0.1.dev2192+g7c539c3.d20250403

flytekit.core.environment

Class	Description
`Environment`

Method	Description
`forge()`
`inherit()`

Property	Type	Description
`P`	`ParamSpec`
`T`	`TypeVar`

Methods

forge()

        
    
def forge(
    source: typing.Callable[typing.Concatenate[typing.Any, ~P], ~T],
) -> typing.Callable[[typing.Callable], typing.Callable[typing.Concatenate[typing.Any, ~P], ~T]]

Parameter	Type
`source`	`typing.Callable[typing.Concatenate[typing.Any, ~P], ~T]`

inherit()

        
    
def inherit(
    old: dict[str, typing.Any],
    new: dict[str, typing.Any],
) -> dict[str, typing.Any]

Parameter	Type
`old`	`dict[str, typing.Any]`
`new`	`dict[str, typing.Any]`

flytekit.core.environment.Environment

        
    
class Environment(
    _task_function: Optional[Callable[P, FuncOut]],
    task_config: Optional[T],
    cache: Union[bool, Cache],
    retries: int,
    interruptible: Optional[bool],
    deprecated: str,
    timeout: Union[datetime.timedelta, int],
    container_image: Optional[Union[str, ImageSpec]],
    environment: Optional[Dict[str, str]],
    requests: Optional[Resources],
    limits: Optional[Resources],
    secret_requests: Optional[List[Secret]],
    execution_mode: PythonFunctionTask.ExecutionBehavior,
    node_dependency_hints: Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]],
    task_resolver: Optional[TaskResolverMixin],
    docs: Optional[Documentation],
    disable_deck: Optional[bool],
    enable_deck: Optional[bool],
    deck_fields: Optional[Tuple[DeckField, ...]],
    pod_template: Optional['PodTemplate'],
    pod_template_name: Optional[str],
    accelerator: Optional[BaseAccelerator],
    pickle_untyped: bool,
    shared_memory: Optional[Union[L[True], str]],
    resources: Optional[Resources],
    kwargs,
)

This is the core decorator to use for any task type in flytekit.

Tasks are the building blocks of Flyte. They represent users code. Tasks have the following properties

Versioned (usually tied to the git revision SHA1)
Strong interfaces (specified inputs and outputs)
Declarative
Independently executable
Unit testable

For a simple python task,

        
    
@task
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

For specific task types

        
    
@task(task_config=Spark(), retries=3)
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

Please see some cookbook :std:ref:task examples <cookbook:tasks> for additional information.

Parameter	Type
`_task_function`	`Optional[Callable[P, FuncOut]]`
`task_config`	`Optional[T]`
`cache`	`Union[bool, Cache]`
`retries`	`int`
`interruptible`	`Optional[bool]`
`deprecated`	`str`
`timeout`	`Union[datetime.timedelta, int]`
`container_image`	`Optional[Union[str, ImageSpec]]`
`environment`	`Optional[Dict[str, str]]`
`requests`	`Optional[Resources]`
`limits`	`Optional[Resources]`
`secret_requests`	`Optional[List[Secret]]`
`execution_mode`	`PythonFunctionTask.ExecutionBehavior`
`node_dependency_hints`	`Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]]`
`task_resolver`	`Optional[TaskResolverMixin]`
`docs`	`Optional[Documentation]`
`disable_deck`	`Optional[bool]`
`enable_deck`	`Optional[bool]`
`deck_fields`	`Optional[Tuple[DeckField, ...]]`
`pod_template`	`Optional['PodTemplate']`
`pod_template_name`	`Optional[str]`
`accelerator`	`Optional[BaseAccelerator]`
`pickle_untyped`	`bool`
`shared_memory`	`Optional[Union[L[True], str]]`
`resources`	`Optional[Resources]`
`kwargs`	`**kwargs`

Methods

Method	Description
`dynamic()`	Please first see the comments for :py:func:`flytekit.
`extend()`	This is the core decorator to use for any task type in flytekit.
`show()`
`task()`	This is the core decorator to use for any task type in flytekit.
`update()`	This is the core decorator to use for any task type in flytekit.

dynamic()

        
    
def dynamic(
    _task_function: Optional[Callable[P, FuncOut]],
    task_config: Optional[T],
    cache: Union[bool, Cache],
    retries: int,
    interruptible: Optional[bool],
    deprecated: str,
    timeout: Union[datetime.timedelta, int],
    container_image: Optional[Union[str, ImageSpec]],
    environment: Optional[Dict[str, str]],
    requests: Optional[Resources],
    limits: Optional[Resources],
    secret_requests: Optional[List[Secret]],
    execution_mode: PythonFunctionTask.ExecutionBehavior,
    node_dependency_hints: Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]],
    task_resolver: Optional[TaskResolverMixin],
    docs: Optional[Documentation],
    disable_deck: Optional[bool],
    enable_deck: Optional[bool],
    deck_fields: Optional[Tuple[DeckField, ...]],
    pod_template: Optional['PodTemplate'],
    pod_template_name: Optional[str],
    accelerator: Optional[BaseAccelerator],
    pickle_untyped: bool,
    shared_memory: Optional[Union[L[True], str]],
    resources: Optional[Resources],
    kwargs,
) -> Union[Callable[P, FuncOut], Callable[[Callable[P, FuncOut]], PythonFunctionTask[T]], PythonFunctionTask[T]]

Please first see the comments for :py:func:flytekit.task and :py:func:flytekit.workflow. This dynamic concept is an amalgamation of both and enables the user to pursue some :std:ref:pretty incredible <cookbook:advanced_merge_sort> constructs.

In short, a task’s function is run at execution time only, and a workflow function is run at compilation time only (local execution notwithstanding). A dynamic workflow is modeled on the backend as a task, but at execution time, the function body is run to produce a workflow. It is almost as if the decorator changed from @task to @workflow except workflows cannot make use of their inputs like native Python values whereas dynamic workflows can. The resulting workflow is passed back to the Flyte engine and is run as a :std:ref:subworkflow <cookbook:subworkflows>. Simple usage

        
    
@dynamic
def my_dynamic_subwf(a: int) -> (typing.List[str], int):
    s = []
    for i in range(a):
        s.append(t1(a=i))
    return s, 5

Note in the code block that we call the Python range operator on the input. This is typically not allowed in a workflow but it is here. You can even express dependencies between tasks.

        
    
@dynamic
def my_dynamic_subwf(a: int, b: int) -> int:
    x = t1(a=a)
    return t2(b=b, x=x)

See the :std:ref:cookbook <cookbook:subworkflows> for a longer discussion.

Parameter	Type
`_task_function`	`Optional[Callable[P, FuncOut]]`
`task_config`	`Optional[T]`
`cache`	`Union[bool, Cache]`
`retries`	`int`
`interruptible`	`Optional[bool]`
`deprecated`	`str`
`timeout`	`Union[datetime.timedelta, int]`
`container_image`	`Optional[Union[str, ImageSpec]]`
`environment`	`Optional[Dict[str, str]]`
`requests`	`Optional[Resources]`
`limits`	`Optional[Resources]`
`secret_requests`	`Optional[List[Secret]]`
`execution_mode`	`PythonFunctionTask.ExecutionBehavior`
`node_dependency_hints`	`Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]]`
`task_resolver`	`Optional[TaskResolverMixin]`
`docs`	`Optional[Documentation]`
`disable_deck`	`Optional[bool]`
`enable_deck`	`Optional[bool]`
`deck_fields`	`Optional[Tuple[DeckField, ...]]`
`pod_template`	`Optional['PodTemplate']`
`pod_template_name`	`Optional[str]`
`accelerator`	`Optional[BaseAccelerator]`
`pickle_untyped`	`bool`
`shared_memory`	`Optional[Union[L[True], str]]`
`resources`	`Optional[Resources]`
`kwargs`	`**kwargs`

extend()

        
    
def extend(
    _task_function: Optional[Callable[P, FuncOut]],
    task_config: Optional[T],
    cache: Union[bool, Cache],
    retries: int,
    interruptible: Optional[bool],
    deprecated: str,
    timeout: Union[datetime.timedelta, int],
    container_image: Optional[Union[str, ImageSpec]],
    environment: Optional[Dict[str, str]],
    requests: Optional[Resources],
    limits: Optional[Resources],
    secret_requests: Optional[List[Secret]],
    execution_mode: PythonFunctionTask.ExecutionBehavior,
    node_dependency_hints: Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]],
    task_resolver: Optional[TaskResolverMixin],
    docs: Optional[Documentation],
    disable_deck: Optional[bool],
    enable_deck: Optional[bool],
    deck_fields: Optional[Tuple[DeckField, ...]],
    pod_template: Optional['PodTemplate'],
    pod_template_name: Optional[str],
    accelerator: Optional[BaseAccelerator],
    pickle_untyped: bool,
    shared_memory: Optional[Union[L[True], str]],
    resources: Optional[Resources],
    kwargs,
) -> Union[Callable[P, FuncOut], Callable[[Callable[P, FuncOut]], PythonFunctionTask[T]], PythonFunctionTask[T]]

This is the core decorator to use for any task type in flytekit.

Tasks are the building blocks of Flyte. They represent users code. Tasks have the following properties

Versioned (usually tied to the git revision SHA1)
Strong interfaces (specified inputs and outputs)
Declarative
Independently executable
Unit testable

For a simple python task,

        
    
@task
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

For specific task types

        
    
@task(task_config=Spark(), retries=3)
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

Please see some cookbook :std:ref:task examples <cookbook:tasks> for additional information.

Parameter	Type
`_task_function`	`Optional[Callable[P, FuncOut]]`
`task_config`	`Optional[T]`
`cache`	`Union[bool, Cache]`
`retries`	`int`
`interruptible`	`Optional[bool]`
`deprecated`	`str`
`timeout`	`Union[datetime.timedelta, int]`
`container_image`	`Optional[Union[str, ImageSpec]]`
`environment`	`Optional[Dict[str, str]]`
`requests`	`Optional[Resources]`
`limits`	`Optional[Resources]`
`secret_requests`	`Optional[List[Secret]]`
`execution_mode`	`PythonFunctionTask.ExecutionBehavior`
`node_dependency_hints`	`Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]]`
`task_resolver`	`Optional[TaskResolverMixin]`
`docs`	`Optional[Documentation]`
`disable_deck`	`Optional[bool]`
`enable_deck`	`Optional[bool]`
`deck_fields`	`Optional[Tuple[DeckField, ...]]`
`pod_template`	`Optional['PodTemplate']`
`pod_template_name`	`Optional[str]`
`accelerator`	`Optional[BaseAccelerator]`
`pickle_untyped`	`bool`
`shared_memory`	`Optional[Union[L[True], str]]`
`resources`	`Optional[Resources]`
`kwargs`	`**kwargs`

show()

def show()

task()

        
    
def task(
    _task_function: Optional[Callable[P, FuncOut]],
    task_config: Optional[T],
    cache: Union[bool, Cache],
    retries: int,
    interruptible: Optional[bool],
    deprecated: str,
    timeout: Union[datetime.timedelta, int],
    container_image: Optional[Union[str, ImageSpec]],
    environment: Optional[Dict[str, str]],
    requests: Optional[Resources],
    limits: Optional[Resources],
    secret_requests: Optional[List[Secret]],
    execution_mode: PythonFunctionTask.ExecutionBehavior,
    node_dependency_hints: Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]],
    task_resolver: Optional[TaskResolverMixin],
    docs: Optional[Documentation],
    disable_deck: Optional[bool],
    enable_deck: Optional[bool],
    deck_fields: Optional[Tuple[DeckField, ...]],
    pod_template: Optional['PodTemplate'],
    pod_template_name: Optional[str],
    accelerator: Optional[BaseAccelerator],
    pickle_untyped: bool,
    shared_memory: Optional[Union[L[True], str]],
    resources: Optional[Resources],
    kwargs,
) -> Union[Callable[P, FuncOut], Callable[[Callable[P, FuncOut]], PythonFunctionTask[T]], PythonFunctionTask[T]]

This is the core decorator to use for any task type in flytekit.

Tasks are the building blocks of Flyte. They represent users code. Tasks have the following properties

Versioned (usually tied to the git revision SHA1)
Strong interfaces (specified inputs and outputs)
Declarative
Independently executable
Unit testable

For a simple python task,

        
    
@task
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

For specific task types

        
    
@task(task_config=Spark(), retries=3)
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

Please see some cookbook :std:ref:task examples <cookbook:tasks> for additional information.

Parameter	Type
`_task_function`	`Optional[Callable[P, FuncOut]]`
`task_config`	`Optional[T]`
`cache`	`Union[bool, Cache]`
`retries`	`int`
`interruptible`	`Optional[bool]`
`deprecated`	`str`
`timeout`	`Union[datetime.timedelta, int]`
`container_image`	`Optional[Union[str, ImageSpec]]`
`environment`	`Optional[Dict[str, str]]`
`requests`	`Optional[Resources]`
`limits`	`Optional[Resources]`
`secret_requests`	`Optional[List[Secret]]`
`execution_mode`	`PythonFunctionTask.ExecutionBehavior`
`node_dependency_hints`	`Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]]`
`task_resolver`	`Optional[TaskResolverMixin]`
`docs`	`Optional[Documentation]`
`disable_deck`	`Optional[bool]`
`enable_deck`	`Optional[bool]`
`deck_fields`	`Optional[Tuple[DeckField, ...]]`
`pod_template`	`Optional['PodTemplate']`
`pod_template_name`	`Optional[str]`
`accelerator`	`Optional[BaseAccelerator]`
`pickle_untyped`	`bool`
`shared_memory`	`Optional[Union[L[True], str]]`
`resources`	`Optional[Resources]`
`kwargs`	`**kwargs`

update()

        
    
def update(
    _task_function: Optional[Callable[P, FuncOut]],
    task_config: Optional[T],
    cache: Union[bool, Cache],
    retries: int,
    interruptible: Optional[bool],
    deprecated: str,
    timeout: Union[datetime.timedelta, int],
    container_image: Optional[Union[str, ImageSpec]],
    environment: Optional[Dict[str, str]],
    requests: Optional[Resources],
    limits: Optional[Resources],
    secret_requests: Optional[List[Secret]],
    execution_mode: PythonFunctionTask.ExecutionBehavior,
    node_dependency_hints: Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]],
    task_resolver: Optional[TaskResolverMixin],
    docs: Optional[Documentation],
    disable_deck: Optional[bool],
    enable_deck: Optional[bool],
    deck_fields: Optional[Tuple[DeckField, ...]],
    pod_template: Optional['PodTemplate'],
    pod_template_name: Optional[str],
    accelerator: Optional[BaseAccelerator],
    pickle_untyped: bool,
    shared_memory: Optional[Union[L[True], str]],
    resources: Optional[Resources],
    kwargs,
) -> Union[Callable[P, FuncOut], Callable[[Callable[P, FuncOut]], PythonFunctionTask[T]], PythonFunctionTask[T]]

This is the core decorator to use for any task type in flytekit.

Tasks are the building blocks of Flyte. They represent users code. Tasks have the following properties

Versioned (usually tied to the git revision SHA1)
Strong interfaces (specified inputs and outputs)
Declarative
Independently executable
Unit testable

For a simple python task,

        
    
@task
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

For specific task types

        
    
@task(task_config=Spark(), retries=3)
def my_task(x: int, y: typing.Dict[str, str]) -> str:
    ...

Please see some cookbook :std:ref:task examples <cookbook:tasks> for additional information.

Parameter	Type
`_task_function`	`Optional[Callable[P, FuncOut]]`
`task_config`	`Optional[T]`
`cache`	`Union[bool, Cache]`
`retries`	`int`
`interruptible`	`Optional[bool]`
`deprecated`	`str`
`timeout`	`Union[datetime.timedelta, int]`
`container_image`	`Optional[Union[str, ImageSpec]]`
`environment`	`Optional[Dict[str, str]]`
`requests`	`Optional[Resources]`
`limits`	`Optional[Resources]`
`secret_requests`	`Optional[List[Secret]]`
`execution_mode`	`PythonFunctionTask.ExecutionBehavior`
`node_dependency_hints`	`Optional[Iterable[Union[PythonFunctionTask, _annotated_launchplan.LaunchPlan, _annotated_workflow.WorkflowBase]]]`
`task_resolver`	`Optional[TaskResolverMixin]`
`docs`	`Optional[Documentation]`
`disable_deck`	`Optional[bool]`
`enable_deck`	`Optional[bool]`
`deck_fields`	`Optional[Tuple[DeckField, ...]]`
`pod_template`	`Optional['PodTemplate']`
`pod_template_name`	`Optional[str]`
`accelerator`	`Optional[BaseAccelerator]`
`pickle_untyped`	`bool`
`shared_memory`	`Optional[Union[L[True], str]]`
`resources`	`Optional[Resources]`
`kwargs`	`**kwargs`

On this page

flytekit.core.environment

Directory

Classes

Methods

Variables

Methods

forge()

inherit()

flytekit.core.environment.Environment

Methods

dynamic()

extend()

show()

task()

update()