Run flake when running tests

Also fix a typo in an error message

Author: sloria

dev-requirements.txt

@@ -1,6 +1,5 @@
 nose>=1.3.0
 tox>=2.6.0
-wheel
-twine
 invoke>=0.15.0
 mock
+flake8==3.5.0

run_tests.py

@@ -12,8 +12,11 @@
     python run_tests.py no-internet
 '''
 from __future__ import unicode_literals
-import nose
+import subprocess
 import sys
+
+import nose
+
 from textblob.compat import PY2
 
 PY26 = PY2 and int(sys.version_info[1]) < 7
@@ -22,6 +25,9 @@
 
 def main():
     args = get_argv()
+    retcode = subprocess.call(['flake8', 'textblob'])
+    if retcode:
+        sys.exit(1)
     success = nose.run(argv=args)
     sys.exit(0) if success else sys.exit(1)
 
@@ -59,5 +65,6 @@ def get_argv():
         args.extend(["-A", attr_expression])
     return args
 
+
 if __name__ == '__main__':
     main()

setup.cfg

@@ -2,5 +2,19 @@
 universal = 1
 
 [flake8]
-ignore = E501,E127,E128,E265,E302
+ignore = E501,E127,E128,E265,E302,E266
 max-line-length = 90
+exclude =
+  .git,
+  .ropeproject,
+  .tox,
+  docs,
+  .git,
+  build,
+  env,
+  venv,
+  # Exclude vendorized code
+  textblob/en,
+  textblob/unicodecsv,
+  textblob/_text.py,
+  textblob/compat.py

textblob/base.py

@@ -65,6 +65,7 @@ def itokenize(self, text, *args, **kwargs):
 
 ##### SENTIMENT ANALYZERS ####
 
+
 DISCRETE = 'ds'
 CONTINUOUS = 'co'
 

textblob/blob.py

@@ -433,7 +433,7 @@ def sentiment_assessments(self):
         :rtype: namedtuple of the form ``Sentiment(polarity, subjectivity,
         assessments)``
         """
-        return self.analyzer.analyze(self.raw,keep_assessments=True)
+        return self.analyzer.analyze(self.raw, keep_assessments=True)
 
     @cached_property
     def polarity(self):

textblob/classifiers.py

@@ -89,8 +89,8 @@ def basic_extractor(document, train_set):
         try:
             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.')
+        except Exception:
+            raise ValueError('train_set is probably malformed.')
 
     tokens = _get_document_tokens(document)
     features = dict(((u'contains({0})'.format(word), (word in tokens))
@@ -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(self.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):

textblob/download_corpora.py

@@ -46,5 +46,6 @@ def main():
         download_all()
     print("Finished.")
 
+
 if __name__ == '__main__':
     main()

textblob/en/sentiments.py

@@ -23,23 +23,25 @@ class PatternAnalyzer(BaseSentimentAnalyzer):
     where [assessments] is a list of the assessed tokens and their
     polarity and subjectivity scores
     """
-
     kind = CONTINUOUS
+    # This is only here for backwards-compatibility.
+    # The return type is actually determined upon calling analyze()
+    RETURN_TYPE = namedtuple('Sentiment', ['polarity', 'subjectivity'])
 
     def analyze(self, text, keep_assessments=False):
         """Return the sentiment as a named tuple of the form:
         ``Sentiment(polarity, subjectivity, [assessments])``.
         """
         #: Return type declaration
         if keep_assessments:
-            RETURN_TYPE = namedtuple('Sentiment', ['polarity', 'subjectivity', 'assessments'])
+            Sentiment = namedtuple('Sentiment', ['polarity', 'subjectivity', 'assessments'])
             assessments = pattern_sentiment(text).assessments
-            polarity,subjectivity = pattern_sentiment(text)
-            return RETURN_TYPE( polarity,subjectivity,assessments )
+            polarity, subjectivity = pattern_sentiment(text)
+            return Sentiment(polarity, subjectivity, assessments)
 
         else:
-            RETURN_TYPE = namedtuple('Sentiment', ['polarity', 'subjectivity'])
-        return RETURN_TYPE(*pattern_sentiment(text))
+            Sentiment = namedtuple('Sentiment', ['polarity', 'subjectivity'])
+            return Sentiment(*pattern_sentiment(text))
 
 
 def _default_feature_extractor(words):

textblob/exceptions.py

@@ -15,6 +15,7 @@ class TextBlobError(Exception):
     """A TextBlob-related error."""
     pass
 
+
 TextBlobException = TextBlobError  # Backwards compat
 
 class MissingCorpusError(TextBlobError):
@@ -25,6 +26,7 @@ class MissingCorpusError(TextBlobError):
     def __init__(self, message=MISSING_CORPUS_MESSAGE, *args, **kwargs):
         super(MissingCorpusError, self).__init__(message, *args, **kwargs)
 
+
 MissingCorpusException = MissingCorpusError  # Backwards compat
 
 class DeprecationError(TextBlobError):

textblob/formats.py

@@ -127,6 +127,7 @@ def detect(cls, stream):
         except ValueError:
             return False
 
+
 _registry = OrderedDict([
     ('csv', CSV),
     ('json', JSON),

textblob/tokenizers.py

@@ -56,6 +56,7 @@ def tokenize(self, text):
         '''Return a list of sentences.'''
         return nltk.tokenize.sent_tokenize(text)
 
+
 #: Convenience function for tokenizing sentences
 sent_tokenize = SentenceTokenizer().itokenize
 

textblob/translate.py

@@ -98,8 +98,7 @@ def _unescape(text):
     """Unescape unicode character codes within a string.
     """
     pattern = r'\\{1,2}u[0-9a-fA-F]{4}'
-    decode = lambda x: codecs.getdecoder('unicode_escape')(x.group())[0]
-    return re.sub(pattern, decode, text)
+    return re.sub(pattern, lambda x: codecs.getdecoder('unicode_escape')(x.group())[0], text)
 
 
 def _calculate_tk(source):