flytekit.remote.launch_plan.FlyteLaunchPlan

class flytekit.remote.launch_plan.FlyteLaunchPlan(id, *args, **kwargs)[source]

A class encapsulating a remote Flyte launch plan.

The spec for a Launch Plan.

Parameters
  • workflow_id (flytekit.models.core.identifier.Identifier) – Unique identifier for the workflow in question

  • entity_metadata (LaunchPlanMetadata) – Metadata

  • default_inputs (flytekit.models.interface.ParameterMap) – Input values to be passed for the execution

  • fixed_inputs (flytekit.models.literals.LiteralMap) – Fixed, non-overridable inputs for the Launch Plan

  • flytekit.models.common.Labels – Any custom kubernetes labels to apply to workflows executed by this launch plan.

  • annotations (flytekit.models.admin.common.Annotations) – Any custom kubernetes annotations to apply to workflows executed by this launch plan.

  • auth_role (flytekit.models.admin.common.AuthRole) – The auth method with which to execute the workflow.

  • raw_output_data_config (flytekit.models.admin.common.RawOutputDataConfig) – Value for where to store offloaded data like Blobs and Schemas.

  • int (max_parallelism) – Controls the maximum number of tasknodes that can be run in parallel for the entire workflow. This is useful to achieve fairness. Note: MapTasks are regarded as one unit, and parallelism/concurrency of MapTasks is independent from this.

Methods

classmethod from_flyte_idl(pb2)
Parameters

pb2 (flyteidl.admin.launch_plan_pb2.LaunchPlanSpec) –

Return type

LaunchPlanSpec

classmethod promote_from_model(id, model)[source]
Parameters
  • id (flytekit.remote.identifier.Identifier) –

  • model (flytekit.models.admin.launch_plan.LaunchPlanSpec) –

Return type

flytekit.remote.launch_plan.FlyteLaunchPlan

short_string()
Return type

Text

to_flyte_idl()
Return type

flyteidl.admin.launch_plan_pb2.LaunchPlanSpec

update(state)[source]
Parameters

state (flytekit.models.admin.launch_plan.LaunchPlanState) –

verbose_string()
Return type

Text

Attributes

annotations

The annotations to execute the workflow with :rtype: flytekit.models.admin.common.Annotations

auth_role

The authorization method with which to execute the workflow. :rtype: flytekit.models.admin.common.AuthRole

default_inputs

Input values to be passed for the execution :rtype: flytekit.models.interface.ParameterMap

entity_metadata

LaunchPlanMetadata

Type

rtype

entity_type_text
fixed_inputs

Fixed, non-overridable inputs for the Launch Plan :rtype: flytekit.models.literals.LiteralMap

guessed_python_interface
id
interface

The interface is not technically part of the admin.LaunchPlanSpec in the IDL, however the workflow ID is, and from the workflow ID, fetch will fill in the interface. This is nice because then you can __call__ the= object and get a node.

is_empty
is_scheduled
labels

The labels to execute the workflow with :rtype: flytekit.models.admin.common.Labels

max_parallelism
raw_output_data_config

Where to store offloaded data like Blobs and Schemas :rtype: flytekit.models.admin.common.RawOutputDataConfig

resource_type
workflow_id