old_contents: from unittest import TestCase
  from itertools import repeat, imap, izip, cycle
  
  from spicedham.bayes import Bayes
  from spicedham import Spicedham
  
  
  class TestBayes(TestCase):
      
      def test_classify(self):
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          alphabet = map(chr, range(97, 123))
          for letter in alphabet:
              p = b.classify(letter)
              self.assertEqual(p, 0.5)
  
      def _training(self, bayes):
          alphabet = map(chr, range(97, 123))
          reversed_alphabet = reversed(alphabet)
          messagePairs = izip(alphabet, reversed_alphabet)
          for message, is_spam in izip(messagePairs, cycle((True, False))):
              bayes.train(message, is_spam)
  
      def test_train(self):
          alphabet = map(chr, range(97, 123))
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          for letter in alphabet:
              result = sh.backend.get_key(b.__class__.__name__, letter)
              self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
              self.assertGreaterEqual(result['numTotal'], result['numSpam'])
  
new_contents: from unittest import TestCase
  from itertools import repeat, imap, izip, cycle
  
  from spicedham.bayes import Bayes
  from spicedham import Spicedham
  
  
  class TestBayes(TestCase):
      
      def test_classify(self):
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          alphabet = map(chr, range(97, 123))
          for letter in alphabet:
              p = b.classify(letter)
              self.assertEqual(p, 0.5)
  
      def _training(self, bayes):
          alphabet = map(chr, range(97, 123))
          reversed_alphabet = reversed(alphabet)
          messagePairs = izip(alphabet, reversed_alphabet)
          for message, is_spam in izip(messagePairs, cycle((True, False))):
              bayes.train(message, is_spam)
  
      def test_train(self):
          alphabet = map(chr, range(97, 123))
          sh = Spicedham()
          b = Bayes(sh.config, sh.backend)
          b.backend.reset()
          self._training(b)
          for letter in alphabet:
              result = sh.backend.get_key(b.__class__.__name__, letter)
              self.assertEqual(result, {'numTotal': 2, 'numSpam': 1})
              self.assertTrue(result['numTotal'] >= result['numSpam'])
  
subject: Replace assertGreaterEqual with assertTrue(a >= b)