def test_construct_schema_union():
def fun(x: Union[int, str]):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({"x": 1}).to_native() == {"x": 1}
assert model_type({"x": "hi"}).to_native() == {"x": "hi"}
def test_construct_schema_numpy():
def fun(x: np.ndarray):
pass
model_type = schema.construct_schema("FunSchema", fun)
model_native = model_type({"x": np.array([1, 2, 3])}).to_native()
assert list(model_native.keys()) == ["x"]
np.testing.assert_array_equal(model_native["x"], [1, 2, 3])
def test_construct_schema_2positional():
def fun(x: int, y: float):
pass
model_type = schema.construct_schema("FunSchema",
fun,
skip_first_arg=False)
assert model_type({"x": 5, "y": 2}).to_native() == {"x": 5, "y": 2}
def test_construct_schema_default():
def fun(x: int = 3):
pass
model_type = schema.construct_schema("FunSchema",
fun,
skip_first_arg=False)
assert model_type().to_native() == {"x": 3}
assert model_type({"x": 5}).to_native() == {"x": 5}
def test_construct_schema_nested():
def fun(x: Union[int, List[Union[int, str]]]):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({"x": 1}).to_native() == {"x": 1}
assert model_type({"x": ["hi"]}).to_native() == {"x": ["hi"]}
assert model_type({"x": [2, "hi"]}).to_native() == {"x": [2, "hi"]}
with pytest.raises(models.DataError):
model_type({"x": "hi"}).to_native() == {"x": "hi"}
def test_construct_schema_1positional():
def fun(x: int):
pass
model_type = schema.construct_schema("FunSchema",
fun,
skip_first_arg=False)
assert model_type({"x": 5}).to_native() == {"x": 5}
with pytest.raises(models.DataError):
model_type({"x": "hi"}).to_native() == {"x": "hi"}
def test_construct_schema_optplan_base_model():
def fun(x: int):
pass
model_type = schema.construct_schema("FunSchema",
fun,
base_classes=(optplan.Model, ))
data = model_type(x=3)
data.validate()
assert data.to_native() == {"x": 3}
def test_construct_schema_nested():
def fun(x: Union[int, List[Union[int, str]]]):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({"x": 1}).to_native() == {"x": 1}
assert model_type({"x": ["hi"]}).to_native() == {"x": ["hi"]}
#TODO(@jskarda,@jesse): Determine why this commented assert fails
# when gitlab runs all tests:
#assert model_type({"x": [2, "hi"]}).to_native() == {"x": [2, "hi"]}
with pytest.raises(models.DataError):
model_type({"x": "hi"}).to_native() == {"x": "hi"}
def test_construct_schema_schematics_model():
@optplan.polymorphic_model()
class Model(optplan.Model):
type = optplan.ModelNameType("model")
y = optplan.types.IntType()
def fun(x: Model):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({
"x": {
"type": "model",
"y": 3
}
}).to_native() == {
"x": {
"type": "model",
"y": 3
}
}
def test_construct_schema_complex():
def fun(x: complex):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({"x": 1 + 2j}).to_native() == {"x": 1 + 2j}
def test_construct_schema_list():
def fun(x: List[int]):
pass
model_type = schema.construct_schema("FunSchema", fun)
assert model_type({"x": [1, 2, 3]}).to_native() == {"x": [1, 2, 3]}
