def run_async(self, workflow_id: Optional[str] = None) -> ObjectRef:
"""Run a workflow asynchronously.
If the workflow with the given id already exists, it will be resumed.
Examples:
>>> @workflow.step
... def book_flight(origin: str, dest: str) -> Flight:
... return Flight(...)
>>> @workflow.step
... def book_hotel(location: str) -> Reservation:
... return Reservation(...)
>>> @workflow.step
... def finalize_trip(bookings: List[Any]) -> Trip:
... return Trip(...)
>>> flight1 = book_flight.step("OAK", "SAN")
>>> flight2 = book_flight.step("SAN", "OAK")
>>> hotel = book_hotel.step("SAN")
>>> trip = finalize_trip.step([flight1, flight2, hotel])
>>> result = ray.get(trip.run_async())
Args:
workflow_id: A unique identifier that can be used to resume the
workflow. If not specified, a random id will be generated.
"""
# TODO(suquark): avoid cyclic importing
from ray.workflow.execution import run
self._step_id = None
return run(self, workflow_id)
def run_async(
self,
workflow_id: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> ObjectRef:
"""Run a workflow asynchronously.
If the workflow with the given id already exists, it will be resumed.
Examples:
>>> from ray import workflow
>>> Flight, Reservation, Trip = ... # doctest: +SKIP
>>> @workflow.step # doctest: +SKIP
... def book_flight(origin: str, dest: str) -> Flight: # doctest: +SKIP
... return Flight(...) # doctest: +SKIP
>>> @workflow.step # doctest: +SKIP
... def book_hotel(location: str) -> Reservation: # doctest: +SKIP
... return Reservation(...) # doctest: +SKIP
>>> @workflow.step # doctest: +SKIP
... def finalize_trip(bookings: List[Any]) -> Trip: # doctest: +SKIP
... return Trip(...) # doctest: +SKIP
>>> flight1 = book_flight.step("OAK", "SAN") # doctest: +SKIP
>>> flight2 = book_flight.step("SAN", "OAK") # doctest: +SKIP
>>> hotel = book_hotel.step("SAN") # doctest: +SKIP
>>> trip = finalize_trip.step([flight1, flight2, hotel]) # doctest: +SKIP
>>> result = ray.get(trip.run_async()) # doctest: +SKIP
Args:
workflow_id: A unique identifier that can be used to resume the
workflow. If not specified, a random id will be generated.
metadata: The metadata to add to the workflow. It has to be able
to serialize to json.
Returns:
The running result as ray.ObjectRef.
"""
# TODO(suquark): avoid cyclic importing
from ray.workflow.execution import run
from ray.workflow.api import _ensure_workflow_initialized
_ensure_workflow_initialized()
self._step_id = None
return run(self, workflow_id, metadata)
def run_async(workflow_id: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None):
"""Run a workflow asynchronously.
If the workflow with the given id already exists, it will be resumed.
Args:
workflow_id: A unique identifier that can be used to resume the
workflow. If not specified, a random id will be generated.
metadata: The metadata to add to the workflow. It has to be able
to serialize to json.
Returns:
The running result as ray.ObjectRef.
"""
_ensure_workflow_initialized()
return execution.run(dag_node, input_data, workflow_id, metadata)