instancelib.instances.hdf5pandas module

class instancelib.instances.hdf5pandas.HDF5TextInstance(identifier, data, vector, representation=None, tokenized=None, map_to_original=None, split_marker=None, external=None)

Bases: DataPoint[Union[int, str], str, ndarray, str], TextInstance[Union[int, str], ndarray]

Parameters:

• identifier (Union[int, str]) –

• data (str) –

• vector (Optional[ndarray[Any, dtype[Any]]]) –

• representation (Optional[str]) –

• tokenized (Optional[Sequence[str]]) –

• map_to_original (Optional[ndarray[Any, dtype[Any]]]) –

• split_marker (Optional[Any]) –

• external (Optional[ExternalProvider[Any, Union[int, str], str, ndarray[Any, dtype[Any]], str]]) –

property map_to_original: ndarray[Any, dtype[Any]] | None

property split_marker: Any | None

property tokenized: Sequence[str] | None

class instancelib.instances.hdf5pandas.HDF5TextProvider(data_storage, vector_storage_location, hdf5_dataset, id_col, data_cols)

Bases: HDF5VectorInstanceProvider[HDF5TextInstance, Union[int, str], str, str], ExternalProvider[HDF5TextInstance, Union[int, str], str, ndarray, str]

Parameters:

• data_storage (PathLike[str]) –

• vector_storage_location (PathLike[str]) –

• hdf5_dataset (str) –

• id_col (str) –

• data_cols (Sequence[str]) –

build_from_external(k)

Parameters:

k (Union[int, str]) –

Return type:

HDF5TextInstance

clear()

Return type:

None

property dataframe: DataFrame

property empty: bool

Determines if the provider does not contain instances

Returns:

True if the provider is empty

Return type:

bool

get_all()

Get an iterator that iterates over all instances

Yields:

InstanceType – An iterator that iterates over all instances

update_external(ins)

Parameters:

ins (Instance[Union[int, str], str, ndarray[Any, dtype[Any]], str]) –

Return type:

None

vector_storage_location: PathLike[str]

vectorstorage: Optional[VectorStorage[KT, VT, MT]]