def make_config() -> Union[AwsConfig, GcpConfig]:
config = load_yaml_from_file(NIMBO_CONFIG_FILE)
# Provider field validation is postponed. If cloud_provider is not specified,
# assume AwsConfig for running commands like --help and generate-config.
if "cloud_provider" not in config:
return AwsConfig(**config)
else:
config["cloud_provider"] = config["cloud_provider"].upper()
try:
cloud_provider = CloudProvider(config["cloud_provider"])
except ValueError:
permitted_values = ", ".join([f"'{p.value}'" for p in CloudProvider])
raise pydantic.ValidationError(
[
pydantic.error_wrappers.ErrorWrapper(
Exception(
f"value is not a valid enumeration member; permitted: "
f"{permitted_values}"
),
"cloud_provider",
)
],
AwsConfig,
)
if cloud_provider == CloudProvider.AWS:
return AwsConfig(**config)
return GcpConfig(**config)
def _validate_pinned_values_cannot_be_changed(self, new_value) -> None:
if not self.pinned or self.value is None:
return
if new_value != self.value:
error = ValueError(
f"value of pinned settings cannot be changed: assigned value {repr(new_value)} is not equal to existing value {repr(self.value)}"
)
error_ = pydantic.error_wrappers.ErrorWrapper(error, loc="value")
raise pydantic.ValidationError([error_], self.__class__)
def parse_base_config(cls, v):
if isinstance(v, dict):
try:
return train.Configuration(**v)
except pydantic.error_wrappers.ValidationError as e:
logger.info(str(e))
if 'defaults' in str(e):
raise pydantic.ValidationError(
f'{e}. Configuration field `defaults` from the training '
'config is not supported in the search config. Either specify '
'the data fields in the regular way, or put the config in '
'a separate file and point to the path.')
else:
return Path(v)
def test_create_response_body_converter_invalid_response(
self, mocker, pydantic_model_mock):
data = {"quick": "fox"}
_, model = pydantic_model_mock
parse_obj_mock = mocker.patch.object(
model,
"parse_obj",
side_effect=pydantic.ValidationError([], model))
converter = converters.PydanticConverter()
c = converter.create_response_body_converter(model)
with pytest.raises(pydantic.ValidationError):
c.convert(data)
parse_obj_mock.assert_called_once_with(data)
def w(cls, *args, **kwargs):
try:
return f(cls, *args, **kwargs)
except (TypeError, ValueError, AssertionError) as exc:
raise pydantic.ValidationError([ErrorWrapper(exc, loc)], cls)
def all_zones_available(cls, v):
count_not_in_keys = [count not in v.keys() for count in range(0, 12)]
if sum(count_not_in_keys) > 0:
raise pydantic.ValidationError(
"Values for some packing counts are missing.")
return v