flytekit.PythonInstanceTask#

class flytekit.PythonInstanceTask(*args, **kwargs)[source]#

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.

Please see class level documentation.

Methods

compile(ctx, *args, **kwargs)#

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

Parameters

ctx (flytekit.core.context_manager.FlyteContext) –

construct_node_metadata()#

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

Return type

flytekit.models.core.workflow.NodeMetadata

dispatch_execute(ctx, input_literal_map)#

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

Parameters
Return type

Union[flytekit.models.literals.LiteralMap, flytekit.models.dynamic_job.DynamicJobSpec]

abstract execute(**kwargs)#

This method will be invoked to execute the task.

Return type

Any

find_lhs()#
Return type

str

get_command(settings)#

Returns the command which should be used in the container definition for the serialized version of this task registered on a hosted Flyte platform.

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

List[str]

get_config(settings)#

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

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

Optional[Dict[str, str]]

get_container(settings)#

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

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

flytekit.models.task.Container

get_custom(settings)#

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

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

Optional[Dict[str, Any]]

get_default_command(settings)#

Returns the default pyflyte-execute command used to run this on hosted Flyte platforms.

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

List[str]

get_input_types()#

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

Return type

Optional[Dict[str, type]]

get_k8s_pod(settings)#

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

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

flytekit.models.task.K8sPod

get_sql(settings)#

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

Parameters

settings (flytekit.configuration.SerializationSettings) –

Return type

Optional[flytekit.models.task.Sql]

get_type_for_input_var(k, v)#

Returns the python type for an input variable by name.

Parameters
Return type

Optional[Type[Any]]

get_type_for_output_var(k, v)#

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

Parameters
Return type

Optional[Type[Any]]

local_execute(ctx, **kwargs)#

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).

Parameters

ctx (flytekit.core.context_manager.FlyteContext) –

Return type

Optional[Union[Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise]]

post_execute(user_params, rval)#

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

Parameters
Return type

Any

pre_execute(user_params)#

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

Parameters

user_params (flytekit.core.context_manager.ExecutionParameters) –

Return type

flytekit.core.context_manager.ExecutionParameters

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.

set_command_fn(get_command_fn=None)#

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.

Parameters

get_command_fn (Optional[Callable[[flytekit.configuration.SerializationSettings], List[str]]]) –

Attributes

container_image#
disable_deck#

If true, this task will not output deck html file

docs#
environment#

Any environment variables that supplied during the execution of the task.

instantiated_in#
interface#
lhs#
location#
metadata#
name#
python_interface#

Returns this task’s python interface.

resources#
security_context#
task_config#

Returns the user-specified task config which is used for plugin-specific handling of the task.

task_resolver#
task_type#
task_type_version#