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 parallel. It manages execution parameters including concurrency limits, minimum success counts, and success ratios to control how the array of sub-tasks is processed. The class automatically transforms the target's interface to handle list-based inputs and outputs, supporting both local execution and remote workflow compilation.

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	Optional[_workflow_model.NodeMetadata]	The metadata for the underlying node
name	string	The name of the target entity, used for node identification within the workflow.
python_interface	flyte_interface.Interface	The transformed interface representing the list-based inputs and outputs for local execution.
interface	_interface_models.TypedInterface	The transformed typed interface used for remote execution and serialization.
bindings	List[_literal_models.Binding] = []	A list of input bindings that define how data is passed to the mapped task.
upstream_nodes	List[Node] = []	A list of nodes that must complete before this node can execute, currently returning an empty list.
flyte_entity	Any	The underlying Flyte entity (task or launch plan) being executed by this node.
data_mode	_core_workflow.ArrayNode.DataMode	Determines how input data is partitioned, such as single input file or individual files.
min_success_ratio	Optional[float] = 1.0	The minimum ratio of successful executions.
min_successes	Optional[int] = 0	The minimum number of successful executions. If set, this takes precedence over min_success_ratio
concurrency	Optional[int]	If specified, this limits the number of mapped tasks than can run in parallel to the given batch size.
execution_mode	_core_workflow.ArrayNode.ExecutionMode	Defines the state management strategy for the array node, such as full or minimal state.
is_original_sub_node_interface	boolean = true	A boolean flag indicating if the node uses the original sub-node interface.
bound_inputs	Set[str] = set()	A set of input names that are bound to specific values and not mapped over.

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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 the workflow.
min_successes	Optional[int] = None	The minimum number of successful executions required.
min_success_ratio	Optional[float] = None	The minimum ratio of successful executions required (defaults to 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: ...

Constructs the metadata for the underlying node, defaulting to the target entity 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: ...

Retrieves the name of the target Flyte entity associated with this node.

Returns

Type	Description
str	The string identifier of the target entity.

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python_interface()

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

Provides the Python-native interface definition for the array node, typically transformed to represent list inputs/outputs.

Returns

Type	Description
flyte_interface.Interface	The interface object defining the Python types for inputs and outputs.

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interface()

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

Retrieves the typed interface models for the node, used primarily during serialization.

Returns

Type	Description
_interface_models.TypedInterface	The low-level typed interface model for the remote entity.

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bindings()

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

Returns the list of literal bindings that map workflow inputs to the node's parameters.

Returns

Type	Description
List[_literal_models.Binding]	A list of bindings representing the data flow into the node.

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upstream_nodes()

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

Identifies the nodes that must complete execution before this node can start.

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 (e.g., LaunchPlan or Task) that this node maps over.

Returns

Type	Description
Any	The target entity instance.

---

data_mode()

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

Indicates how data is partitioned and passed to the sub-tasks (e.g., single input file vs individual files).

Returns

Type	Description
_core_workflow.ArrayNode.DataMode	The data mode enum value determining input handling.

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local_execute()

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

Simulates the array execution locally by iterating over input lists and invoking the target entity for each element.

Parameters

Name	Type	Description
ctx	FlyteContext	The execution context providing access to configuration and state.
kwargs	Any	The keyword arguments representing the input lists to be mapped 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): ...

Defines the execution state mode for local runs.

Returns

Type	Description
Any	The local task execution mode constant.

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min_success_ratio()

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

Fetches the minimum ratio of successful sub-task executions required for the ArrayNode to be considered successful.

Returns

Type	Description
Optional[float]	A float between 0 and 1, or None if min_successes is used instead.

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min_successes()

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

Fetches the absolute minimum number of successful sub-task executions required.

Returns

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

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concurrency()

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

Fetches the limit on the number of sub-tasks that can run in parallel.

Returns

Type	Description
Optional[int]	The maximum batch size for parallel execution, or None for workflow default.

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execution_mode()

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

Indicates the execution strategy, such as FULL_STATE or MINIMAL_STATE, based on the target entity type.

Returns

Type	Description
_core_workflow.ArrayNode.ExecutionMode	The execution mode enum value.

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is_original_sub_node_interface()

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

Indicates 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 input names that are bound to specific values rather than mapped over.

Returns

Type	Description
Set[str]	An empty set as bound inputs are currently not supported.

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