# License: BSD 3-Clause

from __future__ import annotations

from typing import TYPE_CHECKING, Any, ClassVar, Sequence

if TYPE_CHECKING:

from IPython.lib import pretty

class OpenMLDataFeature:

"""

Data Feature (a.k.a. Attribute) object.

Parameters

----------

index : int

The index of this feature

name : str

Name of the feature

data_type : str

can be nominal, numeric, string, date (corresponds to arff)

nominal_values : list(str)

list of the possible values, in case of nominal attribute

number_missing_values : int

Number of rows that have a missing value for this feature.

ontologies : list(str)

list of ontologies attached to this feature. An ontology describes the

concept that are described in a feature. An ontology is defined by an

URL where the information is provided.

"""

LEGAL_DATA_TYPES: ClassVar[Sequence[str]] = ["nominal", "numeric", "string", "date"]

def __init__( # noqa: PLR0913

self,

index: int,

name: str,

data_type: str,

nominal_values: list[str],

number_missing_values: int,

ontologies: list[str] | None = None,

):

if not isinstance(index, int):

raise TypeError(f"Index must be `int` but is {type(index)}")

if data_type not in self.LEGAL_DATA_TYPES:

raise ValueError(

f"data type should be in {self.LEGAL_DATA_TYPES!s}, found: {data_type}",

)

if data_type == "nominal":

if nominal_values is None:

raise TypeError(

"Dataset features require attribute `nominal_values` for nominal "

"feature type.",

)

if not isinstance(nominal_values, list):

raise TypeError(

"Argument `nominal_values` is of wrong datatype, should be list, "

f"but is {type(nominal_values)}",

)

elif nominal_values is not None:

raise TypeError("Argument `nominal_values` must be None for non-nominal feature.")

if not isinstance(number_missing_values, int):

msg = f"number_missing_values must be int but is {type(number_missing_values)}"

raise TypeError(msg)

self.index = index

self.name = str(name)

self.data_type = str(data_type)

self.nominal_values = nominal_values

self.number_missing_values = number_missing_values

self.ontologies = ontologies

def __repr__(self) -> str:

return "[%d - %s (%s)]" % (self.index, self.name, self.data_type)

def __eq__(self, other: Any) -> bool:

return isinstance(other, OpenMLDataFeature) and self.__dict__ == other.__dict__

def _repr_pretty_(self, pp: pretty.PrettyPrinter, cycle: bool) -> None: # noqa: FBT001, ARG002

pp.text(str(self))