list_studio_lifecycle_configs ¶

def list_studio_lifecycle_configs(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    max_results: Optional["capo_sagemaker.types.max_results.MaxResults"] = None,
    next_token: Optional["capo_sagemaker.types.next_token.NextToken"] = None,
    name_contains: Optional[
        "capo_sagemaker.types.studio_lifecycle_config_name.StudioLifecycleConfigName"
    ] = None,
    app_type_equals: Optional[
        "capo_sagemaker.types.studio_lifecycle_config_app_type.StudioLifecycleConfigAppType"
    ] = None,
    creation_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    creation_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    modified_time_before: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    modified_time_after: Optional[
        "capo_sagemaker.types.timestamp.Timestamp"
    ] = None,
    sort_by: Optional[
        "capo_sagemaker.types.studio_lifecycle_config_sort_key.StudioLifecycleConfigSortKey"
    ] = None,
    sort_order: Optional["capo_sagemaker.types.sort_order.SortOrder"] = None,
) -> "capo_sagemaker.types.list_studio_lifecycle_configs_response.ListStudioLifecycleConfigsResponse":
    """<p>Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services Account.</p>

    Args:
        max_results: <p>The total number of items to return in the response. If the total number of items available is more than the value specified, a <code>NextToken</code> is provided in the response. To resume pagination, provide the <code>NextToken</code> value in the as part of a subsequent call. The default value is 10.</p>
        next_token: <p>If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.</p>
        name_contains: <p>A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.</p>
        app_type_equals: <p>A parameter to search for the App Type to which the Lifecycle Configuration is attached.</p>
        creation_time_before: <p>A filter that returns only Lifecycle Configurations created on or before the specified time.</p>
        creation_time_after: <p>A filter that returns only Lifecycle Configurations created on or after the specified time.</p>
        modified_time_before: <p>A filter that returns only Lifecycle Configurations modified before the specified time.</p>
        modified_time_after: <p>A filter that returns only Lifecycle Configurations modified after the specified time.</p>
        sort_by: <p>The property used to sort results. The default value is CreationTime.</p>
        sort_order: <p>The sort order. The default value is Descending.</p>

    Raises:
        capo_sagemaker.errors.resource_in_use.ResourceInUse: <p>Resource being accessed is in use.</p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.list_studio_lifecycle_configs_request.ListStudioLifecycleConfigsRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.list_studio_lifecycle_configs_response.ListStudioLifecycleConfigsResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.list_studio_lifecycle_configs

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListStudioLifecycleConfigs")
    )
    input_: capo_sagemaker.types.list_studio_lifecycle_configs_request.ListStudioLifecycleConfigsRequest = {}
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token
    if name_contains is not None:
        input_["name_contains"] = name_contains
    if app_type_equals is not None:
        input_["app_type_equals"] = app_type_equals
    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
    if modified_time_before is not None:
        input_["modified_time_before"] = modified_time_before
    if modified_time_after is not None:
        input_["modified_time_after"] = modified_time_after
    if sort_by is not None:
        input_["sort_by"] = sort_by
    if sort_order is not None:
        input_["sort_order"] = sort_order

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