0.1.dev2192+g7c539c3.d20250403

flytekit

This package contains all of the most common abstractions you’ll need to write Flyte workflows and extend Flytekit.

Basic Authoring

These are the essentials needed to get started writing tasks and workflows.

  • task
  • workflow
  • kwtypes
  • current_context
  • ExecutionParameters
  • FlyteContext
  • map_task
  • ImperativeWorkflow
  • create_node
  • NodeOutput
  • FlyteContextManager

Local Execution

Tasks and Workflows can both be locally run, assuming the relevant tasks are capable of local execution. This is useful for unit testing.

Branching and Conditionals

Branches and conditionals can be expressed explicitly in Flyte. These conditions are evaluated in the flyte engine and hence should be used for control flow. “dynamic workflows” can be used to perform custom conditional logic not supported by flytekit.

Customizing Tasks & Workflows

  • TaskMetadata - Wrapper object that allows users to specify Task
  • Resources - Things like CPUs/Memory, etc.
  • WorkflowFailurePolicy - Customizes what happens when a workflow fails.
  • PodTemplate - Custom PodTemplate for a task.

Dynamic and Nested Workflows

See the Dynamic module for more information.

Signaling
  • approve
  • sleep
  • wait_for_input

Scheduling

  • CronSchedule
  • FixedRate
Notifications
  • Email
  • PagerDuty
  • Slack
Reference Entities
  • get_reference_entity
  • LaunchPlanReference
  • TaskReference
  • WorkflowReference
  • reference_task
  • reference_workflow
  • reference_launch_plan
Core Task Types
  • SQLTask
  • ContainerTask
  • PythonFunctionTask
  • PythonInstanceTask
  • LaunchPlan
Secrets and SecurityContext
  • Secret
  • SecurityContext
Common Flyte IDL Objects
  • AuthRole
  • Labels
  • Annotations
  • WorkflowExecutionPhase
  • Blob
  • BlobMetadata
  • Literal
  • Scalar
  • LiteralType
  • BlobType

Directory

Methods

Method Description
current_context() Use this method to get a handle of specific parameters available in a flyte task.
load_implicit_plugins() This method allows loading all plugins that have the entrypoint specification.
new_context()

Variables

Property Type Description
LOGGING_RICH_FMT_ENV_VAR str

Methods

current_context()

def current_context()

Use this method to get a handle of specific parameters available in a flyte task.

Usage

flytekit.current_context().logging.info(...)

Available params are documented in :py:class:flytekit.core.context_manager.ExecutionParams. There are some special params, that should be available

load_implicit_plugins()

def load_implicit_plugins()

This method allows loading all plugins that have the entrypoint specification. This uses the plugin loading behavior.

This is an opt in system and plugins that have an implicit loading requirement should add the implicit loading entrypoint specification to their setup.py. The following example shows how we can autoload a module called fsspec (whose init files contains the necessary plugin registration step)

The group is always flytekit.plugins

 
setup(
    ...
    entry_points={'flytekit.plugins': 'fsspec=flytekitplugins.fsspec'},
    ...
)

This works as long as the fsspec module has

For data persistence plugins:

 
DataPersistencePlugins.register_plugin(f"{k}://", FSSpecPersistence, force=True)

OR for type plugins:

TypeEngine.register(PanderaTransformer())
# etc

new_context()

def new_context()