == "foo" # type: ignore[comparison-overlap]
m = construct_type(
value={"type": "a", "data": 100},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, A)
assert m.type == "a"
if PYDANTIC_V1:
# pydantic v1 automatically converts inputs to strings
# if the expected type is a str
assert m.data == "100"
else:
assert m.data == 100 # type: ignore[comparison-overlap]
def test_discriminated_unions_unknown_variant() -> None:
class A(BaseModel):
type: Literal["a"]
data: str
class B(BaseModel):
type: Literal["b"]
data: int
m = construct_type(
value={"type": "c", "data": None, "new_thing": "bar"},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]),
)
# just chooses the first variant
assert isinstance(m, A)
assert m.type == "c" # type: ignore[comparison-overlap]
assert m.data == None # type: ignore[unreachable]
assert m.new_thing == "bar"
def test_discriminated_unions_invalid_data_nested_unions() -> None:
class A(BaseModel):
type: Literal["a"]
data: str
class B(BaseModel):
type: Literal["b"]
data: int
class C(BaseModel):
type: Literal["c"]
data: bool
m = construct_type(
value={"type": "b", "data": "foo"},
type_=cast(Any, Annotated[Union[Union[A, B], C], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, B)
assert m.type == "b"
assert m.data == "foo" # type: ignore[comparison-overlap]
m = construct_type(
value={"type": "c", "data": "foo"},
type_=cast(Any, Annotated[Union[Union[A, B], C], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, C)
assert m.type == "c"
assert m.data == "foo" # type: ignore[comparison-overlap]
def test_discriminated_unions_with_aliases_invalid_data() -> None:
class A(BaseModel):
foo_type: Literal["a"] = Field(alias="type")
data: str
class B(BaseModel):
foo_type: Literal["b"] = Field(alias="type")
data: int
m = construct_type(
value={"type": "b", "data": "foo"},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="foo_type")]),
)
assert isinstance(m, B)
assert m.foo_type == "b"
assert m.data == "foo" # type: ignore[comparison-overlap]
m = construct_type(
value={"type": "a", "data": 100},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="foo_type")]),
)
assert isinstance(m, A)
assert m.foo_type == "a"
if PYDANTIC_V1:
# pydantic v1 automatically converts inputs to strings
# if the expected type is a str
assert m.data == "100"
else:
assert m.data == 100 # type: ignore[comparison-overlap]
def test_discriminated_unions_overlapping_discriminators_invalid_data() -> None:
class A(BaseModel):
type: Literal["a"]
data: bool
class B(BaseModel):
type: Literal["a"]
data: int
m = construct_type(
value={"type": "a", "data": "foo"},
type_=cast(Any, Annotated[Union[A, B], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, B)
assert m.type == "a"
assert m.data == "foo" # type: ignore[comparison-overlap]
def test_discriminated_unions_invalid_data_uses_cache() -> None:
class A(BaseModel):
type: Literal["a"]
data: str
class B(BaseModel):
type: Literal["b"]
data: int
UnionType = cast(Any, Union[A, B])
assert not DISCRIMINATOR_CACHE.get(UnionType)
m = construct_type(
value={"type": "b", "data": "foo"}, type_=cast(Any, Annotated[UnionType, PropertyInfo(discriminator="type")])
)
assert isinstance(m, B)
assert m.type == "b"
assert m.data == "foo" # type: ignore[comparison-overlap]
discriminator = DISCRIMINATOR_CACHE.get(UnionType)
assert discriminator is not None
m = construct_type(
value={"type": "b", "data": "foo"}, type_=cast(Any, Annotated[UnionType, PropertyInfo(discriminator="type")])
)
assert isinstance(m, B)
assert m.type == "b"
assert m.data == "foo" # type: ignore[comparison-overlap]
# if the discriminator details object stays the same between invocations then
# we hit the cache
assert DISCRIMINATOR_CACHE.get(UnionType) is discriminator
@pytest.mark.skipif(PYDANTIC_V1, reason="TypeAliasType is not supported in Pydantic v1")
def test_type_alias_type() -> None:
Alias = TypeAliasType("Alias", str) # pyright: ignore
class Model(BaseModel):
alias: Alias
union: Union[int, Alias]
m = construct_type(value={"alias": "foo", "union": "bar"}, type_=Model)
assert isinstance(m, Model)
assert isinstance(m.alias, str)
assert m.alias == "foo"
assert isinstance(m.union, str)
assert m.union == "bar"
@pytest.mark.skipif(PYDANTIC_V1, reason="TypeAliasType is not supported in Pydantic v1")
def test_field_named_cls() -> None:
class Model(BaseModel):
cls: str
m = construct_type(value={"cls": "foo"}, type_=Model)
assert isinstance(m, Model)
assert isinstance(m.cls, str)
def test_discriminated_union_case() -> None:
class A(BaseModel):
type: Literal["a"]
data: bool
class B(BaseModel):
type: Literal["b"]
data: List[Union[A, object]]
class ModelA(BaseModel):
type: Literal["modelA"]
data: int
class ModelB(BaseModel):
type: Literal["modelB"]
required: str
data: Union[A, B]
# when constructing ModelA | ModelB, value data doesn't match ModelB exactly - missing `required`
m = construct_type(
value={"type": "modelB", "data": {"type": "a", "data": True}},
type_=cast(Any, Annotated[Union[ModelA, ModelB], PropertyInfo(discriminator="type")]),
)
assert isinstance(m, ModelB)
def test_nested_discriminated_union() -> None:
class InnerType1(BaseModel):
type: Literal["type_1"]
class InnerModel(BaseModel):
inner_value: str
class InnerType2(BaseModel):
type: Literal["type_2"]
some_inner_model: InnerModel
class Type1(BaseModel):
base_type: Literal["base_type_1"]
value: Annotated[
Union[
InnerType1,
InnerType2,
],
PropertyInfo(discriminator="type"),
]
class Type2(BaseModel):
base_type: Literal["base_type_2"]
T = Annotated[
Union[
Type1,
Type2,
],
PropertyInfo(discriminator="base_type"),
]
model = construct_type(
type_=T,
value={
"base_type": "base_type_1",
"value": {
"type": "type_2",
},
},
)
assert isinstance(model, Type1)
assert isinstance(model.value, InnerType2)
@pytest.mark.skipif(PYDANTIC_V1, reason="this is only supported in pydantic v2 for now")
def test_extra_properties() -> None:
class Item(BaseModel):
prop: int
class Model(BaseModel):
__pydantic_extra__: Dict[str, Item] = Field(init=False) # pyright: ignore[reportIncompatibleVariableOverride]
other: str
if TYPE_CHECKING:
def __getattr__(self, attr: str) -> Item: ...
model = construct_type(
type_=Model,
value={
"a": {"prop": 1},
"other": "foo",
},
)
assert isinstance(model, Model)
assert model.a.prop == 1
assert isinstance(model.a, Item)
assert model.other == "foo"
# NOTE: Workaround for Pydantic Iterable behavior.
# Iterable fields are replaced with a ValidatorIterator and may be consumed
# during serialization, which can cause subsequent dumps to return empty data.
# See: https://github.com/pydantic/pydantic/issues/9541
@pytest.mark.parametrize(
"data, expected_validated",
[
([1, 2, 3], [1, 2, 3]),
((1, 2, 3), (1, 2, 3)),
(set([1, 2, 3]), set([1, 2, 3])),
(iter([1, 2, 3]), [1, 2, 3]),
([], []),
((x for x in [1, 2, 3]), [1, 2, 3]),
(map(lambda x: x, [1, 2, 3]), [1, 2, 3]),
(frozenset([1, 2, 3]), frozenset([1, 2, 3])),
(deque([1, 2, 3]), deque([1, 2, 3])),
],
ids=["list", "tuple", "set", "iterator", "empty", "generator", "map", "frozenset", "deque"],
)
@pytest.mark.skipif(PYDANTIC_V1, reason="this is only supported in pydantic v2")
def test_iterable_construction(data: Iterable[int], expected_validated: Iterable[int]) -> None:
class TypeWithIterable(TypedDict):
items: EagerIterable[int]
class Model(BaseModel):
data: TypeWithIterable
m = Model.model_validate({"data": {"items": data}})
assert m.data["items"] == expected_validated
# Verify repeated dumps don't lose data (the original bug)
assert m.model_dump()["data"]["items"] == list(expected_validated)
assert m.model_dump()["data"]["items"] == list(expected_validated)