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 mapping of input names to tuples containing their Python type and default value, used to define the task's input signature.
outputs	Dict[str, Type]	A mapping of output names to their Python types, used to define the task's return signature.
docstring	Optional[Docstring] = null	An optional parsed docstring object containing documentation for the task and its 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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Constructor

Signature

def NativeInterface(
    inputs: Dict[str, Tuple[Type, Any]],
    outputs: Dict[str, Type],
    docstring: Optional[Docstring] = None,
    _remote_defaults: Optional[Dict[str, literals_pb2.Literal]] = None
) - > null

Parameters

Name	Type	Description
inputs	Dict[str, Tuple[Type, Any]]	A dictionary mapping input names to a tuple containing their Python type and default value.
outputs	Dict[str, Type]	A dictionary mapping output names to their respective Python types.
docstring	Optional[Docstring] = None	An optional Docstring object parsed from the task function.
_remote_defaults	Optional[Dict[str, literals_pb2.Literal]] = None	An optional dictionary of default values for remote tasks in protobuf literal format.

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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 defines one or more output parameters, 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 total count of input parameters that do not have a default value

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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 Python function or callable to inspect for parameters and return types

Returns

Type	Description
[NativeInterface](nativeinterface.md?sid=flyte_models_nativeinterface)	A new interface instance derived from the function signature, type hints, and docstrings

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convert_to_kwargs()

@classmethod
def convert_to_kwargs(
    *args: Any,
    **kwargs: Any
) - > 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	Any	Positional arguments to be mapped to the interface's input names
**kwargs	Any	Keyword arguments representing task inputs

Returns

Type	Description
Dict[str, Any]	A dictionary mapping input names to their corresponding values

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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 JSON schema object representing the required and optional inputs

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