def setUp(self):
super(TestClassifierWorker, self).setUp()
self.cls = nltk.NaiveBayesClassifier.train([({'a': 'a', 'b': 'b'}, 'positive')])
self.data = []
for i in range(5):
d = RawStreamQueue()
d.source = 'test'
d.original = {}
d.text = "this is a test"
self.data.append(d)
ClassifiedStream.drop_collection()
def setUp(self):
super(TestClassifierWorker, self).setUp()
self.cls = nltk.NaiveBayesClassifier.train([({
'a': 'a',
'b': 'b'
}, 'positive')])
self.data = []
for i in range(5):
d = RawStreamQueue()
d.source = 'test'
d.original = {}
d.text = "this is a test"
self.data.append(d)
ClassifiedStream.drop_collection()
def tearDown(self):
ClassifiedStream.drop_collection()
def tearDown(self):
ClassifiedStream.drop_collection()
RawStreamQueue.drop_collection()