prefect.task_runners

Interface and implementations of various task runners.

Task Runners in Prefect are responsible for managing the execution of Prefect task runs. Generally speaking, users are not expected to interact with task runners outside of configuring and initializing them for a flow.

Example

>>> from prefect import flow, task
>>> from prefect.task_runners import SequentialTaskRunner
>>> from typing import List
>>>
>>> @task
>>> def say_hello(name):
...     print(f"hello {name}")
>>>
>>> @task
>>> def say_goodbye(name):
...     print(f"goodbye {name}")
>>>
>>> @flow(task_runner=SequentialTaskRunner())
>>> def greetings(names: List[str]):
...     for name in names:
...         say_hello(name)
...         say_goodbye(name)
>>>
>>> greetings(["arthur", "trillian", "ford", "marvin"])
hello arthur
goodbye arthur
hello trillian
goodbye trillian
hello ford
goodbye ford
hello marvin
goodbye marvin

Switching to a DaskTaskRunner:

>>> from prefect_dask.task_runners import DaskTaskRunner
>>> flow.task_runner = DaskTaskRunner()
>>> greetings(["arthur", "trillian", "ford", "marvin"])
hello arthur
goodbye arthur
hello trillian
hello ford
goodbye marvin
hello marvin
goodbye ford
goodbye trillian

For usage details, see the Task Runners documentation.

BaseTaskRunner

Source code in prefect/task_runners.py

class BaseTaskRunner(metaclass=abc.ABCMeta):
    def __init__(self) -> None:
        self.logger = get_logger(f"task_runner.{self.name}")
        self._started: bool = False

    @property
    @abc.abstractmethod
    def concurrency_type(self) -> TaskConcurrencyType:
        pass  # noqa

    @property
    def name(self):
        return type(self).__name__.lower().replace("taskrunner", "")

    @abc.abstractmethod
    async def submit(
        self,
        key: UUID,
        call: Callable[..., Awaitable[State[R]]],
    ) -> None:
        """
        Submit a call for execution and return a `PrefectFuture` that can be used to
        get the call result.

        Args:
            task_run: The task run being submitted.
            task_key: A unique key for this orchestration run of the task. Can be used
                for caching.
            call: The function to be executed
            run_kwargs: A dict of keyword arguments to pass to `call`

        Returns:
            A future representing the result of `call` execution
        """
        raise NotImplementedError()

    @abc.abstractmethod
    async def wait(self, key: UUID, timeout: float = None) -> Optional[State]:
        """
        Given a `PrefectFuture`, wait for its return state up to `timeout` seconds.
        If it is not finished after the timeout expires, `None` should be returned.

        Implementers should be careful to ensure that this function never returns or
        raises an exception.
        """
        raise NotImplementedError()

    @asynccontextmanager
    async def start(
        self: T,
    ) -> AsyncIterator[T]:
        """
        Start the task runner, preparing any resources necessary for task submission.

        Children should implement `_start` to prepare and clean up resources.

        Yields:
            The prepared task runner
        """
        if self._started:
            raise RuntimeError("The task runner is already started!")

        async with AsyncExitStack() as exit_stack:
            self.logger.debug(f"Starting task runner...")
            try:
                await self._start(exit_stack)
                self._started = True
                yield self
            finally:
                self.logger.debug(f"Shutting down task runner...")
                self._started = False

    async def _start(self, exit_stack: AsyncExitStack) -> None:
        """
        Create any resources required for this task runner to submit work.

        Cleanup of resources should be submitted to the `exit_stack`.
        """
        pass  # noqa

    def __str__(self) -> str:
        return type(self).__name__

start async

Start the task runner, preparing any resources necessary for task submission.

Children should implement _start to prepare and clean up resources.

Yields:

Type	Description
AsyncIterator[T]	The prepared task runner

Source code in prefect/task_runners.py

@asynccontextmanager
async def start(
    self: T,
) -> AsyncIterator[T]:
    """
    Start the task runner, preparing any resources necessary for task submission.

    Children should implement `_start` to prepare and clean up resources.

    Yields:
        The prepared task runner
    """
    if self._started:
        raise RuntimeError("The task runner is already started!")

    async with AsyncExitStack() as exit_stack:
        self.logger.debug(f"Starting task runner...")
        try:
            await self._start(exit_stack)
            self._started = True
            yield self
        finally:
            self.logger.debug(f"Shutting down task runner...")
            self._started = False

submit abstractmethod async

Submit a call for execution and return a PrefectFuture that can be used to get the call result.

Parameters:

Name	Type	Description	Default
task_run		The task run being submitted.	required
task_key		A unique key for this orchestration run of the task. Can be used for caching.	required
call	Callable[..., Awaitable[State[R]]]	The function to be executed	required
run_kwargs		A dict of keyword arguments to pass to call	required

Returns:

Type	Description
None	A future representing the result of call execution

Source code in prefect/task_runners.py

@abc.abstractmethod
async def submit(
    self,
    key: UUID,
    call: Callable[..., Awaitable[State[R]]],
) -> None:
    """
    Submit a call for execution and return a `PrefectFuture` that can be used to
    get the call result.

    Args:
        task_run: The task run being submitted.
        task_key: A unique key for this orchestration run of the task. Can be used
            for caching.
        call: The function to be executed
        run_kwargs: A dict of keyword arguments to pass to `call`

    Returns:
        A future representing the result of `call` execution
    """
    raise NotImplementedError()

wait abstractmethod async

Given a PrefectFuture, wait for its return state up to timeout seconds. If it is not finished after the timeout expires, None should be returned.

Implementers should be careful to ensure that this function never returns or raises an exception.

Source code in prefect/task_runners.py

@abc.abstractmethod
async def wait(self, key: UUID, timeout: float = None) -> Optional[State]:
    """
    Given a `PrefectFuture`, wait for its return state up to `timeout` seconds.
    If it is not finished after the timeout expires, `None` should be returned.

    Implementers should be careful to ensure that this function never returns or
    raises an exception.
    """
    raise NotImplementedError()

ConcurrentTaskRunner

Bases: BaseTaskRunner

A concurrent task runner that allows tasks to switch when blocking on IO. Synchronous tasks will be submitted to a thread pool maintained by anyio.

Example

Using a thread for concurrency:
>>> from prefect import flow
>>> from prefect.task_runners import ConcurrentTaskRunner
>>> @flow(task_runner=ConcurrentTaskRunner)
>>> def my_flow():
>>>     ...

Source code in prefect/task_runners.py

class ConcurrentTaskRunner(BaseTaskRunner):
    """
    A concurrent task runner that allows tasks to switch when blocking on IO.
    Synchronous tasks will be submitted to a thread pool maintained by `anyio`.

    Example:
        ```
        Using a thread for concurrency:
        >>> from prefect import flow
        >>> from prefect.task_runners import ConcurrentTaskRunner
        >>> @flow(task_runner=ConcurrentTaskRunner)
        >>> def my_flow():
        >>>     ...
        ```
    """

    def __init__(self):
        # TODO: Consider adding `max_workers` support using anyio capacity limiters

        # Runtime attributes
        self._task_group: anyio.abc.TaskGroup = None
        self._result_events: Dict[UUID, anyio.abc.Event] = {}
        self._results: Dict[UUID, Any] = {}
        self._keys: Set[UUID] = set()

        super().__init__()

    @property
    def concurrency_type(self) -> TaskConcurrencyType:
        return TaskConcurrencyType.CONCURRENT

    async def submit(
        self,
        key: UUID,
        call: Callable[[], Awaitable[State[R]]],
    ) -> None:
        if not self._started:
            raise RuntimeError(
                "The task runner must be started before submitting work."
            )

        if not self._task_group:
            raise RuntimeError(
                "The concurrent task runner cannot be used to submit work after "
                "serialization."
            )

        self._result_events[key] = anyio.Event()

        # Rely on the event loop for concurrency
        self._task_group.start_soon(self._run_and_store_result, key, call)

        # Track the keys so we can ensure to gather them later
        self._keys.add(key)

    async def wait(
        self,
        key: UUID,
        timeout: float = None,
    ) -> Optional[State]:
        if not self._task_group:
            raise RuntimeError(
                "The concurrent task runner cannot be used to wait for work after "
                "serialization."
            )

        return await self._get_run_result(key, timeout)

    async def _run_and_store_result(
        self, key: UUID, call: Callable[[], Awaitable[State[R]]]
    ):
        """
        Simple utility to store the orchestration result in memory on completion

        Since this run is occuring on the main thread, we capture exceptions to prevent
        task crashes from crashing the flow run.
        """
        try:
            self._results[key] = await call()
        except BaseException as exc:
            self._results[key] = await exception_to_crashed_state(exc)

        self._result_events[key].set()

    async def _get_run_result(
        self, key: UUID, timeout: float = None
    ) -> Optional[State]:
        """
        Block until the run result has been populated.
        """
        result = None  # Return value on timeout
        result_event = self._result_events.get(key)

        with anyio.move_on_after(timeout):
            # Attempt to use the event to wait for the result. This is much more efficient
            # than the spin-lock that follows but does not work if the wait call
            # happens from an event loop in a different thread than the one from which
            # the event was created

            while not result_event:
                await anyio.sleep(0)  # yield to other tasks
                result_event = self._result_events.get(key)

            if result_event._event._loop == asyncio.get_running_loop():
                await result_event.wait()

            result = self._results.get(key)
            while not result:
                await anyio.sleep(0)  # yield to other tasks
                result = self._results.get(key)

        return result

    async def _start(self, exit_stack: AsyncExitStack):
        """
        Start the process pool
        """
        self._task_group = await exit_stack.enter_async_context(
            anyio.create_task_group()
        )

    def __getstate__(self):
        """
        Allow the `ConcurrentTaskRunner` to be serialized by dropping the task group.
        """
        data = self.__dict__.copy()
        data.update({k: None for k in {"_task_group"}})
        return data

    def __setstate__(self, data: dict):
        """
        When deserialized, we will no longer have a reference to the task group.
        """
        self.__dict__.update(data)
        self._task_group = None

SequentialTaskRunner

Bases: BaseTaskRunner

A simple task runner that executes calls as they are submitted.

If writing synchronous tasks, this runner will always execute tasks sequentially. If writing async tasks, this runner will execute tasks sequentially unless grouped using anyio.create_task_group or asyncio.gather.

Source code in prefect/task_runners.py

class SequentialTaskRunner(BaseTaskRunner):
    """
    A simple task runner that executes calls as they are submitted.

    If writing synchronous tasks, this runner will always execute tasks sequentially.
    If writing async tasks, this runner will execute tasks sequentially unless grouped
    using `anyio.create_task_group` or `asyncio.gather`.
    """

    def __init__(self) -> None:
        super().__init__()
        self._results: Dict[str, State] = {}

    @property
    def concurrency_type(self) -> TaskConcurrencyType:
        return TaskConcurrencyType.SEQUENTIAL

    async def submit(
        self,
        key: UUID,
        call: Callable[..., Awaitable[State[R]]],
    ) -> None:
        # Run the function immediately and store the result in memory
        try:
            result = await call()
        except BaseException as exc:
            result = await exception_to_crashed_state(exc)

        self._results[key] = result

    async def wait(self, key: UUID, timeout: float = None) -> Optional[State]:
        return self._results[key]