from sklearn.preprocessing import MinMaxScaler, Normalizer, StandardScaler
from .sklearn import SKLearnTransformation
from typing import Literal

ScalerTypes = Literal["normalize", "minmax", "standardize"]


def get_scaler(type: ScalerTypes) -> SKLearnTransformation:
    if type == "normalize":
        return SKLearnTransformation(Normalizer())
    elif type == "minmax":
        return SKLearnTransformation(MinMaxScaler(feature_range=(-1, 1)))
    elif type == "standardize":
        return SKLearnTransformation(StandardScaler())
    else:
        raise Exception("Scaler type not supported")