def test_setEmotions(self): emotions = ['Love', 'Sad', 'Hesitant', 'Calm', 'Happy'] model1 = MoodNeuralNetwork() emotions2 = model1.getEmotions() self.assertNotEqual(emotions, emotions2) self.assertTrue(model1.setEmotions(emotions)) self.assertEqual(emotions, model1.getEmotions())
def test_getEmotions(self): emotions = getEmotions() model1 = MoodNeuralNetwork() emotions2 = model1.getEmotions() self.assertEqual(emotions, emotions2) self.assertTrue(model1.getEmotions())
import json from mood_model.mood_neural_network import MoodNeuralNetwork baseModel = MoodNeuralNetwork() emotions = baseModel.getEmotions() emotion_map = {} for i in range(len(emotions)): emotion_map[emotions[i]] = i with open('notifications.txt', 'r') as file: # Use file to refer to the file object data = file.read().splitlines() print(data) reminders = {} curr = "" for i in range(len(data)): if data[i] in emotion_map: reminders[data[i]] = [] curr = data[i] else: reminders[curr].append(data[i]) print(reminders) print(reminders['Sad']) with open('notifications.json', 'w') as fp: json.dump(reminders, fp)