Skip to main content

​
prefect.utilities.engine

​
Functions

​
is_prefect_sigterm_handler_installed 

is_prefect_sigterm_handler_installed() -> bool
Return whether Prefect’s SIGTERM bridge is currently installed.

​
can_ack_control_intent 

can_ack_control_intent() -> bool
Return whether the child can safely acknowledge a queued control intent. The check is protected by the same lock used when capture_sigterm() installs and restores Prefect’s SIGTERM bridge. On POSIX, the runner’s subsequent real SIGTERM is the actual cancellation trigger, so the child only needs to verify that Prefect still owns the live bridge before advertising readiness with b"a".

​
commit_control_intent_and_ack 

commit_control_intent_and_ack(commit_intent: Callable[[], None], clear_intent: Callable[[], None], send_ack: Callable[[], None], trigger_cancel: Callable[[], None] | None = None) -> bool
Atomically commit control intent and acknowledge it to the runner. The SIGTERM bridge check, intent commit, and ack write must share the same lock used by capture_sigterm() to install and restore Prefect’s SIGTERM handler. Otherwise, teardown can restore the original handler after the child decides it is safe to ack but before the runner observes b"a".

​
collect_task_run_inputs 

collect_task_run_inputs(expr: Any, max_depth: int = -1) -> set[Union[TaskRunResult, FlowRunResult]]
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()
 }

​
collect_task_run_inputs_sync 

collect_task_run_inputs_sync(expr: Any, future_cls: Any = PrefectFuture, max_depth: int = -1) -> set[Union[TaskRunResult, FlowRunResult]]
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_sync(v) for k, v in parameters.items()
 }

​
capture_sigterm 

capture_sigterm() -> Generator[None, Any, None]
Install a SIGTERM handler that raises TerminationSignal. Only the outermost Prefect flow engine in a process installs the handler by default. Nested subflow engines reuse that existing Prefect-owned handler when it is still active; if user or library code temporarily replaced SIGTERM, the nested scope reinstalls Prefect’s bridge for the duration of that scope. This guard is based on explicit local ownership state plus the currently installed handler, not on FlowRunContext: a fresh subprocess may hydrate a parent flow context before its own engine starts, and still needs to install a SIGTERM bridge for the child process. The handler does not need to interpret intent. The engine’s except TerminationSignal block consults prefect._internal.control_listener.get_intent() directly when dispatching (today: handle_cancellation vs handle_crash; in a future PR: plus handle_suspension). The runner control listener only connects while this context is active. Cancels that land before the bridge is armed fall back to the runner’s existing crash-style termination path; once this context is active, the child can acknowledge control intent and treat the later SIGTERM as an intentional cancellation.

​
resolve_inputs 

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

​
propose_state 

propose_state(client: 'PrefectClient', state: State[Any], flow_run_id: UUID, force: bool = False) -> State[Any]
Propose a new state for a flow 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 a flow run
  • flow_run_id: an optional flow run id, used when proposing flow run states
Returns:
  • a State model representation of the flow run state
Raises:
  • prefect.exceptions.Abort: if an ABORT instruction is received from the Prefect API

​
propose_state_sync 

propose_state_sync(client: 'SyncPrefectClient', state: State[Any], flow_run_id: UUID, force: bool = False) -> State[Any]
Propose a new state for a flow 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 flow run
  • flow_run_id: an optional flow run id, used when proposing flow run states
Returns:
  • a State model representation of the flow run state
Raises:
  • ValueError: if flow_run_id is not provided
  • prefect.exceptions.Abort: if an ABORT instruction is received from the Prefect API

​
get_state_for_result 

get_state_for_result(obj: Any) -> Optional[tuple[State, RunType]]
Get the state related to a result object. link_state_to_result must have been called first. For objects that support __weakref__, the entry stored by link_state_to_result carries a weak reference back to the original object. We verify here that the entry’s weak reference still points to the same object that registered the entry — not just to some object that happens to share its id(). This prevents stale hits caused by CPython recycling a freed memory address. Stale entries are evicted on detection. For objects that do not support __weakref__ (plain dict, list, set, str, int, tuple, …), the entry has no weak reference and we fall back to the legacy id()-only lookup. This preserves today’s behavior for those types — including the latent stale-id bug — and isolates the limitation to a single named code path. 
link_state_to_flow_run_result(state: State, result: Any) -> None
Creates a link between a state and flow run result 
link_state_to_task_run_result(state: State, result: Any) -> None
Creates a link between a state and task run result 
link_state_to_result(state: State, result: Any, run_type: RunType) -> 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.
  • Hash-based keying would also conflate equal-but-distinct objects from unrelated tasks.
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.

​
should_log_prints 

should_log_prints(flow_or_task: Union['Flow[..., Any]', 'Task[..., Any]']) -> bool

​
check_api_reachable 

check_api_reachable(client: 'PrefectClient', fail_message: str) -> None

​
emit_task_run_state_change_event 

emit_task_run_state_change_event(task_run: TaskRun, initial_state: Optional[State[Any]], validated_state: State[Any], follows: Optional[Event] = None) -> Optional[Event]

​
resolve_to_final_result 

resolve_to_final_result(expr: Any, context: dict[str, Any]) -> Any
Resolve any PrefectFuture, or State types nested in parameters into data. Designed to be use with visit_collection.

​
resolve_inputs_sync 

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