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

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

	# --------------
	# Create model
	# --------------
	sfilename = os.getcwd()+'/'+'model.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