start_replay ¶

def start_replay(
    self,
    replay_name: "capo_eventbridge.types.replay_name.ReplayName",
    event_source_arn: "capo_eventbridge.types.archive_arn.ArchiveArn",
    event_start_time: "capo_eventbridge.types.timestamp.Timestamp",
    event_end_time: "capo_eventbridge.types.timestamp.Timestamp",
    destination: "capo_eventbridge.types.replay_destination.ReplayDestination",
    *,
    config_overrides: Optional[EventBridgeClientConfig] = None,
    description: Optional[
        "capo_eventbridge.types.replay_description.ReplayDescription"
    ] = None,
) -> "capo_eventbridge.types.start_replay_response.StartReplayResponse":
    """<p>Starts the specified replay. Events are not necessarily replayed in the exact same order that they were added to the archive. A replay processes events to replay based on the time in the event, and replays them using 1 minute intervals. If you specify an <code>EventStartTime</code> and an <code>EventEndTime</code> that covers a 20 minute time range, the events are replayed from the first minute of that 20 minute range first. Then the events from the second minute are replayed. You can use <code>DescribeReplay</code> to determine the progress of a replay. The value returned for <code>EventLastReplayedTime</code> indicates the time within the specified time range associated with the last event replayed.</p>

    Args:
        replay_name: <p>The name of the replay to start.</p>
        description: <p>A description for the replay to start.</p>
        event_source_arn: <p>The ARN of the archive to replay events from.</p>
        event_start_time: <p>A time stamp for the time to start replaying events. Only events that occurred between the <code>EventStartTime</code> and <code>EventEndTime</code> are replayed.</p>
        event_end_time: <p>A time stamp for the time to stop replaying events. Only events that occurred between the <code>EventStartTime</code> and <code>EventEndTime</code> are replayed.</p>
        destination: <p>A <code>ReplayDestination</code> object that includes details about the destination for the replay.</p>

    Raises:
        capo_eventbridge.errors.internal_exception.InternalException: <p>This exception occurs due to unexpected causes.</p>
        capo_eventbridge.errors.invalid_event_pattern_exception.InvalidEventPatternException: <p>The event pattern is not valid.</p>
        capo_eventbridge.errors.limit_exceeded_exception.LimitExceededException: <p>The request failed because it attempted to create resource beyond the allowed service quota.</p>
        capo_eventbridge.errors.resource_already_exists_exception.ResourceAlreadyExistsException: <p>The resource you are trying to create already exists.</p>
        capo_eventbridge.errors.resource_not_found_exception.ResourceNotFoundException: <p>An entity that you specified does not exist.</p>
        capo_eventbridge.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_eventbridge.types.start_replay_request.StartReplayRequest]",
    ) -> OperationResponse[
        "capo_eventbridge.types.start_replay_response.StartReplayResponse"
    ]:
        import capo_eventbridge._operations.aws_events.start_replay

        output, http_response = (
            capo_eventbridge._operations.aws_events.start_replay.start_replay(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartReplay")
    )
    input_: capo_eventbridge.types.start_replay_request.StartReplayRequest = {
        "replay_name": replay_name,
        "event_source_arn": event_source_arn,
        "event_start_time": event_start_time,
        "event_end_time": event_end_time,
        "destination": destination,
    }
    if description is not None:
        input_["description"] = description

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