from scipy.spatial import distance
def euc(a,b):

    return distance.euclidean(a, b)

 class ScrappyKNN():

    def fit(self, x_train, y_train):

    self.x_train = x_train

    self.y_train = y_train

predictions = []

    for row in x_test:

        label = self.closest(row)

        predictions.append(label)

    return predictions

best_dist = euc(row, self.x_train[0])

    best_index = 0

    for i in range(1, len(self.x_train)):

        dist = euc(row, self.x_train[i])

        if dist < best_dist:

            best_dist = dist

            best_index = i

    return self.y_train[best_index]