Base_Classifier wasn't unicode-ready.

Fixed bug where _word_set was based on train_set, even if train_set
is filelike instead of iterable.

Author: emmyzero

textblob/classifiers.py

@@ -83,11 +83,11 @@ def basic_extractor(document, train_set):
         el_zero = iter(train_set).next() #Infer input from first element.
     except StopIteration:
         return {}
-    if isinstance(el_zero, str):
+    if isinstance(el_zero, basestring):
         word_features = [w for w in chain([el_zero],train_set)]
     else:
         try:
-            assert(isinstance(el_zero[0], str))
+            assert(isinstance(el_zero[0], basestring))
             word_features = _get_words_from_dataset(chain([el_zero],train_set))
         except:
             raise ValueError('train_set is proabably malformed.')
@@ -136,7 +136,7 @@ def __init__(self, train_set, feature_extractor=basic_extractor, format=None, **
             self.train_set = self._read_data(train_set, format)
         else:  # train_set is a list of tuples
             self.train_set = train_set
-        self._word_set = _get_words_from_dataset(train_set) #Keep a hidden set of unique words.
+        self._word_set = _get_words_from_dataset(self.train_set) #Keep a hidden set of unique words.
         self.train_features = None
 
     def _read_data(self, dataset, format=None):