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from dataclasses import dataclass
from datetime import date, datetime
from typing import Any, Mapping
from mashumaro import DataClassDictMixin
from mashumaro.mixins.json import DataClassJSONMixin
from mashumaro.types import SerializableType
from tests.entities import MyGenericDataClass, SerializableTypeGenericList
@dataclass
class Foo[T](DataClassJSONMixin):
x: T
y: "Foo[Any] | None"
@dataclass
class Bar(Foo):
pass
@dataclass
class GenericSerializableType[T](SerializableType):
value: object
def _serialize(self):
return self.value
@classmethod
def _deserialize(cls, value):
return cls(value)
def test_one_generic():
@dataclass
class A[T]:
x: T
@dataclass
class B(A[datetime], DataClassDictMixin):
pass
obj = B(datetime(2021, 8, 15))
assert B.from_dict({"x": "2021-08-15T00:00:00"}) == obj
assert obj.to_dict() == {"x": "2021-08-15T00:00:00"}
def test_one_generic_list():
@dataclass
class A[T](list[T]):
x: list[T]
@dataclass
class B(A[datetime], DataClassDictMixin):
pass
obj = B(x=[datetime(2021, 8, 15)])
assert B.from_dict({"x": ["2021-08-15T00:00:00"]}) == obj
assert obj.to_dict() == {"x": ["2021-08-15T00:00:00"]}
def test_two_generics():
@dataclass
class A1[T]:
x: list[T]
@dataclass
class A2[T, S]:
y: Mapping[T, S]
@dataclass
class B(A1[datetime], A2[datetime, date], DataClassDictMixin):
pass
obj = B(
x=[datetime(2021, 8, 15), datetime(2021, 8, 16)],
y={datetime(2021, 8, 17): date(2021, 8, 18)},
)
dump = {
"x": ["2021-08-15T00:00:00", "2021-08-16T00:00:00"],
"y": {"2021-08-17T00:00:00": "2021-08-18"},
}
assert B.from_dict(dump) == obj
assert obj.to_dict() == dump
def test_partially_concrete_generic():
@dataclass
class A[T, S]:
x: Mapping[T, S]
@dataclass
class B[S](A[datetime, S], DataClassDictMixin):
pass
obj = B(x={datetime(2022, 11, 21): "3.14"})
assert B.from_dict({"x": {"2022-11-21T00:00:00": "3.14"}}) == obj
assert obj.to_dict() == {"x": {"2022-11-21T00:00:00": "3.14"}}
def test_partially_concrete_generic_with_bound():
@dataclass
class A[T, P: (Mapping[int, int], list[float])]:
x: Mapping[T, P]
@dataclass
class B[P: (Mapping[int, int], list[float])](
A[date, P], DataClassDictMixin
):
pass
obj1 = B(x={date(2022, 11, 21): {1: 2, 3: 4}})
assert B.from_dict({"x": {"2022-11-21": {"1": "2", "3": "4"}}}) == obj1
assert obj1.to_dict() == {"x": {"2022-11-21": {1: 2, 3: 4}}}
obj2 = B(x={date(2022, 11, 21): [1.1, 3.3]})
assert (
B.from_dict({"x": {"2022-11-21": {"1.1": "2.2", "3.3": "4.4"}}})
== obj2
)
assert obj2.to_dict() == {"x": {"2022-11-21": [1.1, 3.3]}}
obj3 = B(x={date(2022, 11, 21): [1.1, 2.2, 3.3, 4.4]})
assert (
B.from_dict({"x": {"2022-11-21": ["1.1", "2.2", "3.3", "4.4"]}})
== obj3
)
assert obj3.to_dict() == {"x": {"2022-11-21": [1.1, 2.2, 3.3, 4.4]}}
def test_concrete_generic_with_different_type_var():
@dataclass
class A[T]:
x: T
@dataclass
class B[P: (Mapping[int, int], list[float])](A[P], DataClassDictMixin):
pass
obj = B.from_dict({"x": {"1": "2", "3": "4"}})
assert obj == B(x={1: 2, 3: 4})
obj = B.from_dict({"x": {"1.1": "2.2", "3.3": "4.4"}})
assert obj == B(x=[1.1, 3.3])
obj = B.from_dict({"x": ["1.1", "2.2", "3.3", "4.4"]})
assert obj == B(x=[1.1, 2.2, 3.3, 4.4])
def test_loose_generic_info_with_any_type():
@dataclass
class A[T]:
x: T
@dataclass
class B(A, DataClassDictMixin):
pass
obj = B.from_dict({"x": {"1.1": "2.2", "3.3": "4.4"}})
assert obj == B(x={"1.1": "2.2", "3.3": "4.4"})
obj = B.from_dict({"x": ["1.1", "2.2", "3.3", "4.4"]})
assert obj == B(x=["1.1", "2.2", "3.3", "4.4"])
def test_loose_generic_info_with_bound():
@dataclass
class A[P: (Mapping[int, int], list[float])]:
x: P
@dataclass
class B(A, DataClassDictMixin):
pass
obj = B.from_dict({"x": {"1": "2", "3": "4"}})
assert obj == B(x={1: 2, 3: 4})
obj = B.from_dict({"x": {"1.1": "2.2", "3.3": "4.4"}})
assert obj == B(x=[1.1, 3.3])
obj = B.from_dict({"x": ["1.1", "2.2", "3.3", "4.4"]})
assert obj == B(x=[1.1, 2.2, 3.3, 4.4])
def test_loose_generic_info_in_first_generic():
@dataclass
class A[P: (Mapping[int, int], list[float])]:
x: P
@dataclass
class B(A):
pass
@dataclass
class C[P: (Mapping[int, int], list[float])](B):
y: P
@dataclass
class D(C[list[float]], DataClassDictMixin):
pass
obj = D.from_dict({"x": {"1": "2"}, "y": {"3.3": "4.4"}})
assert obj == D(x={1: 2}, y=[3.3])
obj = D.from_dict({"x": {"1.1": "2.2"}, "y": {"3.3": "4.4"}})
assert obj == D(x=[1.1], y=[3.3])
def test_not_dataclass_generic():
class MyGeneric[P: (Mapping[int, int], list[float]), T]:
pass
@dataclass
class GenericDataClass[P: (Mapping[int, int], list[float])]:
x: P
@dataclass
class DataClass[P: (Mapping[int, int], list[float]), T](
MyGeneric[P, T], GenericDataClass[P]
):
pass
@dataclass
class ConcreteDataClass(DataClass[list[float], float], DataClassDictMixin):
pass
obj = ConcreteDataClass.from_dict({"x": {"1": "2", "3": "4"}})
assert obj == ConcreteDataClass(x=[1.0, 3.0])
def test_generic_dataclass_as_field_type():
@dataclass
class DataClass(DataClassDictMixin):
date: MyGenericDataClass[date]
str: MyGenericDataClass[str]
obj = DataClass(
date=MyGenericDataClass(date(2021, 9, 14)),
str=MyGenericDataClass("2021-09-14"),
)
dictionary = {"date": {"x": "2021-09-14"}, "str": {"x": "2021-09-14"}}
assert DataClass.from_dict(dictionary) == obj
assert obj.to_dict() == dictionary
def test_serializable_type_generic_class():
@dataclass
class DataClass(DataClassDictMixin):
x: SerializableTypeGenericList[str]
obj = DataClass(SerializableTypeGenericList(["a", "b", "c"]))
assert DataClass.from_dict({"x": ["a", "b", "c"]}) == obj
assert obj.to_dict() == {"x": ["a", "b", "c"]}
def test_self_referenced_generic_no_max_recursion_error():
obj = Bar(42, Foo(33, None))
assert obj.to_dict() == {"x": 42, "y": {"x": 33, "y": None}}
assert Bar.from_dict({"x": 42, "y": {"x": 33, "y": None}}) == obj
assert obj.to_json() == '{"x": 42, "y": {"x": 33, "y": null}}'
assert Bar.from_json('{"x": 42, "y": {"x": 33, "y": null}}') == obj
# Regression test for https://github.com/Fatal1ty/mashumaro/issues/274.
def test_generic_serializable_type_getitem():
@dataclass
class DataClass(DataClassDictMixin):
# Simply specializing the type would lead to an AttributeError.
x: GenericSerializableType[int]
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