import numpy as np
from sklearn.pipeline import Pipeline

from classifiers.manual import ManualClassifier
from cleaning.transformers import LowercaseTransformer


class ManualCleaningClassifier(ManualClassifier):
    def __init__(self):
        self.cleaning = Pipeline([
            ("lowercase", LowercaseTransformer()),
        ])

    def fit(self, X, y):
        self.cleaning.fit(X)
        return self

    def predict(self, X):
        X_clean = self.cleaning.transform(X)
        return np.array([self.predict_one(msg) for msg in X_clean])