prefect.utilities.engine

collect_task_run_inputs(expr, max_depth=-1) async

This function recurses through an expression to generate a set of any discernible task run inputs it finds in the data structure. It produces a set of all inputs found.

Examples:

>>> task_inputs = {
>>>    k: await collect_task_run_inputs(v) for k, v in parameters.items()
>>> }

Source code in src/prefect/utilities/engine.py

async def collect_task_run_inputs(expr: Any, max_depth: int = -1) -> Set[TaskRunInput]:
    """
    This function recurses through an expression to generate a set of any discernible
    task run inputs it finds in the data structure. It produces a set of all inputs
    found.

    Examples:
        >>> task_inputs = {
        >>>    k: await collect_task_run_inputs(v) for k, v in parameters.items()
        >>> }
    """
    # TODO: This function needs to be updated to detect parameters and constants

    inputs = set()
    futures = set()

    def add_futures_and_states_to_inputs(obj):
        if isinstance(obj, PrefectFuture):
            # We need to wait for futures to be submitted before we can get the task
            # run id but we want to do so asynchronously
            futures.add(obj)
        elif isinstance(obj, State):
            if obj.state_details.task_run_id:
                inputs.add(TaskRunResult(id=obj.state_details.task_run_id))
        # Expressions inside quotes should not be traversed
        elif isinstance(obj, quote):
            raise StopVisiting
        else:
            state = get_state_for_result(obj)
            if state and state.state_details.task_run_id:
                inputs.add(TaskRunResult(id=state.state_details.task_run_id))

    visit_collection(
        expr,
        visit_fn=add_futures_and_states_to_inputs,
        return_data=False,
        max_depth=max_depth,
    )

    await asyncio.gather(*[future._wait_for_submission() for future in futures])
    for future in futures:
        inputs.add(TaskRunResult(id=future.task_run.id))

    return inputs

collect_task_run_inputs_sync(expr, future_cls=NewPrefectFuture, max_depth=-1)

This function recurses through an expression to generate a set of any discernible task run inputs it finds in the data structure. It produces a set of all inputs found.

Examples:

>>> task_inputs = {
>>>    k: collect_task_run_inputs(v) for k, v in parameters.items()
>>> }

Source code in src/prefect/utilities/engine.py

def collect_task_run_inputs_sync(
    expr: Any, future_cls: Any = NewPrefectFuture, max_depth: int = -1
) -> Set[TaskRunInput]:
    """
    This function recurses through an expression to generate a set of any discernible
    task run inputs it finds in the data structure. It produces a set of all inputs
    found.

    Examples:
        >>> task_inputs = {
        >>>    k: collect_task_run_inputs(v) for k, v in parameters.items()
        >>> }
    """
    # TODO: This function needs to be updated to detect parameters and constants

    inputs = set()

    def add_futures_and_states_to_inputs(obj):
        if isinstance(obj, future_cls) and hasattr(obj, "task_run_id"):
            inputs.add(TaskRunResult(id=obj.task_run_id))
        elif isinstance(obj, State):
            if obj.state_details.task_run_id:
                inputs.add(TaskRunResult(id=obj.state_details.task_run_id))
        # Expressions inside quotes should not be traversed
        elif isinstance(obj, quote):
            raise StopVisiting
        else:
            state = get_state_for_result(obj)
            if state and state.state_details.task_run_id:
                inputs.add(TaskRunResult(id=state.state_details.task_run_id))

    visit_collection(
        expr,
        visit_fn=add_futures_and_states_to_inputs,
        return_data=False,
        max_depth=max_depth,
    )

    return inputs

get_state_for_result(obj)

Get the state related to a result object.

link_state_to_result must have been called first.

Source code in src/prefect/utilities/engine.py

def get_state_for_result(obj: Any) -> Optional[State]:
    """
    Get the state related to a result object.

    `link_state_to_result` must have been called first.
    """
    flow_run_context = FlowRunContext.get()
    if flow_run_context:
        return flow_run_context.task_run_results.get(id(obj))

link_state_to_result(state, result)

Caches a link between a state and a result and its components using the id of the components to map to the state. The cache is persisted to the current flow run context since task relationships are limited to within a flow run.

This allows dependency tracking to occur when results are passed around. Note: Because id is used, we cannot cache links between singleton objects.

We only cache the relationship between components 1-layer deep. Example: Given the result [1, ["a","b"], ("c",)], the following elements will be mapped to the state: - [1, ["a","b"], ("c",)] - ["a","b"] - ("c",)

Note: the int `1` will not be mapped to the state because it is a singleton.

Other Notes: We do not hash the result because: - If changes are made to the object in the flow between task calls, we can still track that they are related. - Hashing can be expensive. - Not all objects are hashable.

We do not set an attribute, e.g. __prefect_state__, on the result because:

• Mutating user's objects is dangerous.
• Unrelated equality comparisons can break unexpectedly.
• The field can be preserved on copy.
• We cannot set this attribute on Python built-ins.

Source code in src/prefect/utilities/engine.py

def link_state_to_result(state: State, result: Any) -> None:
    """
    Caches a link between a state and a result and its components using
    the `id` of the components to map to the state. The cache is persisted to the
    current flow run context since task relationships are limited to within a flow run.

    This allows dependency tracking to occur when results are passed around.
    Note: Because `id` is used, we cannot cache links between singleton objects.

    We only cache the relationship between components 1-layer deep.
    Example:
        Given the result [1, ["a","b"], ("c",)], the following elements will be
        mapped to the state:
        - [1, ["a","b"], ("c",)]
        - ["a","b"]
        - ("c",)

        Note: the int `1` will not be mapped to the state because it is a singleton.

    Other Notes:
    We do not hash the result because:
    - If changes are made to the object in the flow between task calls, we can still
      track that they are related.
    - Hashing can be expensive.
    - Not all objects are hashable.

    We do not set an attribute, e.g. `__prefect_state__`, on the result because:

    - Mutating user's objects is dangerous.
    - Unrelated equality comparisons can break unexpectedly.
    - The field can be preserved on copy.
    - We cannot set this attribute on Python built-ins.
    """

    flow_run_context = FlowRunContext.get()

    def link_if_trackable(obj: Any) -> None:
        """Track connection between a task run result and its associated state if it has a unique ID.

        We cannot track booleans, Ellipsis, None, NotImplemented, or the integers from -5 to 256
        because they are singletons.

        This function will mutate the State if the object is an untrackable type by setting the value
        for `State.state_details.untrackable_result` to `True`.

        """
        if (type(obj) in UNTRACKABLE_TYPES) or (
            isinstance(obj, int) and (-5 <= obj <= 256)
        ):
            state.state_details.untrackable_result = True
            return
        flow_run_context.task_run_results[id(obj)] = state

    if flow_run_context:
        visit_collection(expr=result, visit_fn=link_if_trackable, max_depth=1)

propose_state(client, state, force=False, task_run_id=None, flow_run_id=None) async

Propose a new state for a flow run or task run, invoking Prefect orchestration logic.

If the proposed state is accepted, the provided state will be augmented with details and returned.

If the proposed state is rejected, a new state returned by the Prefect API will be returned.

If the proposed state results in a WAIT instruction from the Prefect API, the function will sleep and attempt to propose the state again.

If the proposed state results in an ABORT instruction from the Prefect API, an error will be raised.

Parameters:

Name	Type	Description	Default
state	State[object]	a new state for the task or flow run	required
task_run_id	Optional[UUID]	an optional task run id, used when proposing task run states	None
flow_run_id	Optional[UUID]	an optional flow run id, used when proposing flow run states	None

Returns:

Type	Description
State[object]	a State model representation of the flow or task run state

Raises:

Type	Description
ValueError	if neither task_run_id or flow_run_id is provided
Abort	if an ABORT instruction is received from the Prefect API

Source code in src/prefect/utilities/engine.py

async def propose_state(
    client: "PrefectClient",
    state: State[object],
    force: bool = False,
    task_run_id: Optional[UUID] = None,
    flow_run_id: Optional[UUID] = None,
) -> State[object]:
    """
    Propose a new state for a flow run or task run, invoking Prefect orchestration logic.

    If the proposed state is accepted, the provided `state` will be augmented with
     details and returned.

    If the proposed state is rejected, a new state returned by the Prefect API will be
    returned.

    If the proposed state results in a WAIT instruction from the Prefect API, the
    function will sleep and attempt to propose the state again.

    If the proposed state results in an ABORT instruction from the Prefect API, an
    error will be raised.

    Args:
        state: a new state for the task or flow run
        task_run_id: an optional task run id, used when proposing task run states
        flow_run_id: an optional flow run id, used when proposing flow run states

    Returns:
        a [State model][prefect.client.schemas.objects.State] representation of the
            flow or task run state

    Raises:
        ValueError: if neither task_run_id or flow_run_id is provided
        prefect.exceptions.Abort: if an ABORT instruction is received from
            the Prefect API
    """

    # Determine if working with a task run or flow run
    if not task_run_id and not flow_run_id:
        raise ValueError("You must provide either a `task_run_id` or `flow_run_id`")

    # Handle task and sub-flow tracing
    if state.is_final():
        if isinstance(state.data, BaseResult) and state.data.has_cached_object():
            # Avoid fetching the result unless it is cached, otherwise we defeat
            # the purpose of disabling `cache_result_in_memory`
            result = await state.result(raise_on_failure=False, fetch=True)
        else:
            result = state.data

        link_state_to_result(state, result)

    # Handle repeated WAITs in a loop instead of recursively, to avoid
    # reaching max recursion depth in extreme cases.
    async def set_state_and_handle_waits(set_state_func) -> OrchestrationResult:
        response = await set_state_func()
        while response.status == SetStateStatus.WAIT:
            engine_logger.debug(
                f"Received wait instruction for {response.details.delay_seconds}s: "
                f"{response.details.reason}"
            )
            await anyio.sleep(response.details.delay_seconds)
            response = await set_state_func()
        return response

    # Attempt to set the state
    if task_run_id:
        set_state = partial(client.set_task_run_state, task_run_id, state, force=force)
        response = await set_state_and_handle_waits(set_state)
    elif flow_run_id:
        set_state = partial(client.set_flow_run_state, flow_run_id, state, force=force)
        response = await set_state_and_handle_waits(set_state)
    else:
        raise ValueError(
            "Neither flow run id or task run id were provided. At least one must "
            "be given."
        )

    # Parse the response to return the new state
    if response.status == SetStateStatus.ACCEPT:
        # Update the state with the details if provided
        state.id = response.state.id
        state.timestamp = response.state.timestamp
        if response.state.state_details:
            state.state_details = response.state.state_details
        return state

    elif response.status == SetStateStatus.ABORT:
        raise prefect.exceptions.Abort(response.details.reason)

    elif response.status == SetStateStatus.REJECT:
        if response.state.is_paused():
            raise Pause(response.details.reason, state=response.state)
        return response.state

    else:
        raise ValueError(
            f"Received unexpected `SetStateStatus` from server: {response.status!r}"
        )

propose_state_sync(client, state, force=False, task_run_id=None, flow_run_id=None)

Propose a new state for a flow run or task run, invoking Prefect orchestration logic.

If the proposed state is accepted, the provided state will be augmented with details and returned.

If the proposed state is rejected, a new state returned by the Prefect API will be returned.

If the proposed state results in a WAIT instruction from the Prefect API, the function will sleep and attempt to propose the state again.

If the proposed state results in an ABORT instruction from the Prefect API, an error will be raised.

Parameters:

Name	Type	Description	Default
state	State[object]	a new state for the task or flow run	required
task_run_id	Optional[UUID]	an optional task run id, used when proposing task run states	None
flow_run_id	Optional[UUID]	an optional flow run id, used when proposing flow run states	None

Returns:

Type	Description
State[object]	a State model representation of the flow or task run state

Raises:

Type	Description
ValueError	if neither task_run_id or flow_run_id is provided
Abort	if an ABORT instruction is received from the Prefect API

Source code in src/prefect/utilities/engine.py

def propose_state_sync(
    client: "SyncPrefectClient",
    state: State[object],
    force: bool = False,
    task_run_id: Optional[UUID] = None,
    flow_run_id: Optional[UUID] = None,
) -> State[object]:
    """
    Propose a new state for a flow run or task run, invoking Prefect orchestration logic.

    If the proposed state is accepted, the provided `state` will be augmented with
     details and returned.

    If the proposed state is rejected, a new state returned by the Prefect API will be
    returned.

    If the proposed state results in a WAIT instruction from the Prefect API, the
    function will sleep and attempt to propose the state again.

    If the proposed state results in an ABORT instruction from the Prefect API, an
    error will be raised.

    Args:
        state: a new state for the task or flow run
        task_run_id: an optional task run id, used when proposing task run states
        flow_run_id: an optional flow run id, used when proposing flow run states

    Returns:
        a [State model][prefect.client.schemas.objects.State] representation of the
            flow or task run state

    Raises:
        ValueError: if neither task_run_id or flow_run_id is provided
        prefect.exceptions.Abort: if an ABORT instruction is received from
            the Prefect API
    """

    # Determine if working with a task run or flow run
    if not task_run_id and not flow_run_id:
        raise ValueError("You must provide either a `task_run_id` or `flow_run_id`")

    # Handle task and sub-flow tracing
    if state.is_final():
        if isinstance(state.data, BaseResult) and state.data.has_cached_object():
            # Avoid fetching the result unless it is cached, otherwise we defeat
            # the purpose of disabling `cache_result_in_memory`
            result = state.result(raise_on_failure=False, fetch=True)
            if inspect.isawaitable(result):
                result = run_coro_as_sync(result)
        else:
            result = state.data

        link_state_to_result(state, result)

    # Handle repeated WAITs in a loop instead of recursively, to avoid
    # reaching max recursion depth in extreme cases.
    def set_state_and_handle_waits(set_state_func) -> OrchestrationResult:
        response = set_state_func()
        while response.status == SetStateStatus.WAIT:
            engine_logger.debug(
                f"Received wait instruction for {response.details.delay_seconds}s: "
                f"{response.details.reason}"
            )
            time.sleep(response.details.delay_seconds)
            response = set_state_func()
        return response

    # Attempt to set the state
    if task_run_id:
        set_state = partial(client.set_task_run_state, task_run_id, state, force=force)
        response = set_state_and_handle_waits(set_state)
    elif flow_run_id:
        set_state = partial(client.set_flow_run_state, flow_run_id, state, force=force)
        response = set_state_and_handle_waits(set_state)
    else:
        raise ValueError(
            "Neither flow run id or task run id were provided. At least one must "
            "be given."
        )

    # Parse the response to return the new state
    if response.status == SetStateStatus.ACCEPT:
        # Update the state with the details if provided
        state.id = response.state.id
        state.timestamp = response.state.timestamp
        if response.state.state_details:
            state.state_details = response.state.state_details
        return state

    elif response.status == SetStateStatus.ABORT:
        raise prefect.exceptions.Abort(response.details.reason)

    elif response.status == SetStateStatus.REJECT:
        if response.state.is_paused():
            raise Pause(response.details.reason, state=response.state)
        return response.state

    else:
        raise ValueError(
            f"Received unexpected `SetStateStatus` from server: {response.status!r}"
        )

resolve_inputs(parameters, return_data=True, max_depth=-1) async

Resolve any Quote, PrefectFuture, or State types nested in parameters into data.

Returns:

Type	Description
Dict[str, Any]	A copy of the parameters with resolved data

Raises:

Type	Description
UpstreamTaskError	If any of the upstream states are not COMPLETED

Source code in src/prefect/utilities/engine.py

async def resolve_inputs(
    parameters: Dict[str, Any], return_data: bool = True, max_depth: int = -1
) -> Dict[str, Any]:
    """
    Resolve any `Quote`, `PrefectFuture`, or `State` types nested in parameters into
    data.

    Returns:
        A copy of the parameters with resolved data

    Raises:
        UpstreamTaskError: If any of the upstream states are not `COMPLETED`
    """

    futures = set()
    states = set()
    result_by_state = {}

    if not parameters:
        return {}

    def collect_futures_and_states(expr, context):
        # Expressions inside quotes should not be traversed
        if isinstance(context.get("annotation"), quote):
            raise StopVisiting()

        if isinstance(expr, PrefectFuture):
            futures.add(expr)
        if isinstance(expr, State):
            states.add(expr)

        return expr

    visit_collection(
        parameters,
        visit_fn=collect_futures_and_states,
        return_data=False,
        max_depth=max_depth,
        context={},
    )

    # Wait for all futures so we do not block when we retrieve the state in `resolve_input`
    states.update(await asyncio.gather(*[future._wait() for future in futures]))

    # Only retrieve the result if requested as it may be expensive
    if return_data:
        finished_states = [state for state in states if state.is_final()]

        state_results = await asyncio.gather(
            *[
                state.result(raise_on_failure=False, fetch=True)
                for state in finished_states
            ]
        )

        for state, result in zip(finished_states, state_results):
            result_by_state[state] = result

    def resolve_input(expr, context):
        state = None

        # Expressions inside quotes should not be modified
        if isinstance(context.get("annotation"), quote):
            raise StopVisiting()

        if isinstance(expr, PrefectFuture):
            state = expr._final_state
        elif isinstance(expr, State):
            state = expr
        else:
            return expr

        # Do not allow uncompleted upstreams except failures when `allow_failure` has
        # been used
        if not state.is_completed() and not (
            # TODO: Note that the contextual annotation here is only at the current level
            #       if `allow_failure` is used then another annotation is used, this will
            #       incorrectly evaluate to false — to resolve this, we must track all
            #       annotations wrapping the current expression but this is not yet
            #       implemented.
            isinstance(context.get("annotation"), allow_failure) and state.is_failed()
        ):
            raise UpstreamTaskError(
                f"Upstream task run '{state.state_details.task_run_id}' did not reach a"
                " 'COMPLETED' state."
            )

        return result_by_state.get(state)

    resolved_parameters = {}
    for parameter, value in parameters.items():
        try:
            resolved_parameters[parameter] = visit_collection(
                value,
                visit_fn=resolve_input,
                return_data=return_data,
                # we're manually going 1 layer deeper here
                max_depth=max_depth - 1,
                remove_annotations=True,
                context={},
            )
        except UpstreamTaskError:
            raise
        except Exception as exc:
            raise PrefectException(
                f"Failed to resolve inputs in parameter {parameter!r}. If your"
                " parameter type is not supported, consider using the `quote`"
                " annotation to skip resolution of inputs."
            ) from exc

    return resolved_parameters

resolve_inputs_sync(parameters, return_data=True, max_depth=-1)

Resolve any Quote, PrefectFuture, or State types nested in parameters into data.

Returns:

Type	Description
Dict[str, Any]	A copy of the parameters with resolved data

Raises:

Type	Description
UpstreamTaskError	If any of the upstream states are not COMPLETED

Source code in src/prefect/utilities/engine.py

def resolve_inputs_sync(
    parameters: Dict[str, Any], return_data: bool = True, max_depth: int = -1
) -> Dict[str, Any]:
    """
    Resolve any `Quote`, `PrefectFuture`, or `State` types nested in parameters into
    data.

    Returns:
        A copy of the parameters with resolved data

    Raises:
        UpstreamTaskError: If any of the upstream states are not `COMPLETED`
    """

    if not parameters:
        return {}

    resolved_parameters = {}
    for parameter, value in parameters.items():
        try:
            resolved_parameters[parameter] = visit_collection(
                value,
                visit_fn=resolve_to_final_result,
                return_data=return_data,
                max_depth=max_depth,
                remove_annotations=True,
                context={},
            )
        except UpstreamTaskError:
            raise
        except Exception as exc:
            raise PrefectException(
                f"Failed to resolve inputs in parameter {parameter!r}. If your"
                " parameter type is not supported, consider using the `quote`"
                " annotation to skip resolution of inputs."
            ) from exc

    return resolved_parameters

resolve_to_final_result(expr, context)

Resolve any PrefectFuture, or State types nested in parameters into data. Designed to be use with visit_collection.

Source code in src/prefect/utilities/engine.py

def resolve_to_final_result(expr, context):
    """
    Resolve any `PrefectFuture`, or `State` types nested in parameters into
    data. Designed to be use with `visit_collection`.
    """
    state = None

    # Expressions inside quotes should not be modified
    if isinstance(context.get("annotation"), quote):
        raise StopVisiting()

    if isinstance(expr, NewPrefectFuture):
        upstream_task_run = context.get("current_task_run")
        upstream_task = context.get("current_task")
        if (
            upstream_task
            and upstream_task_run
            and expr.task_run_id == upstream_task_run.id
        ):
            raise ValueError(
                f"Discovered a task depending on itself. Raising to avoid a deadlock. Please inspect the inputs and dependencies of {upstream_task.name}."
            )

        expr.wait()
        state = expr.state
    elif isinstance(expr, State):
        state = expr
    else:
        return expr

    assert state

    # Do not allow uncompleted upstreams except failures when `allow_failure` has
    # been used
    if not state.is_completed() and not (
        # TODO: Note that the contextual annotation here is only at the current level
        #       if `allow_failure` is used then another annotation is used, this will
        #       incorrectly evaluate to false — to resolve this, we must track all
        #       annotations wrapping the current expression but this is not yet
        #       implemented.
        isinstance(context.get("annotation"), allow_failure) and state.is_failed()
    ):
        raise UpstreamTaskError(
            f"Upstream task run '{state.state_details.task_run_id}' did not reach a"
            " 'COMPLETED' state."
        )

    _result = state.result(raise_on_failure=False, fetch=True)
    if inspect.isawaitable(_result):
        _result = run_coro_as_sync(_result)
    return _result