def test_pickle_unpickle_positive01(self):
X = OrderedDict({
'Первый сайт': ['Ваш банк полный ацтой!', 'Ваш магаз — нормас'],
'Второй сайт': ['Мне пофиг на ваш ресторан']
})
sent = SentimentAnalyzer(feature_extractor=self.feature_extractor,
classifier=self.classifier)
output1 = sent.analyze(X)
with open('sent.pkl', 'wb') as f:
pickle.dump(sent, f)
del sent
with open('sent.pkl', 'rb') as f:
sent = pickle.load(f)
output2 = sent.analyze(X)
self.assertEqual(output1, output2)
del sent
def test_analyze_positive01(self):
X = OrderedDict([('Первый сайт',
['Ваш банк полный ацтой!', 'Ваш магаз — нормас']),
('Второй сайт', ['Мне пофиг на ваш ресторан'])])
len_X = sum([len(X[key]) for key in X])
sent = SentimentAnalyzer(feature_extractor=self.feature_extractor,
classifier=self.classifier)
output = sent.analyze(X)
self.assertIsInstance(output, tuple)
self.assertEqual(len(output), 3)
self.assertIsInstance(output[0], int)
self.assertIsInstance(output[1], int)
self.assertIsInstance(output[2], int)
self.assertEqual(output[0] + output[1] + output[2], len_X)
del sent
def test_analyze_negative01(self):
with self.assertRaises(TypeError):
sent = SentimentAnalyzer(feature_extractor=self.feature_extractor,
classifier=self.classifier)
sent.analyze(1)
