ArrayNode

This class represents a node that executes a target Flyte entity, such as a launch plan or task, over a collection of inputs in an array-like fashion. It provides mechanisms to control execution through concurrency limits and success thresholds, supporting both minimum success counts and ratios. The class automatically transforms the target's interface to handle list-based inputs and outputs while managing data and execution modes based on the target entity type.

Attributes

Attribute	Type	Description
target	Union[LaunchPlan, ReferenceTask, FlyteLaunchPlan]	The target Flyte entity to map over
id	string	Unique identifier for the node, derived from the target entity's name.
metadata	NodeMetadata = null	The metadata for the underlying node
concurrency	integer = null	If specified, this limits the number of mapped tasks than can run in parallel to the given batch size.
min_successes	integer = 0	The minimum number of successful executions. If set, this takes precedence over min_success_ratio
min_success_ratio	float = 1.0	The minimum ratio of successful executions.
bindings	List[Binding] = []	A list of input bindings that map workflow data to the node's interface.
python_interface	Interface	The transformed Python interface representing the collection-based inputs and outputs of the array node.
interface	TypedInterface	The transformed typed interface used for serialization and remote execution.
data_mode	DataMode	Determines how input data is partitioned, such as using a single input file or individual files per map instance.
execution_mode	ExecutionMode	Defines the state management strategy for the node, such as FULL_STATE or MINIMAL_STATE.

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Constructor

Signature

def ArrayNode(
        self,
        target: Union[LaunchPlan, ReferenceTask, "FlyteLaunchPlan"],
        bindings: Optional[List[_literal_models.Binding]] = None,
        concurrency: Optional[int] = None,
        min_successes: Optional[int] = None,
        min_success_ratio: Optional[float] = None,
        metadata: Optional[_workflow_model.NodeMetadata] = None,
    ): ...

Parameters

Name	Type	Description
target	Union[LaunchPlan, ReferenceTask, FlyteLaunchPlan]	The target Flyte entity to map over.
bindings	Optional[List[_literal_models.Binding]] = None	A list of input bindings for the node.
concurrency	Optional[int] = None	Limits the number of mapped tasks running in parallel. 0 means unbounded; None inherits from workflow.
min_successes	Optional[int] = None	The minimum absolute number of successful executions required.
min_success_ratio	Optional[float] = None	The minimum ratio of successful executions required (default is 1.0 if min_successes is not set).
metadata	Optional[_workflow_model.NodeMetadata] = None	Metadata for the underlying node.

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Methods

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construct_node_metadata()

def construct_node_metadata(self) -> _workflow_model.NodeMetadata: ...

Builds the metadata for the node, defaulting to the target entity's name if no specific metadata is provided.

Returns

Type	Description
_workflow_model.NodeMetadata	The metadata object containing configuration for the workflow node.

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name()

@property
def name(self) -> str: ...

Fetches the identifier of the target Flyte entity.

Returns

Type	Description
str	The name of the target entity being mapped.

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python_interface()

@property
def python_interface(self) -> flyte_interface.Interface: ...

Retrieves the Python-native interface transformed for list-based inputs and outputs.

Returns

Type	Description
flyte_interface.Interface	The interface representing the collection-based inputs and outputs for the array node.

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interface()

@property
def interface(self) -> _interface_models.TypedInterface: ...

Retrieves the serialized typed interface for remote entities.

Returns

Type	Description
_interface_models.TypedInterface	The low-level typed interface used for serialization and remote execution.

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bindings()

@property
def bindings(self) -> List[_literal_models.Binding]: ...

Retrieves the list of input bindings associated with this node.

Returns

Type	Description
List[_literal_models.Binding]	A list of bindings that map workflow inputs to the node's parameters.

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upstream_nodes()

@property
def upstream_nodes(self) -> List[Node]: ...

Returns the list of nodes that this node depends on.

Returns

Type	Description
List[Node]	An empty list as upstream dependencies are managed at the workflow level.

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flyte_entity()

@property
def flyte_entity(self) -> Any: ...

Returns the underlying Flyte entity that is being executed in a mapped fashion.

Returns

Type	Description
Any	The target LaunchPlan or Task being mapped over.

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data_mode()

@property
def data_mode(self) -> _core_workflow.ArrayNode.DataMode: ...

Indicates how input data is partitioned and passed to the sub-nodes.

Returns

Type	Description
_core_workflow.ArrayNode.DataMode	The data mode specifying single or individual input file handling.

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local_execute()

def local_execute(self, ctx: FlyteContext, **kwargs) -> Union[Tuple[Promise], Promise, VoidPromise]: ...

Executes the array node locally by iterating over input collections and invoking the target entity for each element.

Parameters

Name	Type	Description
ctx	FlyteContext	The current execution context providing access to local state and configuration.
kwargs	Any	The keyword arguments representing the input collections to map over.

Returns

Type	Description
Union[Tuple[Promise], Promise, VoidPromise]	A promise containing a collection of results from the successful sub-task executions.

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local_execution_mode()

def local_execution_mode(self): ...

Returns the execution mode for local runs.

Returns

Type	Description
null	The local task execution mode constant.

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min_success_ratio()

@property
def min_success_ratio(self) -> Optional[float]: ...

Retrieves the minimum ratio of successful sub-node executions required for the array node to be considered successful.

Returns

Type	Description
Optional[float]	A float between 0 and 1 representing the success threshold ratio.

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min_successes()

@property
def min_successes(self) -> Optional[int]: ...

Retrieves the absolute minimum number of successful sub-node executions required.

Returns

Type	Description
Optional[int]	The integer count of required successful executions.

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concurrency()

@property
def concurrency(self) -> Optional[int]: ...

Retrieves the maximum number of sub-nodes allowed to run in parallel.

Returns

Type	Description
Optional[int]	The concurrency limit, or None if it should inherit from the workflow.

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execution_mode()

@property
def execution_mode(self) -> _core_workflow.ArrayNode.ExecutionMode: ...

Indicates the execution strategy used by the array node (e.g., Full State vs Minimal State).

Returns

Type	Description
_core_workflow.ArrayNode.ExecutionMode	The execution mode determined by the type of the target entity.

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is_original_sub_node_interface()

@property
def is_original_sub_node_interface(self) -> bool: ...

Flag indicating if the node uses the original sub-node interface definition.

Returns

Type	Description
bool	Always returns True for ArrayNode instances.

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bound_inputs()

@property
def bound_inputs(self) -> Set[str]: ...

Returns the set of inputs that are bound to specific values rather than mapped over.

Returns

Type	Description
Set[str]	An empty set of input names.

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