list_predefined_attributes ¶

def list_predefined_attributes(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    next_token: Optional["capo_connect.types.next_token.NextToken"] = None,
    max_results: Optional["capo_connect.types.max_result100.MaxResult100"] = None,
) -> "capo_connect.types.list_predefined_attributes_response.ListPredefinedAttributesResponse":
    """<p>Lists predefined attributes for the specified Connect Customer instance. A <i>predefined attribute</i> is made up of a name and a value. You can use predefined attributes for:</p> <ul> <li> <p>Routing proficiency (for example, agent certification) that has predefined values (for example, a list of possible certifications). For more information, see <a href="https://docs.aws.amazon.com/connect/latest/adminguide/predefined-attributes.html">Create predefined attributes for routing contacts to agents</a>.</p> </li> <li> <p>Contact information that varies between transfers or conferences, such as the name of the business unit handling the contact. For more information, see <a href="https://docs.aws.amazon.com/connect/latest/adminguide/use-contact-segment-attributes.html">Use contact segment attributes</a>.</p> </li> </ul> <p>For the predefined attributes per instance quota, see <a href="https://docs.aws.amazon.com/connect/latest/adminguide/amazon-connect-service-limits.html#connect-quotas">Connect Customer quotas</a>.</p> <p> <b>Endpoints</b>: See <a href="https://docs.aws.amazon.com/general/latest/gr/connect_region.html">Connect Customer endpoints and quotas</a>.</p>

    Args:
        instance_id: <p>The identifier of the Connect Customer instance. You can find the instance ID in the Amazon Resource Name (ARN) of the instance.</p>
        next_token: <p>The token for the next set of results. Use the value returned in the previous response in the next request to retrieve the next set of results.</p>
        max_results: <p>The maximum number of results to return per page.</p>

    Raises:
        capo_connect.errors.internal_service_exception.InternalServiceException: <p>Request processing failed because of an error or failure with the service.</p>
        capo_connect.errors.invalid_parameter_exception.InvalidParameterException: <p>One or more of the specified parameters are not valid.</p>
        capo_connect.errors.invalid_request_exception.InvalidRequestException: <p>The request is not valid.</p>
        capo_connect.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</p>
        capo_connect.errors.throttling_exception.ThrottlingException: <p>The throttling limit has been exceeded.</p>
        capo_connect.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_connect.types.list_predefined_attributes_request.ListPredefinedAttributesRequest]",
    ) -> OperationResponse[
        "capo_connect.types.list_predefined_attributes_response.ListPredefinedAttributesResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.list_predefined_attributes

        output, http_response = (
            capo_connect._operations.amazon_connect_service.list_predefined_attributes.list_predefined_attributes(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListPredefinedAttributes")
    )
    input_: capo_connect.types.list_predefined_attributes_request.ListPredefinedAttributesRequest = {
        "instance_id": instance_id
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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