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 (str | None)
metadata (Optional[literals.StructuredDatasetMetadata])

all()[source]#

Return type:: DF

classmethod column_names()[source]#

Return type:: List[str]

classmethod columns()[source]#

Return type:: Dict[str, Type]

deserialize_structured_dataset(info)[source]#

Return type:: StructuredDataset

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

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

Parameters:

data (str | bytes | bytearray)
decoder (Callable[[str | bytes | bytearray], dict[Any, Any]])
from_dict_kwargs (Any)

Return type:

T

iter()[source]#

Return type:: Generator[DF, None, None]

open(dataframe_type)[source]#

Parameters:: dataframe_type (Type[DF])

serialize_structured_dataset()[source]#

Return type:: Dict[str, str | None]

set_literal(ctx, expected)[source]#

A public wrapper method to set the StructuredDataset Literal.

This method provides external access to the internal _set_literal method.

Parameters:

ctx (FlyteContext)
expected (LiteralType)

Return type:

None

to_dict()#

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

Parameters:

self (T)
encoder (Callable[[Any], str | bytes | bytearray])
to_dict_kwargs (Any)

Return type:

str | bytes | bytearray

Attributes

dataframe

file_format: str | None = ''

literal

metadata

uri: str | None = None