list_endpoint_configs ¶

def list_endpoint_configs(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    sort_by: Optional[
        "capo_sagemaker.types.endpoint_config_sort_key.EndpointConfigSortKey"
    ] = None,
    sort_order: Optional["capo_sagemaker.types.order_key.OrderKey"] = None,
    next_token: Optional[
        "capo_sagemaker.types.pagination_token.PaginationToken"
    ] = None,
    max_results: Optional["capo_sagemaker.types.max_results.MaxResults"] = None,
    name_contains: Optional[
        "capo_sagemaker.types.endpoint_config_name_contains.EndpointConfigNameContains"
    ] = None,
    creation_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    creation_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
) -> "capo_sagemaker.types.list_endpoint_configs_output.ListEndpointConfigsOutput":
    """<p>Lists endpoint configurations.</p>

    Args:
        sort_by: <p>The field to sort results by. The default is <code>CreationTime</code>.</p>
        sort_order: <p>The sort order for results. The default is <code>Descending</code>.</p>
        next_token: <p>If the result of the previous <code>ListEndpointConfig</code> request was truncated, the response includes a <code>NextToken</code>. To retrieve the next set of endpoint configurations, use the token in the next request. </p>
        max_results: <p>The maximum number of training jobs to return in the response.</p>
        name_contains: <p>A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string. </p>
        creation_time_before: <p>A filter that returns only endpoint configurations created before the specified time (timestamp).</p>
        creation_time_after: <p>A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).</p>

    Raises:
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.list_endpoint_configs_input.ListEndpointConfigsInput]",
    ) -> OperationResponse[
        "capo_sagemaker.types.list_endpoint_configs_output.ListEndpointConfigsOutput"
    ]:
        import capo_sagemaker._operations.sage_maker.list_endpoint_configs

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListEndpointConfigs")
    )
    input_: capo_sagemaker.types.list_endpoint_configs_input.ListEndpointConfigsInput = {}
    if sort_by is not None:
        input_["sort_by"] = sort_by
    if sort_order is not None:
        input_["sort_order"] = sort_order
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if name_contains is not None:
        input_["name_contains"] = name_contains
    if creation_time_before is not None:
        input_["creation_time_before"] = creation_time_before
    if creation_time_after is not None:
        input_["creation_time_after"] = creation_time_after

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