batch_evaluate_geofences ¶

def batch_evaluate_geofences(
    self,
    collection_name: "capo_location.types.resource_name.ResourceName",
    device_position_updates: "capo_location.types.device_position_update_list.DevicePositionUpdateList",
    *,
    config_overrides: Optional[LocationClientConfig] = None,
) -> "capo_location.types.batch_evaluate_geofences_response.BatchEvaluateGeofencesResponse":
    """<p>Evaluates device positions against the geofence geometries from a given geofence collection.</p> <p>This operation always returns an empty response because geofences are asynchronously evaluated. The evaluation determines if the device has entered or exited a geofenced area, and then publishes one of the following events to Amazon EventBridge:</p> <ul> <li> <p> <code>ENTER</code> if Amazon Location determines that the tracked device has entered a geofenced area.</p> </li> <li> <p> <code>EXIT</code> if Amazon Location determines that the tracked device has exited a geofenced area.</p> </li> </ul> <note> <p>The last geofence that a device was observed within is tracked for 30 days after the most recent device position update.</p> </note> <note> <p>Geofence evaluation uses the given device position. It does not account for the optional <code>Accuracy</code> of a <code>DevicePositionUpdate</code>.</p> </note> <note> <p>The <code>DeviceID</code> is used as a string to represent the device. You do not need to have a <code>Tracker</code> associated with the <code>DeviceID</code>.</p> </note>

    Args:
        collection_name: <p>The geofence collection used in evaluating the position of devices against its geofences.</p>
        device_position_updates: <p>Contains device details for each device to be evaluated against the given geofence collection.</p>

    Raises:
        capo_location.errors.access_denied_exception.AccessDeniedException: <p>The request was denied because of insufficient access or permissions. Check with an administrator to verify your permissions.</p>
        capo_location.errors.internal_server_exception.InternalServerException: <p>The request has failed to process because of an unknown server error, exception, or failure.</p>
        capo_location.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource that you've entered was not found in your AWS account.</p>
        capo_location.errors.throttling_exception.ThrottlingException: <p>The request was denied because of request throttling.</p>
        capo_location.errors.validation_exception.ValidationException: <p>The input failed to meet the constraints specified by the AWS service. </p>
        capo_location.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_location.types.batch_evaluate_geofences_request.BatchEvaluateGeofencesRequest]",
    ) -> OperationResponse[
        "capo_location.types.batch_evaluate_geofences_response.BatchEvaluateGeofencesResponse"
    ]:
        import capo_location._operations.location_service.batch_evaluate_geofences

        output, http_response = (
            capo_location._operations.location_service.batch_evaluate_geofences.batch_evaluate_geofences(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_location.types.batch_evaluate_geofences_request.BatchEvaluateGeofencesRequest",
    ) -> dict[str, Any]:
        import capo_location.types.batch_evaluate_geofences_request

        return (
            capo_location.types.batch_evaluate_geofences_request.redact_sensitive(
                input_
            )
        )

    def _redact_output(
        output: "capo_location.types.batch_evaluate_geofences_response.BatchEvaluateGeofencesResponse",
    ) -> dict[str, Any]:
        import capo_location.types.batch_evaluate_geofences_response

        return (
            capo_location.types.batch_evaluate_geofences_response.redact_sensitive(
                output
            )
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging(
            "BatchEvaluateGeofences",
            redact_input=_redact_input,
            redact_output=_redact_output,
        ),
    )
    input_: capo_location.types.batch_evaluate_geofences_request.BatchEvaluateGeofencesRequest = {
        "collection_name": collection_name,
        "device_position_updates": device_position_updates,
    }

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