old_contents: from __future__ import unicode_literals
  from nose.tools import eq_, assert_almost_equal, assert_greater
  from wordfreq.query import (word_frequency, average_frequency, wordlist_size,
                              wordlist_info, metanl_word_frequency)
  
  
  def test_freq_examples():
      assert_almost_equal(
          word_frequency('normalization', 'en', 'google-books'),
          1.767e-6, places=9
      )
      assert_almost_equal(
          word_frequency('normalization', 'en', 'google-books', 1e-6),
          2.767e-6, places=9
      )
      assert_almost_equal(
          word_frequency('normalisation', 'fr', 'leeds-internet'),
          4.162e-6, places=9
      )
      assert_greater(
          word_frequency('lol', 'xx', 'twitter'),
          word_frequency('lol', 'en', 'google-books')
      )
      eq_(
          word_frequency('totallyfakeword', 'en', 'multi', .5),
          .5
      )
  
  
  def test_compatibility():
      assert_almost_equal(metanl_word_frequency('the|en'), 1e9, places=3)
      assert_almost_equal(metanl_word_frequency('the|en', offset=1e9), 2e9, places=3)
  
  
  def _check_normalized_frequencies(wordlist, lang):
      assert_almost_equal(
          average_frequency(wordlist, lang) * wordlist_size(wordlist, lang),
          1.0, places=6
      )
  
  
  def test_normalized_frequencies():
      for list_info in wordlist_info():
          wordlist = list_info['wordlist']
          lang = list_info['lang']
          yield _check_normalized_frequencies, wordlist, lang
  
new_contents: from __future__ import unicode_literals
  from nose.tools import eq_, assert_almost_equal, assert_greater
  from wordfreq.query import (word_frequency, average_frequency, wordlist_size,
                              wordlist_info)
  
  
  def test_freq_examples():
      assert_almost_equal(
          word_frequency('normalization', 'en', 'google-books'),
          1.767e-6, places=9
      )
      assert_almost_equal(
          word_frequency('normalization', 'en', 'google-books', 1e-6),
          2.767e-6, places=9
      )
      assert_almost_equal(
          word_frequency('normalisation', 'fr', 'leeds-internet'),
          4.162e-6, places=9
      )
      assert_greater(
          word_frequency('lol', 'xx', 'twitter'),
          word_frequency('lol', 'en', 'google-books')
      )
      eq_(
          word_frequency('totallyfakeword', 'en', 'multi', .5),
          .5
      )
  
  
  def _check_normalized_frequencies(wordlist, lang):
      assert_almost_equal(
          average_frequency(wordlist, lang) * wordlist_size(wordlist, lang),
          1.0, places=6
      )
  
  
  def test_normalized_frequencies():
      for list_info in wordlist_info():
          wordlist = list_info['wordlist']
          lang = list_info['lang']
          yield _check_normalized_frequencies, wordlist, lang
  
subject: Remove the tests for metanl_word_frequency too. Doh.