evaluate_data_table_values ¶

def evaluate_data_table_values(
    self,
    instance_id: "capo_connect.types.instance_id.InstanceId",
    data_table_id: "capo_connect.types.data_table_id.DataTableId",
    values: "capo_connect.types.data_table_value_evaluation_set_list.DataTableValueEvaluationSetList",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
    time_zone: Optional["capo_connect.types.time_zone.TimeZone"] = None,
    next_token: Optional["capo_connect.types.next_token.NextToken"] = None,
    max_results: Optional["capo_connect.types.max_result100.MaxResult100"] = None,
) -> "capo_connect.types.evaluate_data_table_values_response.EvaluateDataTableValuesResponse":
    """<p>Evaluates values at the time of the request and returns them. It considers the request's timezone or the table's timezone, in that order, when accessing time based tables. When a value is accessed, the accessor's identity and the time of access are saved alongside the value to help identify values that are actively in use. The term "Batch" is not included in the operation name since it does not meet all the criteria for a batch operation as specified in Batch Operations: Amazon Web Services API Standards.</p>

    Args:
        instance_id: <p>The unique identifier for the Amazon Connect instance.</p>
        data_table_id: <p>The unique identifier for the data table. Must also accept the table ARN with or without a version alias.</p>
        values: <p>A list of value evaluation sets specifying which primary values and attributes to evaluate.</p>
        time_zone: <p>Optional IANA timezone identifier to use when resolving time based dynamic values. Defaults to the data table time zone if not provided.</p>
        next_token: <p>Specify the pagination token from a previous request to retrieve the next page of results.</p>
        max_results: <p>The maximum number of data table values to return in one page of results.</p>

    Raises:
        capo_connect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient permissions to perform this action.</p>
        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.evaluate_data_table_values_request.EvaluateDataTableValuesRequest]",
    ) -> OperationResponse[
        "capo_connect.types.evaluate_data_table_values_response.EvaluateDataTableValuesResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.evaluate_data_table_values

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("EvaluateDataTableValues")
    )
    input_: capo_connect.types.evaluate_data_table_values_request.EvaluateDataTableValuesRequest = {
        "instance_id": instance_id,
        "data_table_id": data_table_id,
        "values": values,
    }
    if time_zone is not None:
        input_["time_zone"] = time_zone
    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