# flytekit.core.python_function_task

## Directory

### Classes

| Class | Description |
|-|-|
| [`AsyncPythonFunctionTask`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskasyncpythonfunctiontask) | This is the base task for eager tasks, as well as normal async tasks. |
| [`EagerAsyncPythonFunctionTask`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskeagerasyncpythonfunctiontask) | This is the base eager task (aka eager workflow) type. |
| [`EagerFailureHandlerTask`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskeagerfailurehandlertask) |  |
| [`EagerFailureTaskResolver`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskeagerfailuretaskresolver) |  |
| [`PythonFunctionTask`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskpythonfunctiontask) | A Python Function task should be used as the base for all extensions that have a python function. |
| [`PythonInstanceTask`](https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/page.md#flytekitcorepython_function_taskpythoninstancetask) | This class should be used as the base class for all Tasks that do not have a user defined function body, but have. |

### Variables

| Property | Type | Description |
|-|-|-|
| `CLEANUP_LOOP_DELAY_SECONDS` | `int` |  |
| `EAGER_ROOT_ENV_NAME` | `str` |  |
| `T` | `TypeVar` |  |
| `eager_failure_task_resolver` | `EagerFailureTaskResolver` |  |

## flytekit.core.python_function_task.AsyncPythonFunctionTask

This is the base task for eager tasks, as well as normal async tasks
Really only need to override the call function.

### Parameters

```python
class AsyncPythonFunctionTask(
    task_config: T,
    task_function: Callable,
    task_type,
    ignore_input_vars: Optional[List[str]],
    execution_mode: ExecutionBehavior,
    task_resolver: Optional[TaskResolverMixin],
    node_dependency_hints: Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]],
    pickle_untyped: bool,
    kwargs,
)
```
| Parameter | Type | Description |
|-|-|-|
| `task_config` | `T` | |
| `task_function` | `Callable` | |
| `task_type` |  | |
| `ignore_input_vars` | `Optional[List[str]]` | |
| `execution_mode` | `ExecutionBehavior` | |
| `task_resolver` | `Optional[TaskResolverMixin]` | |
| `node_dependency_hints` | `Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]]` | |
| `pickle_untyped` | `bool` | |
| `kwargs` | `**kwargs` | |

### Properties

| Property | Type | Description |
|-|-|-|
| `container_image` | `None` |  |
| `deck_fields` | `None` | If not empty, this task will output deck html file for the specified decks |
| `disable_deck` | `None` | If true, this task will not output deck html file |
| `docs` | `None` |  |
| `enable_deck` | `None` | If true, this task will output deck html file |
| `environment` | `None` | Any environment variables that supplied during the execution of the task. |
| `execution_mode` | `None` |  |
| `instantiated_in` | `None` |  |
| `interface` | `None` |  |
| `lhs` | `None` |  |
| `location` | `None` |  |
| `metadata` | `None` |  |
| `name` | `None` | Returns the name of the task. |
| `node_dependency_hints` | `None` |  |
| `python_interface` | `None` | Returns this task's python interface. |
| `resources` | `None` |  |
| `security_context` | `None` |  |
| `task_config` | `None` | Returns the user-specified task config which is used for plugin-specific handling of the task. |
| `task_function` | `None` |  |
| `task_resolver` | `None` |  |
| `task_type` | `None` |  |
| `task_type_version` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`async_execute()`](#async_execute) | Overrides the base execute function. |
| [`compile()`](#compile) | Generates a node that encapsulates this task in a workflow definition. |
| [`compile_into_workflow()`](#compile_into_workflow) | In the case of dynamic workflows, this function will produce a workflow definition at execution time which will. |
| [`construct_node_metadata()`](#construct_node_metadata) | Used when constructing the node that encapsulates this task as part of a broader workflow definition. |
| [`dispatch_execute()`](#dispatch_execute) | This method translates Flyte's Type system based input values and invokes the actual call to the executor. |
| [`dynamic_execute()`](#dynamic_execute) | By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte. |
| [`execute()`](#execute) | Overrides the base execute function. |
| [`find_lhs()`](#find_lhs) |  |
| [`get_command()`](#get_command) | Returns the command which should be used in the container definition for the serialized version of this task. |
| [`get_config()`](#get_config) | Returns the task config as a serializable dictionary. |
| [`get_container()`](#get_container) | Returns the container definition (if any) that is used to run the task on hosted Flyte. |
| [`get_custom()`](#get_custom) | Return additional plugin-specific custom data (if any) as a serializable dictionary. |
| [`get_default_command()`](#get_default_command) | Returns the default pyflyte-execute command used to run this on hosted Flyte platforms. |
| [`get_extended_resources()`](#get_extended_resources) | Returns the extended resources to allocate to the task on hosted Flyte. |
| [`get_image()`](#get_image) | Update image spec based on fast registration usage, and return string representing the image. |
| [`get_input_types()`](#get_input_types) | Returns the names and python types as a dictionary for the inputs of this task. |
| [`get_k8s_pod()`](#get_k8s_pod) | Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte. |
| [`get_sql()`](#get_sql) | Returns the Sql definition (if any) that is used to run the task on hosted Flyte. |
| [`get_type_for_input_var()`](#get_type_for_input_var) | Returns the python type for an input variable by name. |
| [`get_type_for_output_var()`](#get_type_for_output_var) | Returns the python type for the specified output variable by name. |
| [`local_execute()`](#local_execute) | This function is used only in the local execution path and is responsible for calling dispatch execute. |
| [`local_execution_mode()`](#local_execution_mode) |  |
| [`post_execute()`](#post_execute) | Post execute is called after the execution has completed, with the user_params and can be used to clean-up,. |
| [`pre_execute()`](#pre_execute) | This is the method that will be invoked directly before executing the task method and before all the inputs. |
| [`reset_command_fn()`](#reset_command_fn) | Resets the command which should be used in the container definition of this task to the default arguments. |
| [`sandbox_execute()`](#sandbox_execute) | Call dispatch_execute, in the context of a local sandbox execution. |
| [`set_command_fn()`](#set_command_fn) | By default, the task will run on the Flyte platform using the pyflyte-execute command. |
| [`set_resolver()`](#set_resolver) | By default, flytekit uses the DefaultTaskResolver to resolve the task. |

#### async_execute()

```python
def async_execute(
    args,
    kwargs,
) -> Any
```
Overrides the base execute function. This function does not handle dynamic at all. Eager and dynamic don't mix.

| Parameter | Type | Description |
|-|-|-|
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### compile()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### compile_into_workflow()

```python
def compile_into_workflow(
    ctx: FlyteContext,
    task_function: Callable,
    kwargs,
) -> Union[_dynamic_job.DynamicJobSpec, _literal_models.LiteralMap]
```
In the case of dynamic workflows, this function will produce a workflow definition at execution time which will
then proceed to be executed.

| Parameter | Type | Description |
|-|-|-|
| `ctx` | `FlyteContext` | |
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### construct_node_metadata()

```python
def construct_node_metadata()
```
Used when constructing the node that encapsulates this task as part of a broader workflow definition.

#### dispatch_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### dynamic_execute()

```python
def dynamic_execute(
    task_function: Callable,
    kwargs,
) -> Any
```
By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte
literal wrappers so that the kwargs we are working with here are now Python native literal values. This
function is also expected to return Python native literal values.

Since the user code within a dynamic task constitute a workflow, we have to first compile the workflow, and
then execute that workflow.

When running for real in production, the task would stop after the compilation step, and then create a file
representing that newly generated workflow, instead of executing it.

| Parameter | Type | Description |
|-|-|-|
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### execute()

```python
def execute(
    args,
    kwargs,
) -> Any
```
Overrides the base execute function. This function does not handle dynamic at all. Eager and dynamic don't mix.

| Parameter | Type | Description |
|-|-|-|
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### find_lhs()

```python
def find_lhs()
```
#### get_command()

```python
def get_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the command which should be used in the container definition for the serialized version of this task
registered on a hosted Flyte platform.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_config()

```python
def get_config(
    settings: SerializationSettings,
) -> Optional[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 | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_container()

```python
def get_container(
    settings: SerializationSettings,
) -> _task_model.Container
```
Returns the container definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_custom()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_default_command()

```python
def get_default_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_extended_resources()

```python
def get_extended_resources(
    settings: SerializationSettings,
) -> Optional[tasks_pb2.ExtendedResources]
```
Returns the extended resources to allocate to the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_image()

```python
def get_image(
    settings: SerializationSettings,
) -> str
```
Update image spec based on fast registration usage, and return string representing the image

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_input_types()

```python
def get_input_types()
```
Returns the names and python types as a dictionary for the inputs of this task.

#### get_k8s_pod()

```python
def get_k8s_pod(
    settings: SerializationSettings,
) -> _task_model.K8sPod
```
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_sql()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_type_for_input_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### get_type_for_output_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### local_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `kwargs` | `**kwargs` | |

#### local_execution_mode()

```python
def local_execution_mode()
```
#### post_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | are the modified user params as created during the pre_execute step |
| `rval` | `typing.Any` | |

#### pre_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | |

#### reset_command_fn()

```python
def reset_command_fn()
```
Resets the command which should be used in the container definition of this task to the default arguments.
This is useful when the command line is overridden at serialization time.

#### sandbox_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### set_command_fn()

```python
def set_command_fn(
    get_command_fn: Optional[Callable[[SerializationSettings], List[str]]],
)
```
By default, the task will run on the Flyte platform using the pyflyte-execute command.
However, it can be useful to update the command with which the task is serialized for specific cases like
running map tasks ("pyflyte-map-execute") or for fast-executed tasks.

| Parameter | Type | Description |
|-|-|-|
| `get_command_fn` | `Optional[Callable[[SerializationSettings], List[str]]]` | |

#### set_resolver()

```python
def set_resolver(
    resolver: TaskResolverMixin,
)
```
By default, flytekit uses the DefaultTaskResolver to resolve the task. This method allows the user to set a custom
task resolver. It can be useful to override the task resolver for specific cases like running tasks in the jupyter notebook.

| Parameter | Type | Description |
|-|-|-|
| `resolver` | `TaskResolverMixin` | |

## flytekit.core.python_function_task.EagerAsyncPythonFunctionTask

This is the base eager task (aka eager workflow) type. It replaces the previous experiment eager task type circa
Q4 2024. Users unfamiliar with this concept should refer to the documentation for more information.
But basically, Python becomes propeller, and every task invocation, creates a stack frame on the Flyte cluster in
the form of an execution rather than on the actual memory stack.

### Parameters

```python
class EagerAsyncPythonFunctionTask(
    task_config: T,
    task_function: Callable,
    task_type,
    ignore_input_vars: Optional[List[str]],
    task_resolver: Optional[TaskResolverMixin],
    node_dependency_hints: Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]],
    enable_deck: bool,
    kwargs,
)
```
| Parameter | Type | Description |
|-|-|-|
| `task_config` | `T` | |
| `task_function` | `Callable` | |
| `task_type` |  | |
| `ignore_input_vars` | `Optional[List[str]]` | |
| `task_resolver` | `Optional[TaskResolverMixin]` | |
| `node_dependency_hints` | `Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]]` | |
| `enable_deck` | `bool` | |
| `kwargs` | `**kwargs` | |

### Properties

| Property | Type | Description |
|-|-|-|
| `container_image` | `None` |  |
| `deck_fields` | `None` | If not empty, this task will output deck html file for the specified decks |
| `disable_deck` | `None` | If true, this task will not output deck html file |
| `docs` | `None` |  |
| `enable_deck` | `None` | If true, this task will output deck html file |
| `environment` | `None` | Any environment variables that supplied during the execution of the task. |
| `execution_mode` | `None` |  |
| `instantiated_in` | `None` |  |
| `interface` | `None` |  |
| `lhs` | `None` |  |
| `location` | `None` |  |
| `metadata` | `None` |  |
| `name` | `None` | Returns the name of the task. |
| `node_dependency_hints` | `None` |  |
| `python_interface` | `None` | Returns this task's python interface. |
| `resources` | `None` |  |
| `security_context` | `None` |  |
| `task_config` | `None` | Returns the user-specified task config which is used for plugin-specific handling of the task. |
| `task_function` | `None` |  |
| `task_resolver` | `None` |  |
| `task_type` | `None` |  |
| `task_type_version` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`async_execute()`](#async_execute) | Overrides the base execute function. |
| [`compile()`](#compile) | Generates a node that encapsulates this task in a workflow definition. |
| [`compile_into_workflow()`](#compile_into_workflow) | In the case of dynamic workflows, this function will produce a workflow definition at execution time which will. |
| [`construct_node_metadata()`](#construct_node_metadata) | Used when constructing the node that encapsulates this task as part of a broader workflow definition. |
| [`dispatch_execute()`](#dispatch_execute) | This method translates Flyte's Type system based input values and invokes the actual call to the executor. |
| [`dynamic_execute()`](#dynamic_execute) | By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte. |
| [`execute()`](#execute) | Overrides the base execute function. |
| [`find_lhs()`](#find_lhs) |  |
| [`get_as_workflow()`](#get_as_workflow) |  |
| [`get_command()`](#get_command) | Returns the command which should be used in the container definition for the serialized version of this task. |
| [`get_config()`](#get_config) | Returns the task config as a serializable dictionary. |
| [`get_container()`](#get_container) | Returns the container definition (if any) that is used to run the task on hosted Flyte. |
| [`get_custom()`](#get_custom) | Return additional plugin-specific custom data (if any) as a serializable dictionary. |
| [`get_default_command()`](#get_default_command) | Returns the default pyflyte-execute command used to run this on hosted Flyte platforms. |
| [`get_extended_resources()`](#get_extended_resources) | Returns the extended resources to allocate to the task on hosted Flyte. |
| [`get_image()`](#get_image) | Update image spec based on fast registration usage, and return string representing the image. |
| [`get_input_types()`](#get_input_types) | Returns the names and python types as a dictionary for the inputs of this task. |
| [`get_k8s_pod()`](#get_k8s_pod) | Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte. |
| [`get_sql()`](#get_sql) | Returns the Sql definition (if any) that is used to run the task on hosted Flyte. |
| [`get_type_for_input_var()`](#get_type_for_input_var) | Returns the python type for an input variable by name. |
| [`get_type_for_output_var()`](#get_type_for_output_var) | Returns the python type for the specified output variable by name. |
| [`local_execute()`](#local_execute) | This function is used only in the local execution path and is responsible for calling dispatch execute. |
| [`local_execution_mode()`](#local_execution_mode) |  |
| [`post_execute()`](#post_execute) | Post execute is called after the execution has completed, with the user_params and can be used to clean-up,. |
| [`pre_execute()`](#pre_execute) | This is the method that will be invoked directly before executing the task method and before all the inputs. |
| [`reset_command_fn()`](#reset_command_fn) | Resets the command which should be used in the container definition of this task to the default arguments. |
| [`run()`](#run) | This is a helper function to help run eager parent tasks locally, pointing to a remote cluster. |
| [`run_with_backend()`](#run_with_backend) | This is the main entry point to kick off a live run. |
| [`sandbox_execute()`](#sandbox_execute) | Call dispatch_execute, in the context of a local sandbox execution. |
| [`set_command_fn()`](#set_command_fn) | By default, the task will run on the Flyte platform using the pyflyte-execute command. |
| [`set_resolver()`](#set_resolver) | By default, flytekit uses the DefaultTaskResolver to resolve the task. |

#### async_execute()

```python
def async_execute(
    args,
    kwargs,
) -> Any
```
Overrides the base execute function. This function does not handle dynamic at all. Eager and dynamic don't mix.

Some notes on the different call scenarios since it's a little different than other tasks.
a) starting local execution - eager_task()
    -> last condition of call handler,
    -> set execution mode and self.local_execute()
    -> self.execute(native_vals)
      -> 1) -> task function() or 2) -> self.run_with_backend()  # fn name will be changed.
b) inside an eager task local execution - calling normal_task()
    -> call handler detects in eager local execution (middle part of call handler)
    -> call normal_task's local_execute()
c) inside an eager task local execution - calling async_normal_task()
    -> produces a coro, which when awaited/run
        -> call handler detects in eager local execution (middle part of call handler)
        -> call async_normal_task's local_execute()
        -> call AsyncPythonFunctionTask's async_execute(), which awaits the task function
d) inside an eager task local execution - calling another_eager_task()
    -> produces a coro, which when awaited/run
        -> call handler detects in eager local execution (middle part of call handler)
        -> call another_eager_task's local_execute()
        -> results are returned instead of being passed to create_native_named_tuple
d) eager_task, starting backend execution from entrypoint.py
    -> eager_task.dispatch_execute(literals)
    -> eager_task.execute(native values)
    -> awaits eager_task.run_with_backend()  # fn name will be changed
e) in an eager task during backend execution, calling any flyte_entity()
    -> add the entity to the worker queue and await the result.

| Parameter | Type | Description |
|-|-|-|
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### compile()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### compile_into_workflow()

```python
def compile_into_workflow(
    ctx: FlyteContext,
    task_function: Callable,
    kwargs,
) -> Union[_dynamic_job.DynamicJobSpec, _literal_models.LiteralMap]
```
In the case of dynamic workflows, this function will produce a workflow definition at execution time which will
then proceed to be executed.

| Parameter | Type | Description |
|-|-|-|
| `ctx` | `FlyteContext` | |
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### construct_node_metadata()

```python
def construct_node_metadata()
```
Used when constructing the node that encapsulates this task as part of a broader workflow definition.

#### dispatch_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### dynamic_execute()

```python
def dynamic_execute(
    task_function: Callable,
    kwargs,
) -> Any
```
By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte
literal wrappers so that the kwargs we are working with here are now Python native literal values. This
function is also expected to return Python native literal values.

Since the user code within a dynamic task constitute a workflow, we have to first compile the workflow, and
then execute that workflow.

When running for real in production, the task would stop after the compilation step, and then create a file
representing that newly generated workflow, instead of executing it.

| Parameter | Type | Description |
|-|-|-|
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### execute()

```python
def execute(
    kwargs,
) -> Any
```
Overrides the base execute function. This function does not handle dynamic at all. Eager and dynamic don't mix.

| Parameter | Type | Description |
|-|-|-|
| `kwargs` | `**kwargs` | |

#### find_lhs()

```python
def find_lhs()
```
#### get_as_workflow()

```python
def get_as_workflow()
```
#### get_command()

```python
def get_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the command which should be used in the container definition for the serialized version of this task
registered on a hosted Flyte platform.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_config()

```python
def get_config(
    settings: SerializationSettings,
) -> Optional[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 | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_container()

```python
def get_container(
    settings: SerializationSettings,
) -> _task_model.Container
```
Returns the container definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_custom()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_default_command()

```python
def get_default_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_extended_resources()

```python
def get_extended_resources(
    settings: SerializationSettings,
) -> Optional[tasks_pb2.ExtendedResources]
```
Returns the extended resources to allocate to the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_image()

```python
def get_image(
    settings: SerializationSettings,
) -> str
```
Update image spec based on fast registration usage, and return string representing the image

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_input_types()

```python
def get_input_types()
```
Returns the names and python types as a dictionary for the inputs of this task.

#### get_k8s_pod()

```python
def get_k8s_pod(
    settings: SerializationSettings,
) -> _task_model.K8sPod
```
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_sql()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_type_for_input_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### get_type_for_output_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### local_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `kwargs` | `**kwargs` | |

#### local_execution_mode()

```python
def local_execution_mode()
```
#### post_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | are the modified user params as created during the pre_execute step |
| `rval` | `typing.Any` | |

#### pre_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | |

#### reset_command_fn()

```python
def reset_command_fn()
```
Resets the command which should be used in the container definition of this task to the default arguments.
This is useful when the command line is overridden at serialization time.

#### run()

```python
def run(
    remote: 'FlyteRemote',
    ss: SerializationSettings,
    kwargs,
)
```
This is a helper function to help run eager parent tasks locally, pointing to a remote cluster. This is used
only for local testing for now.

| Parameter | Type | Description |
|-|-|-|
| `remote` | `'FlyteRemote'` | |
| `ss` | `SerializationSettings` | |
| `kwargs` | `**kwargs` | |

#### run_with_backend()

```python
def run_with_backend(
    kwargs,
)
```
This is the main entry point to kick off a live run. Like if you're running locally, but want to use a
Flyte backend, or running for real on a Flyte backend.

| Parameter | Type | Description |
|-|-|-|
| `kwargs` | `**kwargs` | |

#### sandbox_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### set_command_fn()

```python
def set_command_fn(
    get_command_fn: Optional[Callable[[SerializationSettings], List[str]]],
)
```
By default, the task will run on the Flyte platform using the pyflyte-execute command.
However, it can be useful to update the command with which the task is serialized for specific cases like
running map tasks ("pyflyte-map-execute") or for fast-executed tasks.

| Parameter | Type | Description |
|-|-|-|
| `get_command_fn` | `Optional[Callable[[SerializationSettings], List[str]]]` | |

#### set_resolver()

```python
def set_resolver(
    resolver: TaskResolverMixin,
)
```
By default, flytekit uses the DefaultTaskResolver to resolve the task. This method allows the user to set a custom
task resolver. It can be useful to override the task resolver for specific cases like running tasks in the jupyter notebook.

| Parameter | Type | Description |
|-|-|-|
| `resolver` | `TaskResolverMixin` | |

## flytekit.core.python_function_task.EagerFailureHandlerTask

### Parameters

```python
class EagerFailureHandlerTask(
    name: str,
    container_image: Optional[Union[str, ImageSpec]],
    inputs: typing.Optional[typing.Dict[str, typing.Type]],
    kwargs,
)
```
| Parameter | Type | Description |
|-|-|-|
| `name` | `str` | |
| `container_image` | `Optional[Union[str, ImageSpec]]` | |
| `inputs` | `typing.Optional[typing.Dict[str, typing.Type]]` | |
| `kwargs` | `**kwargs` | |

### Properties

| Property | Type | Description |
|-|-|-|
| `container_image` | `None` |  |
| `deck_fields` | `None` | If not empty, this task will output deck html file for the specified decks |
| `disable_deck` | `None` | If true, this task will not output deck html file |
| `docs` | `None` |  |
| `enable_deck` | `None` | If true, this task will output deck html file |
| `environment` | `None` | Any environment variables that supplied during the execution of the task. |
| `instantiated_in` | `None` |  |
| `interface` | `None` |  |
| `lhs` | `None` |  |
| `location` | `None` |  |
| `metadata` | `None` |  |
| `name` | `None` |  |
| `python_interface` | `None` | Returns this task's python interface. |
| `resources` | `None` |  |
| `security_context` | `None` |  |
| `task_config` | `None` | Returns the user-specified task config which is used for plugin-specific handling of the task. |
| `task_resolver` | `None` |  |
| `task_type` | `None` |  |
| `task_type_version` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`compile()`](#compile) | Generates a node that encapsulates this task in a workflow definition. |
| [`construct_node_metadata()`](#construct_node_metadata) | Used when constructing the node that encapsulates this task as part of a broader workflow definition. |
| [`dispatch_execute()`](#dispatch_execute) | This task should only be called during remote execution. |
| [`execute()`](#execute) | This method will be invoked to execute the task. |
| [`find_lhs()`](#find_lhs) |  |
| [`get_command()`](#get_command) | Returns the command which should be used in the container definition for the serialized version of this task. |
| [`get_config()`](#get_config) | Returns the task config as a serializable dictionary. |
| [`get_container()`](#get_container) | Returns the container definition (if any) that is used to run the task on hosted Flyte. |
| [`get_custom()`](#get_custom) | Return additional plugin-specific custom data (if any) as a serializable dictionary. |
| [`get_default_command()`](#get_default_command) | Returns the default pyflyte-execute command used to run this on hosted Flyte platforms. |
| [`get_extended_resources()`](#get_extended_resources) | Returns the extended resources to allocate to the task on hosted Flyte. |
| [`get_image()`](#get_image) | Update image spec based on fast registration usage, and return string representing the image. |
| [`get_input_types()`](#get_input_types) | Returns the names and python types as a dictionary for the inputs of this task. |
| [`get_k8s_pod()`](#get_k8s_pod) | Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte. |
| [`get_sql()`](#get_sql) | Returns the Sql definition (if any) that is used to run the task on hosted Flyte. |
| [`get_type_for_input_var()`](#get_type_for_input_var) | Returns the python type for an input variable by name. |
| [`get_type_for_output_var()`](#get_type_for_output_var) | Returns the python type for the specified output variable by name. |
| [`local_execute()`](#local_execute) | This function is used only in the local execution path and is responsible for calling dispatch execute. |
| [`local_execution_mode()`](#local_execution_mode) |  |
| [`post_execute()`](#post_execute) | Post execute is called after the execution has completed, with the user_params and can be used to clean-up,. |
| [`pre_execute()`](#pre_execute) | This is the method that will be invoked directly before executing the task method and before all the inputs. |
| [`reset_command_fn()`](#reset_command_fn) | Resets the command which should be used in the container definition of this task to the default arguments. |
| [`sandbox_execute()`](#sandbox_execute) | Call dispatch_execute, in the context of a local sandbox execution. |
| [`set_command_fn()`](#set_command_fn) | By default, the task will run on the Flyte platform using the pyflyte-execute command. |
| [`set_resolver()`](#set_resolver) | By default, flytekit uses the DefaultTaskResolver to resolve the task. |

#### compile()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### construct_node_metadata()

```python
def construct_node_metadata()
```
Used when constructing the node that encapsulates this task as part of a broader workflow definition.

#### dispatch_execute()

```python
def dispatch_execute(
    ctx: FlyteContext,
    input_literal_map: LiteralMap,
) -> LiteralMap
```
This task should only be called during remote execution. Because when rehydrating this task at execution
time, we don't have access to the python interface of the corresponding eager task/workflow, we don't
have the Python types to convert the input literal map, but nor do we need them.
This task is responsible only for ensuring that all executions are terminated.

| Parameter | Type | Description |
|-|-|-|
| `ctx` | `FlyteContext` | |
| `input_literal_map` | `LiteralMap` | |

#### execute()

```python
def execute(
    kwargs,
) -> Any
```
This method will be invoked to execute the task.

| Parameter | Type | Description |
|-|-|-|
| `kwargs` | `**kwargs` | |

#### find_lhs()

```python
def find_lhs()
```
#### get_command()

```python
def get_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the command which should be used in the container definition for the serialized version of this task
registered on a hosted Flyte platform.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_config()

```python
def get_config(
    settings: SerializationSettings,
) -> Optional[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 | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_container()

```python
def get_container(
    settings: SerializationSettings,
) -> _task_model.Container
```
Returns the container definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_custom()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_default_command()

```python
def get_default_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_extended_resources()

```python
def get_extended_resources(
    settings: SerializationSettings,
) -> Optional[tasks_pb2.ExtendedResources]
```
Returns the extended resources to allocate to the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_image()

```python
def get_image(
    settings: SerializationSettings,
) -> str
```
Update image spec based on fast registration usage, and return string representing the image

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_input_types()

```python
def get_input_types()
```
Returns the names and python types as a dictionary for the inputs of this task.

#### get_k8s_pod()

```python
def get_k8s_pod(
    settings: SerializationSettings,
) -> _task_model.K8sPod
```
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_sql()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_type_for_input_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### get_type_for_output_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### local_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `kwargs` | `**kwargs` | |

#### local_execution_mode()

```python
def local_execution_mode()
```
#### post_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | are the modified user params as created during the pre_execute step |
| `rval` | `typing.Any` | |

#### pre_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | |

#### reset_command_fn()

```python
def reset_command_fn()
```
Resets the command which should be used in the container definition of this task to the default arguments.
This is useful when the command line is overridden at serialization time.

#### sandbox_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### set_command_fn()

```python
def set_command_fn(
    get_command_fn: Optional[Callable[[SerializationSettings], List[str]]],
)
```
By default, the task will run on the Flyte platform using the pyflyte-execute command.
However, it can be useful to update the command with which the task is serialized for specific cases like
running map tasks ("pyflyte-map-execute") or for fast-executed tasks.

| Parameter | Type | Description |
|-|-|-|
| `get_command_fn` | `Optional[Callable[[SerializationSettings], List[str]]]` | |

#### set_resolver()

```python
def set_resolver(
    resolver: TaskResolverMixin,
)
```
By default, flytekit uses the DefaultTaskResolver to resolve the task. This method allows the user to set a custom
task resolver. It can be useful to override the task resolver for specific cases like running tasks in the jupyter notebook.

| Parameter | Type | Description |
|-|-|-|
| `resolver` | `TaskResolverMixin` | |

## flytekit.core.python_function_task.EagerFailureTaskResolver

### Properties

| Property | Type | Description |
|-|-|-|
| `location` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`get_all_tasks()`](#get_all_tasks) | Future proof method. |
| [`load_task()`](#load_task) | Given the set of identifier keys, should return one Python Task or raise an error if not found. |
| [`loader_args()`](#loader_args) | Return a list of strings that can help identify the parameter Task. |
| [`name()`](#name) |  |
| [`task_name()`](#task_name) | Overridable function that can optionally return a custom name for a given task. |

#### get_all_tasks()

```python
def get_all_tasks()
```
Future proof method. Just making it easy to access all tasks (Not required today as we auto register them)

#### load_task()

```python
def load_task(
    loader_args: List[str],
) -> Task
```
Given the set of identifier keys, should return one Python Task or raise an error if not found

| Parameter | Type | Description |
|-|-|-|
| `loader_args` | `List[str]` | |

#### loader_args()

```python
def loader_args(
    settings: SerializationSettings,
    t: Task,
) -> List[str]
```
Return a list of strings that can help identify the parameter Task

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |
| `t` | `Task` | |

#### name()

```python
def name()
```
#### task_name()

```python
def task_name(
    t: flytekit.core.base_task.Task,
) -> typing.Optional[str]
```
Overridable function that can optionally return a custom name for a given task

| Parameter | Type | Description |
|-|-|-|
| `t` | `flytekit.core.base_task.Task` | |

## flytekit.core.python_function_task.PythonFunctionTask

A Python Function task should be used as the base for all extensions that have a python function. It will
automatically detect interface of the python function and when serialized on the hosted Flyte platform handles the
writing execution command to execute the function

It is advised this task is used using the @task decorator as follows

```python
@task
def my_func(a: int) -> str:
    ...
```
In the above code, the name of the function, the module, and the interface (inputs = int and outputs = str) will be
auto detected.

### Parameters

```python
class PythonFunctionTask(
    task_config: T,
    task_function: Callable,
    task_type,
    ignore_input_vars: Optional[List[str]],
    execution_mode: ExecutionBehavior,
    task_resolver: Optional[TaskResolverMixin],
    node_dependency_hints: Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]],
    pickle_untyped: bool,
    kwargs,
)
```
| Parameter | Type | Description |
|-|-|-|
| `task_config` | `T` | |
| `task_function` | `Callable` | |
| `task_type` |  | |
| `ignore_input_vars` | `Optional[List[str]]` | |
| `execution_mode` | `ExecutionBehavior` | |
| `task_resolver` | `Optional[TaskResolverMixin]` | |
| `node_dependency_hints` | `Optional[Iterable[Union['PythonFunctionTask', '_annotated_launch_plan.LaunchPlan', WorkflowBase]]]` | |
| `pickle_untyped` | `bool` | |
| `kwargs` | `**kwargs` | |

### Properties

| Property | Type | Description |
|-|-|-|
| `container_image` | `None` |  |
| `deck_fields` | `None` | If not empty, this task will output deck html file for the specified decks |
| `disable_deck` | `None` | If true, this task will not output deck html file |
| `docs` | `None` |  |
| `enable_deck` | `None` | If true, this task will output deck html file |
| `environment` | `None` | Any environment variables that supplied during the execution of the task. |
| `execution_mode` | `None` |  |
| `instantiated_in` | `None` |  |
| `interface` | `None` |  |
| `lhs` | `None` |  |
| `location` | `None` |  |
| `metadata` | `None` |  |
| `name` | `None` | Returns the name of the task. |
| `node_dependency_hints` | `None` |  |
| `python_interface` | `None` | Returns this task's python interface. |
| `resources` | `None` |  |
| `security_context` | `None` |  |
| `task_config` | `None` | Returns the user-specified task config which is used for plugin-specific handling of the task. |
| `task_function` | `None` |  |
| `task_resolver` | `None` |  |
| `task_type` | `None` |  |
| `task_type_version` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`compile()`](#compile) | Generates a node that encapsulates this task in a workflow definition. |
| [`compile_into_workflow()`](#compile_into_workflow) | In the case of dynamic workflows, this function will produce a workflow definition at execution time which will. |
| [`construct_node_metadata()`](#construct_node_metadata) | Used when constructing the node that encapsulates this task as part of a broader workflow definition. |
| [`dispatch_execute()`](#dispatch_execute) | This method translates Flyte's Type system based input values and invokes the actual call to the executor. |
| [`dynamic_execute()`](#dynamic_execute) | By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte. |
| [`execute()`](#execute) | This method will be invoked to execute the task. |
| [`find_lhs()`](#find_lhs) |  |
| [`get_command()`](#get_command) | Returns the command which should be used in the container definition for the serialized version of this task. |
| [`get_config()`](#get_config) | Returns the task config as a serializable dictionary. |
| [`get_container()`](#get_container) | Returns the container definition (if any) that is used to run the task on hosted Flyte. |
| [`get_custom()`](#get_custom) | Return additional plugin-specific custom data (if any) as a serializable dictionary. |
| [`get_default_command()`](#get_default_command) | Returns the default pyflyte-execute command used to run this on hosted Flyte platforms. |
| [`get_extended_resources()`](#get_extended_resources) | Returns the extended resources to allocate to the task on hosted Flyte. |
| [`get_image()`](#get_image) | Update image spec based on fast registration usage, and return string representing the image. |
| [`get_input_types()`](#get_input_types) | Returns the names and python types as a dictionary for the inputs of this task. |
| [`get_k8s_pod()`](#get_k8s_pod) | Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte. |
| [`get_sql()`](#get_sql) | Returns the Sql definition (if any) that is used to run the task on hosted Flyte. |
| [`get_type_for_input_var()`](#get_type_for_input_var) | Returns the python type for an input variable by name. |
| [`get_type_for_output_var()`](#get_type_for_output_var) | Returns the python type for the specified output variable by name. |
| [`local_execute()`](#local_execute) | This function is used only in the local execution path and is responsible for calling dispatch execute. |
| [`local_execution_mode()`](#local_execution_mode) |  |
| [`post_execute()`](#post_execute) | Post execute is called after the execution has completed, with the user_params and can be used to clean-up,. |
| [`pre_execute()`](#pre_execute) | This is the method that will be invoked directly before executing the task method and before all the inputs. |
| [`reset_command_fn()`](#reset_command_fn) | Resets the command which should be used in the container definition of this task to the default arguments. |
| [`sandbox_execute()`](#sandbox_execute) | Call dispatch_execute, in the context of a local sandbox execution. |
| [`set_command_fn()`](#set_command_fn) | By default, the task will run on the Flyte platform using the pyflyte-execute command. |
| [`set_resolver()`](#set_resolver) | By default, flytekit uses the DefaultTaskResolver to resolve the task. |

#### compile()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### compile_into_workflow()

```python
def compile_into_workflow(
    ctx: FlyteContext,
    task_function: Callable,
    kwargs,
) -> Union[_dynamic_job.DynamicJobSpec, _literal_models.LiteralMap]
```
In the case of dynamic workflows, this function will produce a workflow definition at execution time which will
then proceed to be executed.

| Parameter | Type | Description |
|-|-|-|
| `ctx` | `FlyteContext` | |
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### construct_node_metadata()

```python
def construct_node_metadata()
```
Used when constructing the node that encapsulates this task as part of a broader workflow definition.

#### dispatch_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### dynamic_execute()

```python
def dynamic_execute(
    task_function: Callable,
    kwargs,
) -> Any
```
By the time this function is invoked, the local_execute function should have unwrapped the Promises and Flyte
literal wrappers so that the kwargs we are working with here are now Python native literal values. This
function is also expected to return Python native literal values.

Since the user code within a dynamic task constitute a workflow, we have to first compile the workflow, and
then execute that workflow.

When running for real in production, the task would stop after the compilation step, and then create a file
representing that newly generated workflow, instead of executing it.

| Parameter | Type | Description |
|-|-|-|
| `task_function` | `Callable` | |
| `kwargs` | `**kwargs` | |

#### execute()

```python
def execute(
    kwargs,
) -> Any
```
This method will be invoked to execute the task. If you do decide to override this method you must also
handle dynamic tasks or you will no longer be able to use the task as a dynamic task generator.

| Parameter | Type | Description |
|-|-|-|
| `kwargs` | `**kwargs` | |

#### find_lhs()

```python
def find_lhs()
```
#### get_command()

```python
def get_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the command which should be used in the container definition for the serialized version of this task
registered on a hosted Flyte platform.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_config()

```python
def get_config(
    settings: SerializationSettings,
) -> Optional[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 | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_container()

```python
def get_container(
    settings: SerializationSettings,
) -> _task_model.Container
```
Returns the container definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_custom()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_default_command()

```python
def get_default_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_extended_resources()

```python
def get_extended_resources(
    settings: SerializationSettings,
) -> Optional[tasks_pb2.ExtendedResources]
```
Returns the extended resources to allocate to the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_image()

```python
def get_image(
    settings: SerializationSettings,
) -> str
```
Update image spec based on fast registration usage, and return string representing the image

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_input_types()

```python
def get_input_types()
```
Returns the names and python types as a dictionary for the inputs of this task.

#### get_k8s_pod()

```python
def get_k8s_pod(
    settings: SerializationSettings,
) -> _task_model.K8sPod
```
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_sql()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_type_for_input_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### get_type_for_output_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### local_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `kwargs` | `**kwargs` | |

#### local_execution_mode()

```python
def local_execution_mode()
```
#### post_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | are the modified user params as created during the pre_execute step |
| `rval` | `typing.Any` | |

#### pre_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | |

#### reset_command_fn()

```python
def reset_command_fn()
```
Resets the command which should be used in the container definition of this task to the default arguments.
This is useful when the command line is overridden at serialization time.

#### sandbox_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### set_command_fn()

```python
def set_command_fn(
    get_command_fn: Optional[Callable[[SerializationSettings], List[str]]],
)
```
By default, the task will run on the Flyte platform using the pyflyte-execute command.
However, it can be useful to update the command with which the task is serialized for specific cases like
running map tasks ("pyflyte-map-execute") or for fast-executed tasks.

| Parameter | Type | Description |
|-|-|-|
| `get_command_fn` | `Optional[Callable[[SerializationSettings], List[str]]]` | |

#### set_resolver()

```python
def set_resolver(
    resolver: TaskResolverMixin,
)
```
By default, flytekit uses the DefaultTaskResolver to resolve the task. This method allows the user to set a custom
task resolver. It can be useful to override the task resolver for specific cases like running tasks in the jupyter notebook.

| Parameter | Type | Description |
|-|-|-|
| `resolver` | `TaskResolverMixin` | |

## flytekit.core.python_function_task.PythonInstanceTask

This class should be used as the base class for all Tasks that do not have a user defined function body, but have
a platform defined execute method. (Execute needs to be overridden). This base class ensures that the module loader
will invoke the right class automatically, by capturing the module name and variable in the module name.

```python
x = MyInstanceTask(name="x", .....)

# this can be invoked as
x(a=5) # depending on the interface of the defined task
```

### Parameters

```python
class PythonInstanceTask(
    name: str,
    task_config: T,
    task_type: str,
    task_resolver: Optional[TaskResolverMixin],
    kwargs,
)
```
Please see class level documentation.

| Parameter | Type | Description |
|-|-|-|
| `name` | `str` | |
| `task_config` | `T` | |
| `task_type` | `str` | |
| `task_resolver` | `Optional[TaskResolverMixin]` | |
| `kwargs` | `**kwargs` | |

### Properties

| Property | Type | Description |
|-|-|-|
| `container_image` | `None` |  |
| `deck_fields` | `None` | If not empty, this task will output deck html file for the specified decks |
| `disable_deck` | `None` | If true, this task will not output deck html file |
| `docs` | `None` |  |
| `enable_deck` | `None` | If true, this task will output deck html file |
| `environment` | `None` | Any environment variables that supplied during the execution of the task. |
| `instantiated_in` | `None` |  |
| `interface` | `None` |  |
| `lhs` | `None` |  |
| `location` | `None` |  |
| `metadata` | `None` |  |
| `name` | `None` |  |
| `python_interface` | `None` | Returns this task's python interface. |
| `resources` | `None` |  |
| `security_context` | `None` |  |
| `task_config` | `None` | Returns the user-specified task config which is used for plugin-specific handling of the task. |
| `task_resolver` | `None` |  |
| `task_type` | `None` |  |
| `task_type_version` | `None` |  |

### Methods

| Method | Description |
|-|-|
| [`compile()`](#compile) | Generates a node that encapsulates this task in a workflow definition. |
| [`construct_node_metadata()`](#construct_node_metadata) | Used when constructing the node that encapsulates this task as part of a broader workflow definition. |
| [`dispatch_execute()`](#dispatch_execute) | This method translates Flyte's Type system based input values and invokes the actual call to the executor. |
| [`execute()`](#execute) | This method will be invoked to execute the task. |
| [`find_lhs()`](#find_lhs) |  |
| [`get_command()`](#get_command) | Returns the command which should be used in the container definition for the serialized version of this task. |
| [`get_config()`](#get_config) | Returns the task config as a serializable dictionary. |
| [`get_container()`](#get_container) | Returns the container definition (if any) that is used to run the task on hosted Flyte. |
| [`get_custom()`](#get_custom) | Return additional plugin-specific custom data (if any) as a serializable dictionary. |
| [`get_default_command()`](#get_default_command) | Returns the default pyflyte-execute command used to run this on hosted Flyte platforms. |
| [`get_extended_resources()`](#get_extended_resources) | Returns the extended resources to allocate to the task on hosted Flyte. |
| [`get_image()`](#get_image) | Update image spec based on fast registration usage, and return string representing the image. |
| [`get_input_types()`](#get_input_types) | Returns the names and python types as a dictionary for the inputs of this task. |
| [`get_k8s_pod()`](#get_k8s_pod) | Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte. |
| [`get_sql()`](#get_sql) | Returns the Sql definition (if any) that is used to run the task on hosted Flyte. |
| [`get_type_for_input_var()`](#get_type_for_input_var) | Returns the python type for an input variable by name. |
| [`get_type_for_output_var()`](#get_type_for_output_var) | Returns the python type for the specified output variable by name. |
| [`local_execute()`](#local_execute) | This function is used only in the local execution path and is responsible for calling dispatch execute. |
| [`local_execution_mode()`](#local_execution_mode) |  |
| [`post_execute()`](#post_execute) | Post execute is called after the execution has completed, with the user_params and can be used to clean-up,. |
| [`pre_execute()`](#pre_execute) | This is the method that will be invoked directly before executing the task method and before all the inputs. |
| [`reset_command_fn()`](#reset_command_fn) | Resets the command which should be used in the container definition of this task to the default arguments. |
| [`sandbox_execute()`](#sandbox_execute) | Call dispatch_execute, in the context of a local sandbox execution. |
| [`set_command_fn()`](#set_command_fn) | By default, the task will run on the Flyte platform using the pyflyte-execute command. |
| [`set_resolver()`](#set_resolver) | By default, flytekit uses the DefaultTaskResolver to resolve the task. |

#### compile()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `args` | `*args` | |
| `kwargs` | `**kwargs` | |

#### construct_node_metadata()

```python
def construct_node_metadata()
```
Used when constructing the node that encapsulates this task as part of a broader workflow definition.

#### dispatch_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### execute()

```python
def execute(
    kwargs,
) -> typing.Any
```
This method will be invoked to execute the task.

| Parameter | Type | Description |
|-|-|-|
| `kwargs` | `**kwargs` | |

#### find_lhs()

```python
def find_lhs()
```
#### get_command()

```python
def get_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the command which should be used in the container definition for the serialized version of this task
registered on a hosted Flyte platform.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_config()

```python
def get_config(
    settings: SerializationSettings,
) -> Optional[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 | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_container()

```python
def get_container(
    settings: SerializationSettings,
) -> _task_model.Container
```
Returns the container definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_custom()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_default_command()

```python
def get_default_command(
    settings: SerializationSettings,
) -> List[str]
```
Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_extended_resources()

```python
def get_extended_resources(
    settings: SerializationSettings,
) -> Optional[tasks_pb2.ExtendedResources]
```
Returns the extended resources to allocate to the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_image()

```python
def get_image(
    settings: SerializationSettings,
) -> str
```
Update image spec based on fast registration usage, and return string representing the image

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_input_types()

```python
def get_input_types()
```
Returns the names and python types as a dictionary for the inputs of this task.

#### get_k8s_pod()

```python
def get_k8s_pod(
    settings: SerializationSettings,
) -> _task_model.K8sPod
```
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

| Parameter | Type | Description |
|-|-|-|
| `settings` | `SerializationSettings` | |

#### get_sql()

```python
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 | Description |
|-|-|-|
| `settings` | `flytekit.configuration.SerializationSettings` | |

#### get_type_for_input_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### get_type_for_output_var()

```python
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 | Description |
|-|-|-|
| `k` | `str` | |
| `v` | `typing.Any` | |

#### local_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `kwargs` | `**kwargs` | |

#### local_execution_mode()

```python
def local_execution_mode()
```
#### post_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | are the modified user params as created during the pre_execute step |
| `rval` | `typing.Any` | |

#### pre_execute()

```python
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 | Description |
|-|-|-|
| `user_params` | `typing.Optional[flytekit.core.context_manager.ExecutionParameters]` | |

#### reset_command_fn()

```python
def reset_command_fn()
```
Resets the command which should be used in the container definition of this task to the default arguments.
This is useful when the command line is overridden at serialization time.

#### sandbox_execute()

```python
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 | Description |
|-|-|-|
| `ctx` | `flytekit.core.context_manager.FlyteContext` | |
| `input_literal_map` | `flytekit.models.literals.LiteralMap` | |

#### set_command_fn()

```python
def set_command_fn(
    get_command_fn: Optional[Callable[[SerializationSettings], List[str]]],
)
```
By default, the task will run on the Flyte platform using the pyflyte-execute command.
However, it can be useful to update the command with which the task is serialized for specific cases like
running map tasks ("pyflyte-map-execute") or for fast-executed tasks.

| Parameter | Type | Description |
|-|-|-|
| `get_command_fn` | `Optional[Callable[[SerializationSettings], List[str]]]` | |

#### set_resolver()

```python
def set_resolver(
    resolver: TaskResolverMixin,
)
```
By default, flytekit uses the DefaultTaskResolver to resolve the task. This method allows the user to set a custom
task resolver. It can be useful to override the task resolver for specific cases like running tasks in the jupyter notebook.

| Parameter | Type | Description |
|-|-|-|
| `resolver` | `TaskResolverMixin` | |

---
**Source**: https://github.com/unionai/unionai-docs/blob/main/content/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task.md
**HTML**: https://www.union.ai/docs/v1/union/api-reference/flytekit-sdk/packages/flytekit.core.python_function_task/