0.1.dev2192+g7c539c3.d20250403

flytekit.sensor.sensor_engine

Class	Description
`SensorEngine`	This is the base class for all async connectors.

flytekit.sensor.sensor_engine.SensorEngine

This is the base class for all async connectors. It defines the interface that all connectors must implement. The connector service is responsible for invoking connectors. The propeller will communicate with the connector service to create tasks, get the status of tasks, and delete tasks.

All the connectors should be registered in the ConnectorRegistry. Connector Service will look up the connector based on the task type. Every task type can only have one connector.

def SensorEngine()

Methods

Method	Description
`create()`	Return a resource meta that can be used to get the status of the task.
`delete()`	Delete the task.
`get()`	Return the status of the task, and return the outputs in some cases.
`get_logs()`	Return the metrics for the task.
`get_metrics()`	Return the metrics for the task.

create()

        
    
def create(
    task_template: flytekit.models.task.TaskTemplate,
    inputs: typing.Optional[flytekit.models.literals.LiteralMap],
    kwarg,
) -> flytekit.sensor.base_sensor.SensorMetadata

Return a resource meta that can be used to get the status of the task.

Parameter	Type
`task_template`	`flytekit.models.task.TaskTemplate`
`inputs`	`typing.Optional[flytekit.models.literals.LiteralMap]`
`kwarg`

delete()

        
    
def delete(
    resource_meta: flytekit.sensor.base_sensor.SensorMetadata,
    kwargs,
)

Delete the task. This call should be idempotent. It should raise an error if fails to delete the task.

Parameter	Type
`resource_meta`	`flytekit.sensor.base_sensor.SensorMetadata`
`kwargs`	`**kwargs`

get()

        
    
def get(
    resource_meta: flytekit.sensor.base_sensor.SensorMetadata,
    kwargs,
) -> flytekit.extend.backend.base_connector.Resource

Return the status of the task, and return the outputs in some cases. For example, bigquery job can’t write the structured dataset to the output location, so it returns the output literals to the propeller, and the propeller will write the structured dataset to the blob store.

Parameter	Type
`resource_meta`	`flytekit.sensor.base_sensor.SensorMetadata`
`kwargs`	`**kwargs`

get_logs()

        
    
def get_logs(
    resource_meta: flytekit.extend.backend.base_connector.ResourceMeta,
    kwargs,
) -> flyteidl.admin.agent_pb2.GetTaskLogsResponse

Return the metrics for the task.

Parameter	Type
`resource_meta`	`flytekit.extend.backend.base_connector.ResourceMeta`
`kwargs`	`**kwargs`

get_metrics()

        
    
def get_metrics(
    resource_meta: flytekit.extend.backend.base_connector.ResourceMeta,
    kwargs,
) -> flyteidl.admin.agent_pb2.GetTaskMetricsResponse