import numpy as np
from sklearn.naive_bayes import GaussianNB
from sklearn import metrics
import pickle
import os 
def prediction_generator(list_):
    # This method need a np. array.
    # Therefore this method needs the imports:
    # import pandas as pd
    # import pickle
    # In the folder models.py
    # @return one it with the prediction

    print(list_)
    x = np.asarray(list_, dtype=np.float32)

    # --------------
    # Create model
    # --------------
    sfilename = os.getcwd()+'/'+'model_NaiveBayses-70.19acc.sav'
    # load the model from disk
    model = pickle.load(open(sfilename, 'rb'))

    x = x.reshape(1, -1)

    y_pred = model.predict(x)

    iY_pred = int(y_pred)

    return iY_pred