NativeInterface

A class representing the native interface for a task. This is used to interact with the task and its execution context.

Attributes

Attribute	Type	Description
inputs	Dict[str, Tuple[Type, Any]]	A dictionary where keys are input names and values are tuples containing the input's type and its default value or an indicator if it has a default.
outputs	Dict[str, Type]	A dictionary where keys are output names and values are their corresponding types.
docstring	Optional[Docstring] = None	The parsed docstring of the task, providing documentation for the task's purpose and parameters.
has_default	ClassVar[Type[_has_default]]	This can be used to indicate if a specific input has a default value or not, in the case when the default value is not known.

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Methods

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has_outputs()

@classmethod
def has_outputs() - > bool

Check if the task has outputs. This is used to determine if the task has outputs or not.

Returns

Type	Description
bool	True if the task has outputs, False otherwise.

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required_inputs()

@classmethod
def required_inputs() - > List[str]

Get the names of the required inputs for the task. This is used to determine which inputs are required for the task execution.

Returns

Type	Description
List[str]	A list of required input names.

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num_required_inputs()

@classmethod
def num_required_inputs() - > int

Get the number of required inputs for the task. This is used to determine how many inputs are required for the task execution.

Returns

Type	Description
int	The count of required inputs for the task.

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from_types()

@classmethod
def from_types(
    inputs: Dict[str, Tuple[Type, Type[_has_default]| Type[inspect._empty]]],
    outputs: Dict[str, Type],
    default_inputs: Optional[Dict[str, literals_pb2.Literal]] = None
) - > [NativeInterface](nativeinterface.md?sid=flyte_models_nativeinterface)

Create a new NativeInterface from the given types. This is used to create a native interface for the task.

Parameters

Name	Type	Description
inputs	`Dict[str, Tuple[Type, Type[_has_default]	Type[inspect._empty]]]`
outputs	Dict[str, Type]	A dictionary of output names and their types.
default_inputs	Optional[Dict[str, literals_pb2.Literal]] = None	Optional dictionary of default inputs for remote tasks.

Returns

Type	Description
[NativeInterface](nativeinterface.md?sid=flyte_models_nativeinterface)	A NativeInterface object with the given inputs and outputs.

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from_callable()

@classmethod
def from_callable(
    func: Callable
) - > [NativeInterface](nativeinterface.md?sid=flyte_models_nativeinterface)

Extract the native interface from the given function. This is used to create a native interface for the task.

Parameters

Name	Type	Description
func	Callable	The callable (function) from which to extract the native interface.

Returns

Type	Description
[NativeInterface](nativeinterface.md?sid=flyte_models_nativeinterface)	A NativeInterface object representing the interface of the provided callable.

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convert_to_kwargs()

@classmethod
def convert_to_kwargs(
    args: *args,
    kwargs: **kwargs
) - > Dict[str, Any]

Convert the given arguments to keyword arguments based on the native interface. This is used to convert the arguments to the correct types for the task execution.

Parameters

Name	Type	Description
args	*args	Positional arguments to convert.
kwargs	**kwargs	Keyword arguments to convert.

Returns

Type	Description
Dict[str, Any]	A dictionary of keyword arguments derived from the provided positional and keyword arguments.

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get_input_types()

@classmethod
def get_input_types() - > Dict[str, Type]

Get the input types for the task. This is used to get the types of the inputs for the task execution.

Returns

Type	Description
Dict[str, Type]	A dictionary mapping input names to their Python types.

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json_schema()

@classmethod
def json_schema() - > Dict[str, Any]

Convert task inputs to a JSON schema dict. Uses the Flyte type engine to produce a LiteralType for each input, then converts to JSON schema.

Returns

Type	Description
Dict[str, Any]	A dictionary representing the JSON schema for the task's inputs.

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