Returns a presigned URL that you can use to connect to the MLflow UI attached to your MLflow App. For more information, see Launch the MLflow UI using a presigned URL.
Parameters:
-
arn
(Optional[MlflowAppArn], default:
None
)
–
The ARN of the MLflow App to connect to your MLflow UI.
-
expires_in_seconds
(Optional[ExpiresInSeconds], default:
None
)
–
The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.
-
session_expiration_duration_in_seconds
(Optional[SessionExpirationDurationInSeconds], default:
None
)
–
The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.
Raises:
Source code in docs_src/capo_sagemaker/_services/async_sage_maker.py
| async def create_presigned_mlflow_app_url(
self,
*,
config_overrides: Optional[AsyncSageMakerClientConfig] = None,
arn: Optional["capo_sagemaker.types.mlflow_app_arn.MlflowAppArn"] = None,
expires_in_seconds: Optional[
"capo_sagemaker.types.expires_in_seconds.ExpiresInSeconds"
] = None,
session_expiration_duration_in_seconds: Optional[
"capo_sagemaker.types.session_expiration_duration_in_seconds.SessionExpirationDurationInSeconds"
] = None,
) -> "capo_sagemaker.types.create_presigned_mlflow_app_url_response.CreatePresignedMlflowAppUrlResponse":
"""<p>Returns a presigned URL that you can use to connect to the MLflow UI attached to your MLflow App. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/mlflow-launch-ui.html">Launch the MLflow UI using a presigned URL</a>.</p>
Args:
arn: <p>The ARN of the MLflow App to connect to your MLflow UI.</p>
expires_in_seconds: <p>The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.</p>
session_expiration_duration_in_seconds: <p>The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.</p>
Raises:
capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
async def _handler(
req: "AsyncOperationRequest[capo_sagemaker.types.create_presigned_mlflow_app_url_request.CreatePresignedMlflowAppUrlRequest]",
) -> AsyncOperationResponse[
"capo_sagemaker.types.create_presigned_mlflow_app_url_response.CreatePresignedMlflowAppUrlResponse"
]:
import capo_sagemaker._operations.sage_maker.create_presigned_mlflow_app_url
(
output,
http_response,
) = await capo_sagemaker._operations.sage_maker.create_presigned_mlflow_app_url.async_create_presigned_mlflow_app_url(
req.options, req.input
)
return AsyncOperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("CreatePresignedMlflowAppUrl")
)
input_: capo_sagemaker.types.create_presigned_mlflow_app_url_request.CreatePresignedMlflowAppUrlRequest = {}
if arn is not None:
input_["arn"] = arn
if expires_in_seconds is not None:
input_["expires_in_seconds"] = expires_in_seconds
if session_expiration_duration_in_seconds is not None:
input_["session_expiration_duration_in_seconds"] = (
session_expiration_duration_in_seconds
)
response = await aexecute_pipeline(
AsyncOperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
await response.response.aclose()
return response.output
|