def test_datetime_time_field(
self,
normalize_sdl,
graphene_version,
is_graphene_1_or_2,
):
versions_1_x = {"1.1.2", "1.1.1", "1.1", "1.0.2", "1.0.1", "1.0"}
if graphene_version in versions_1_x:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(datetime.time))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(datetime.time))
expected_value = '''
type FakeGql {
field: Time!
}
"""
The `Time` scalar type represents a Time value as specified by
[iso8601](https://en.wikipedia.org/wiki/ISO_8601).
"""
scalar Time
'''
if is_graphene_1_or_2:
expected_value = """
type FakeGql {
field: Time!
}scalarTime
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_input_usage(input_query_schema):
MyModelGql = pydantic2graphene.to_graphene(MyModel)
MyModelInputGql = pydantic2graphene.to_graphene(MyModel,
graphene.InputObjectType)
schema = input_query_schema(MyModelGql,
MyModelInputGql(),
resolve_model=MyModel)
query = """
query {
h1: hello (inp: {field1: 99.01}) {
f1: field1
f2: field2
}
h2: hello (inp: {field1: 109.01, field2: 101.1}) {
field1
field2
}
}
"""
value = schema.execute(query).data
expected_value = {
"h1": {
"f1": 99.01,
"f2": 3.14159265359
},
"h2": {
"field1": 109.01,
"field2": 101.1
},
}
assert value == expected_value
def test_datetime_date_field(
self,
normalize_sdl,
graphene_version,
is_graphene_1_or_2,
):
version_1_x = graphene_version.startswith("1.")
version_2_0 = graphene_version == "2.0"
if version_1_x or version_2_0:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(datetime.date))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(datetime.date))
expected_value = '''
type FakeGql {
field: Date!
}
"""
The `Date` scalar type represents a Date
value as specified by
[iso8601](https://en.wikipedia.org/wiki/ISO_8601).
"""
scalar Date
'''
if is_graphene_1_or_2:
expected_value = """
scalarDatetypeFakeGql {
field: Date!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_json_field(self, normalize_sdl):
graphene_not_suported = graphene.__version__ in {
"1.4.2",
"1.4.1",
"1.4",
"1.3",
"1.2",
"1.1.3",
"1.1.2",
"1.1.1",
"1.1",
"1.0.2",
"1.0.1",
"1.0",
}
pydantic_not_supported = str(pydantic.VERSION)[:3] in {
"1.2",
"1.1",
"1.0",
}
if graphene_not_suported or pydantic_not_supported:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(pydantic.Json))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(pydantic.Json))
expected_value = """
type FakeGql {
field: JSONString
}
scalar JSONString
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_json_field(
self,
normalize_sdl,
graphene_version,
is_graphene_1_or_2,
pydantic_version,
):
graphene_not_suported = graphene_version in {
"1.4.2",
"1.4.1",
"1.4",
"1.3",
"1.2",
"1.1.3",
"1.1.2",
"1.1.1",
"1.1",
"1.0.2",
"1.0.1",
"1.0",
}
pydantic_not_supported = pydantic_version[:3] in {
"1.2",
"1.1",
"1.0",
}
if graphene_not_suported or pydantic_not_supported:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(pydantic.Json))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(pydantic.Json))
expected_value = '''
type FakeGql {
field: JSONString
}
"""
Allows use of a JSON String for input / output from the GraphQL
schema.
Use of this type is *not recommended* as you lose the benefits of
having a defined, static schema
(one of the key benefits of GraphQL).
"""
scalar JSONString
'''
if is_graphene_1_or_2:
expected_value = """
type FakeGql {
field: JSONString
}
scalar JSONString
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_datetime_time_field(self, normalize_sdl):
versions_1_x = {"1.1.2", "1.1.1", "1.1", "1.0.2", "1.0.1", "1.0"}
if graphene.__version__ in versions_1_x:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(datetime.time))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(datetime.time))
expected_value = """
type FakeGql {
field: Time!
}scalarTime
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_datetime_date_field(self, normalize_sdl):
version_1_x = graphene.__version__.startswith("1.")
version_2_0 = graphene.__version__ == "2.0"
if version_1_x or version_2_0:
with pytest.raises(pydantic2graphene.FieldNotSupported):
pydantic2graphene.to_graphene(to_pydantic_class(datetime.date))
return
value = pydantic2graphene.to_graphene(to_pydantic_class(datetime.date))
expected_value = """
scalarDatetypeFakeGql {
field: Date!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_int_enum_field(self, normalize_sdl, is_graphene_1_or_2):
class Enumer(enum.IntEnum):
ONE = 1
TWO = 2
value = pydantic2graphene.to_graphene(to_pydantic_class(Enumer))
expected_value = '''
type FakeGql {
field: Enumer!
}
"""An enumeration."""
enum Enumer {
ONE
TWO
}
'''
if is_graphene_1_or_2:
expected_value = """
enum Enumer {
ONE
TWO
}
type FakeGql {
field: Enumer!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_uuid_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(to_pydantic_class(uuid.UUID))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_conint_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.conint()))
expected_value = """
type FakeGql {
field: Int!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_positive_float_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.PositiveFloat))
expected_value = """
type FakeGql {
field: Float!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_ipv_any_network_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.IPvAnyNetwork))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_secret_str_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.SecretStr))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_redisdsn_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.RedisDsn))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_http_url_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.HttpUrl))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_typing_pattern_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(to_pydantic_class(
typing.Pattern))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_optional_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(typing.Optional[int]))
expected_value = """
type FakeGql {
field: Int
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_decimal_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(decimal.Decimal))
expected_value = """
type FakeGql {
field: Float!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_ipaddress_ipv6network_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(ipaddress.IPv6Network))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_conlist_str_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.conlist(str, min_items=1, max_items=4)))
expected_value = """
type FakeGql {
field: [String!]!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_schema_input_declaration(normalize_sdl):
value = pydantic2graphene.to_graphene(MyModel, graphene.InputObjectType)
expected_value = """
input MyModelInputGql {
field1: Float!
field2: Float=3.14159265359
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_typing_sequence_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(typing.Sequence[str]))
expected_value = """
type FakeGql {
field: [String!]!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_schema_interface_declaration(normalize_sdl):
value = pydantic2graphene.to_graphene(MyModel, graphene.Interface)
expected_value = """
interface MyModelInterfaceGql {
field1: String!
field2: String
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
def test_pydantic_payment_card_number_field(self, normalize_sdl):
value = pydantic2graphene.to_graphene(
to_pydantic_class(pydantic.PaymentCardNumber))
expected_value = """
type FakeGql {
field: String!
}
"""
assert normalize_sdl(value) == normalize_sdl(expected_value)
