Readability measures are used to score the reading difficulty of a text, for the purposes of selecting texts of appropriate difficulty for language learners. Let us define to be the average number of letters per word, and to be the average number of words per sentence, in a given text. The Automated Readability Index (ARI) of the text is defined to be: 4.71+0.521.43 . Write a function readability that computes the ARI score for various sections of the Brown Corpus. The function should take as an arugment a section of the Brown Corpus represented by a letter (e.g. Section F is "popular lore" and Section J is "learned"). Make use of the fact that nltk.corpus.brown.words() produces a sequence of words, while nltk.corpus.brown.sents() produces a sequence of sentences.

It should pass following test def test_readability(self): self.assertAlmostEqual(readability('f'), 10.254756197101155, places=2)