def test_get_unique_resource_id_with_invalid_max_length_throws_exception():
match = "unique resource id must be positive"
with pytest.raises(ValueError, match=match):
get_unique_resource_id(max_length=-50)
with pytest.raises(ValueError, match=match):
get_unique_resource_id(max_length=0)
def _get_mlflow_azure_resource_name():
"""
:return: A unique name for an Azure resource indicating that the resource was created by
MLflow
"""
azureml_max_resource_length = 32
resource_prefix = "mlflow-"
unique_id = get_unique_resource_id(
max_length=(azureml_max_resource_length - len(resource_prefix)))
return resource_prefix + unique_id
def _get_sagemaker_config_name(endpoint_name):
return "{en}-config-{uid}".format(en=endpoint_name, uid=get_unique_resource_id())
def _get_sagemaker_model_name(endpoint_name):
return "{en}-model-{uid}".format(en=endpoint_name, uid=get_unique_resource_id())
def test_get_unique_resource_id_with_invalid_max_length_throws_exception():
with pytest.raises(ValueError):
get_unique_resource_id(max_length=-50)
with pytest.raises(ValueError):
get_unique_resource_id(max_length=0)
def test_get_unique_resource_id_respects_max_length():
for max_length in range(5, 30, 5):
for _ in range(10000):
assert len(get_unique_resource_id(max_length=max_length)) <= max_length
