flytekit.types.structured.StructuredDataset#

class flytekit.types.structured.StructuredDataset(dataframe=None, uri=None, metadata=None, **kwargs)[source]#

This is the user facing StructuredDataset class. Please don’t confuse it with the literals.StructuredDataset class (that is just a model, a Python class representation of the protobuf).

Methods

Parameters

dataframe (Optional[Any]) –
uri (Optional[str]) –
metadata (Optional[literals.StructuredDatasetMetadata]) –

all()[source]#

Return type: flytekit.types.structured.structured_dataset.DF

classmethod column_names()[source]#

Return type: List[str]

classmethod columns()[source]#

Return type: Dict[str, Type]

classmethod from_dict(d, *, dialect=None)#

classmethod from_json(data, decoder=<function loads>, **from_dict_kwargs)#

Parameters

data (Union[str, bytes, bytearray]) –
decoder (Callable[[Union[str, bytes, bytearray]], Dict[Any, Any]]) –
from_dict_kwargs (Any) –

Return type

mashumaro.mixins.json.T

iter()[source]#

Return type: Generator[flytekit.types.structured.structured_dataset.DF, None, None]

open(dataframe_type)[source]#

Parameters: dataframe_type (Type[flytekit.types.structured.structured_dataset.DF]) –

to_dict()#

to_json(encoder=<function dumps>, **to_dict_kwargs)#

Parameters

self (mashumaro.mixins.json.T) –
encoder (Callable[[Any], Union[str, bytes, bytearray]]) –
to_dict_kwargs (Any) –

Return type

Union[str, bytes, bytearray]

Attributes

dataframe

file_format: Optional[str] = ''

literal

metadata

uri: Optional[str] = None