Reader

class lightautoml.reader.base.Reader(task, *args, **kwargs)

Bases: object

Abstract Reader class.

Abstract class for analyzing input data and creating inner LAMLDataset from raw data. Takes data in different formats as input, drop obviously useless features, estimates avaliable size and returns dataset.

Parameters:

• task (Task) – Task object

• *args (Any) – Not used.

• *kwargs (Any) – Not used.

property roles

Roles dict.

property dropped_features

List of dropped features.

property used_features

List of used features.

property used_array_attrs

Dict of used array attributes.

fit_read(train_data, features_names=None, roles=None, **kwargs)

Abstract function to get dataset with initial feature selection.

read(data, features_names, **kwargs)

Abstract function to add validation columns.

upd_used_features(add=None, remove=None)

Updates the list of used features.

Parameters:

• add (Optional[Sequence[str]]) – List of feature names to add or None.

• remove (Optional[Sequence[str]]) – List of feature names to remove or None.

classmethod from_reader(reader, **kwargs)

Create reader for new data type from existed.

Note - for now only Pandas reader exists, made for future plans.

Parameters:

• reader (Reader) – Source reader.

• **kwargs – Ignored as in the class itself.

Return type:

Reader

Returns:

New reader.

cols_by_type(col_type)

Get roles names by it’s type.

Parameters:

col_type (str) – Column type, for example ‘Text’.

Return type:

List[str]

Returns:

Array with column names.