0.1.dev2184+g1e0cbe7.d20250401

flytekit.core.container_task

Class	Description
`ContainerTask`	This is an intermediate class that represents Flyte Tasks that run a container at execution time.

Property	Type	Description
`DOCKER_IMPORT_ERROR_MESSAGE`	`str`

flytekit.core.container_task.ContainerTask

This is an intermediate class that represents Flyte Tasks that run a container at execution time. This is the vast majority of tasks - the typical @task decorated tasks for instance all run a container. An example of something that doesn’t run a container would be something like the Athena SQL task.

        
    
class ContainerTask(
    name: str,
    image: typing.Union[str, flytekit.image_spec.image_spec.ImageSpec],
    command: typing.List[str],
    inputs: typing.Optional[typing.OrderedDict[str, typing.Type]],
    metadata: typing.Optional[flytekit.core.base_task.TaskMetadata],
    arguments: typing.Optional[typing.List[str]],
    outputs: typing.Optional[typing.Dict[str, typing.Type]],
    requests: typing.Optional[flytekit.core.resources.Resources],
    limits: typing.Optional[flytekit.core.resources.Resources],
    input_data_dir: typing.Optional[str],
    output_data_dir: typing.Optional[str],
    metadata_format: <enum 'MetadataFormat'>,
    io_strategy: typing.Optional[flytekit.core.container_task.ContainerTask.IOStrategy],
    secret_requests: typing.Optional[typing.List[flytekit.models.security.Secret]],
    pod_template: typing.Optional[ForwardRef('PodTemplate')],
    pod_template_name: typing.Optional[str],
    local_logs: bool,
    resources: typing.Optional[flytekit.core.resources.Resources],
    kwargs,
)

Parameter	Type
`name`	`str`
`image`	`typing.Union[str, flytekit.image_spec.image_spec.ImageSpec]`
`command`	`typing.List[str]`
`inputs`	`typing.Optional[typing.OrderedDict[str, typing.Type]]`
`metadata`	`typing.Optional[flytekit.core.base_task.TaskMetadata]`
`arguments`	`typing.Optional[typing.List[str]]`
`outputs`	`typing.Optional[typing.Dict[str, typing.Type]]`
`requests`	`typing.Optional[flytekit.core.resources.Resources]`
`limits`	`typing.Optional[flytekit.core.resources.Resources]`
`input_data_dir`	`typing.Optional[str]`
`output_data_dir`	`typing.Optional[str]`
`metadata_format`	`<enum 'MetadataFormat'>`
`io_strategy`	`typing.Optional[flytekit.core.container_task.ContainerTask.IOStrategy]`
`secret_requests`	`typing.Optional[typing.List[flytekit.models.security.Secret]]`
`pod_template`	`typing.Optional[ForwardRef('PodTemplate')]`
`pod_template_name`	`typing.Optional[str]`
`local_logs`	`bool`
`resources`	`typing.Optional[flytekit.core.resources.Resources]`
`kwargs`	`**kwargs`

Methods

Method	Description
`compile()`	Generates a node that encapsulates this task in a workflow definition.
`construct_node_metadata()`	Used when constructing the node that encapsulates this task as part of a broader workflow definition.
`dispatch_execute()`	This method translates Flyte’s Type system based input values and invokes the actual call to the executor.
`execute()`	This method will be invoked to execute the task.
`find_lhs()`
`get_config()`	Returns the task config as a serializable dictionary.
`get_container()`	Returns the container definition (if any) that is used to run the task on hosted Flyte.
`get_custom()`	Return additional plugin-specific custom data (if any) as a serializable dictionary.
`get_extended_resources()`	Returns the extended resources to allocate to the task on hosted Flyte.
`get_input_types()`	Returns the names and python types as a dictionary for the inputs of this task.
`get_k8s_pod()`	Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.
`get_sql()`	Returns the Sql definition (if any) that is used to run the task on hosted Flyte.
`get_type_for_input_var()`	Returns the python type for an input variable by name.
`get_type_for_output_var()`	Returns the python type for the specified output variable by name.
`local_execute()`	This function is used only in the local execution path and is responsible for calling dispatch execute.
`local_execution_mode()`
`post_execute()`	Post execute is called after the execution has completed, with the user_params and can be used to clean-up,.
`pre_execute()`	This is the method that will be invoked directly before executing the task method and before all the inputs.
`sandbox_execute()`	Call dispatch_execute, in the context of a local sandbox execution.

compile()

        
    
def compile(
    ctx: flytekit.core.context_manager.FlyteContext,
    args,
    kwargs,
) -> typing.Union[typing.Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise, NoneType]

Generates a node that encapsulates this task in a workflow definition.

Parameter	Type
`ctx`	`flytekit.core.context_manager.FlyteContext`
`args`	`*args`
`kwargs`	`**kwargs`

construct_node_metadata()

def construct_node_metadata()

Used when constructing the node that encapsulates this task as part of a broader workflow definition.

dispatch_execute()

        
    
def dispatch_execute(
    ctx: flytekit.core.context_manager.FlyteContext,
    input_literal_map: flytekit.models.literals.LiteralMap,
) -> typing.Union[flytekit.models.literals.LiteralMap, flytekit.models.dynamic_job.DynamicJobSpec, typing.Coroutine]

This method translates Flyte’s Type system based input values and invokes the actual call to the executor This method is also invoked during runtime.

VoidPromise is returned in the case when the task itself declares no outputs.
Literal Map is returned when the task returns either one more outputs in the declaration. Individual outputs may be none
DynamicJobSpec is returned when a dynamic workflow is executed

Parameter	Type
`ctx`	`flytekit.core.context_manager.FlyteContext`
`input_literal_map`	`flytekit.models.literals.LiteralMap`

execute()

        
    
def execute(
    kwargs,
) -> flytekit.models.literals.LiteralMap

This method will be invoked to execute the task.

Parameter	Type
`kwargs`	`**kwargs`

find_lhs()

def find_lhs()

get_config()

        
    
def get_config(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[typing.Dict[str, str]]

Returns the task config as a serializable dictionary. This task config consists of metadata about the custom defined for this task.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_container()

        
    
def get_container(
    settings: flytekit.configuration.SerializationSettings,
) -> flytekit.models.task.Container

Returns the container definition (if any) that is used to run the task on hosted Flyte.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_custom()

        
    
def get_custom(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[typing.Dict[str, typing.Any]]

Return additional plugin-specific custom data (if any) as a serializable dictionary.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_extended_resources()

        
    
def get_extended_resources(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[flyteidl.core.tasks_pb2.ExtendedResources]

Returns the extended resources to allocate to the task on hosted Flyte.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_input_types()

def get_input_types()

Returns the names and python types as a dictionary for the inputs of this task.

get_k8s_pod()

        
    
def get_k8s_pod(
    settings: flytekit.configuration.SerializationSettings,
) -> flytekit.models.task.K8sPod

Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_sql()

        
    
def get_sql(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[flytekit.models.task.Sql]

Returns the Sql definition (if any) that is used to run the task on hosted Flyte.

Parameter	Type
`settings`	`flytekit.configuration.SerializationSettings`

get_type_for_input_var()

        
    
def get_type_for_input_var(
    k: str,
    v: typing.Any,
) -> typing.Type[typing.Any]

Returns the python type for an input variable by name.

Parameter	Type
`k`	`str`
`v`	`typing.Any`

get_type_for_output_var()

        
    
def get_type_for_output_var(
    k: str,
    v: typing.Any,
) -> typing.Type[typing.Any]

Returns the python type for the specified output variable by name.

Parameter	Type
`k`	`str`
`v`	`typing.Any`

local_execute()

        
    
def local_execute(
    ctx: flytekit.core.context_manager.FlyteContext,
    kwargs,
) -> typing.Union[typing.Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise, typing.Coroutine, NoneType]

This function is used only in the local execution path and is responsible for calling dispatch execute. Use this function when calling a task with native values (or Promises containing Flyte literals derived from Python native values).

Parameter	Type
`ctx`	`flytekit.core.context_manager.FlyteContext`
`kwargs`	`**kwargs`

local_execution_mode()

def local_execution_mode()

post_execute()

        
    
def post_execute(
    user_params: typing.Optional[flytekit.core.context_manager.ExecutionParameters],
    rval: typing.Any,
) -> typing.Any

Post execute is called after the execution has completed, with the user_params and can be used to clean-up, or alter the outputs to match the intended tasks outputs. If not overridden, then this function is a No-op

Parameter	Type
`user_params`	`typing.Optional[flytekit.core.context_manager.ExecutionParameters]`
`rval`	`typing.Any`

pre_execute()

        
    
def pre_execute(
    user_params: typing.Optional[flytekit.core.context_manager.ExecutionParameters],
) -> typing.Optional[flytekit.core.context_manager.ExecutionParameters]

This is the method that will be invoked directly before executing the task method and before all the inputs are converted. One particular case where this is useful is if the context is to be modified for the user process to get some user space parameters. This also ensures that things like SparkSession are already correctly setup before the type transformers are called

This should return either the same context of the mutated context

Parameter	Type
`user_params`	`typing.Optional[flytekit.core.context_manager.ExecutionParameters]`

sandbox_execute()

        
    
def sandbox_execute(
    ctx: flytekit.core.context_manager.FlyteContext,
    input_literal_map: flytekit.models.literals.LiteralMap,
) -> flytekit.models.literals.LiteralMap

Call dispatch_execute, in the context of a local sandbox execution. Not invoked during runtime.

Parameter	Type
`ctx`	`flytekit.core.context_manager.FlyteContext`
`input_literal_map`	`flytekit.models.literals.LiteralMap`

Properties

Property	Type	Description
`deck_fields`		If not empty, this task will output deck html file for the specified decks
`disable_deck`		If true, this task will not output deck html file
`docs`
`enable_deck`		If true, this task will output deck html file
`environment`		Any environment variables that supplied during the execution of the task.
`instantiated_in`
`interface`
`lhs`
`location`
`metadata`
`name`
`python_interface`		Returns this task’s python interface.
`resources`
`security_context`
`task_config`		Returns the user-specified task config which is used for plugin-specific handling of the task.
`task_type`
`task_type_version`

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