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batch_update_data_table_value

batch_update_data_table_value(
    instance_id: InstanceId,
    data_table_id: DataTableId,
    values: DataTableValueList,
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
) -> BatchUpdateDataTableValueResponse

Updates multiple data table values using all properties from BatchCreateDataTableValue. System managed values are not modifiable by customers. The operation requires proper lock versions to prevent concurrent modification conflicts.

Parameters:

  • instance_id (InstanceId) –

    The unique identifier for the Amazon Connect instance.

  • data_table_id (DataTableId) –

    The unique identifier for the data table. Must also accept the table ARN with or without a version alias.

  • values (DataTableValueList) –

    A list of values to update, each including the current lock version to ensure optimistic locking.

Raises:

Source code in docs_src/capo_connect/_services/connect.py
def batch_update_data_table_value(
    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_list.DataTableValueList",
    *,
    config_overrides: Optional[ConnectClientConfig] = None,
) -> "capo_connect.types.batch_update_data_table_value_response.BatchUpdateDataTableValueResponse":
    """<p>Updates multiple data table values using all properties from BatchCreateDataTableValue. System managed values are not modifiable by customers. The operation requires proper lock versions to prevent concurrent modification conflicts.</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 values to update, each including the current lock version to ensure optimistic locking.</p>

    Raises:
        capo_connect.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient permissions to perform this action.</p>
        capo_connect.errors.conflict_exception.ConflictException: <p>Operation cannot be performed at this time as there is a conflict with another operation or contact state.</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.batch_update_data_table_value_request.BatchUpdateDataTableValueRequest]",
    ) -> OperationResponse[
        "capo_connect.types.batch_update_data_table_value_response.BatchUpdateDataTableValueResponse"
    ]:
        import capo_connect._operations.amazon_connect_service.batch_update_data_table_value

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("BatchUpdateDataTableValue")
    )
    input_: capo_connect.types.batch_update_data_table_value_request.BatchUpdateDataTableValueRequest = {
        "instance_id": instance_id,
        "data_table_id": data_table_id,
        "values": values,
    }

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