delete_mlflow_app ¶

def delete_mlflow_app(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    arn: Optional["capo_sagemaker.types.mlflow_app_arn.MlflowAppArn"] = None,
) -> "capo_sagemaker.types.delete_mlflow_app_response.DeleteMlflowAppResponse":
    """<p>Deletes an MLflow App.</p>

    Args:
        arn: <p>The ARN of the MLflow App to delete.</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.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.delete_mlflow_app_request.DeleteMlflowAppRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.delete_mlflow_app_response.DeleteMlflowAppResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.delete_mlflow_app

        output, http_response = (
            capo_sagemaker._operations.sage_maker.delete_mlflow_app.delete_mlflow_app(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteMlflowApp")
    )
    input_: capo_sagemaker.types.delete_mlflow_app_request.DeleteMlflowAppRequest = {}
    if arn is not None:
        input_["arn"] = arn

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output