fix az-Latn transliteration, and test

tests/test_transliteration.py

@@ -1,5 +1,6 @@
 from nose.tools import eq_
 from wordfreq import tokenize
+from wordfreq.preprocess import preprocess_text
 
 
 def test_transliteration():
@@ -10,6 +11,21 @@ def test_transliteration():
     eq_(tokenize("Pa, ima tu mnogo stvari koje ne shvataš.", 'sr'),
         ['pa', 'ima', 'tu', 'mnogo', 'stvari', 'koje', 'ne', 'shvataš'])
 
+    # I don't have examples of complete sentences in Azerbaijani that are
+    # naturally in Cyrillic, because it turns out everyone writes Azerbaijani
+    # in Latin letters on the Internet, _except_ sometimes for Wiktionary.
+    # So here are some individual words.
+
+    # 'library' in Azerbaijani Cyrillic
+    eq_(preprocess_text('китабхана', 'az'), 'kitabxana')
+    eq_(preprocess_text('КИТАБХАНА', 'az'), 'kitabxana')
+    eq_(preprocess_text('KİTABXANA', 'az'), 'kitabxana')
+
+    # 'scream' in Azerbaijani Cyrillic
+    eq_(preprocess_text('бағырты', 'az'), 'bağırtı')
+    eq_(preprocess_text('БАҒЫРТЫ', 'az'), 'bağırtı')
+    eq_(preprocess_text('BAĞIRTI', 'az'), 'bağırtı')
+
 
 def test_actually_russian():
     # This looks mostly like Serbian, but was probably actually Russian.

wordfreq/preprocess.py

@@ -162,6 +162,9 @@ def preprocess_text(text, language):
     Azerbaijani (Azeri) has a similar transliteration step to Serbian,
     and then the Latin-alphabet text is handled similarly to Turkish.
 
+    >>> preprocess_text('бағырты', 'az')
+    'bağırtı'
+
     We don't transliterate Traditional to Simplified Chinese in this step.
     There are some steps where we unify them internally: see chinese.py
     for more information.

wordfreq/transliterate.py

@@ -81,7 +81,7 @@ AZ_LATN_TABLE.update({
     ord('Ч'): 'Ç',   ord('ч'): 'ç',
     ord('Х'): 'X',   ord('х'): 'x',
     ord('Ы'): 'I',   ord('ы'): 'ı',
-    ord('И'): 'İ',   ord('и'): 'ı',
+    ord('И'): 'İ',   ord('и'): 'i',
     ord('Ж'): 'J',   ord('ж'): 'j',
     ord('Ј'): 'Y',   ord('ј'): 'y',
     ord('Г'): 'Q',   ord('г'): 'q',