Merge pull request #120 from mkcor/process_text-return-dict

Let process_text() return a dict.

README.md

@@ -5,7 +5,8 @@ word_cloud
 ==========
 
 A little word cloud generator in Python. Read more about it on the [blog
-post][blog-post] or the [website][website]
+post][blog-post] or the [website][website].
+The code is Python 2, but Python 3 compatible.
 
 ## Installation
 

test/test_wordcloud.py

@@ -169,6 +169,26 @@ def test_single_color_func_grey():
     assert_equal(red_function(random_state=random), 'rgb(56, 56, 56)')
 
 
+def test_process_text():
+    # test that process function returns a dict
+    wc = WordCloud(max_words=50)
+    result = wc.process_text(THIS)
+
+    # check for proper return type
+    assert_true(isinstance(result, dict))
+
+
+def test_generate_from_frequencies():
+    # test that generate_from_frequencies() takes input argument of class
+    # 'dict_items'
+    wc = WordCloud(max_words=50)
+    words = wc.process_text(THIS)
+    items = words.items()
+    result = wc.generate_from_frequencies(items)
+
+    assert_true(isinstance(result, WordCloud))
+
+
 def check_parameters():
     # check that parameters are actually used
     pass

wordcloud/wordcloud.py

@@ -376,9 +376,12 @@ class WordCloud(object):
 
         Returns
         -------
-        words : list of tuples (string, float)
+        words : dict (string, int)
             Word tokens with associated frequency.
 
+        ..versionchanged:: 1.2.2
+            Changed return type from list of tuples to dict.
+
         Notes
         -----
         There are better ways to do word tokenization, but I don't want to
@@ -427,19 +430,23 @@ class WordCloud(object):
             first = max(d2.items(), key=item1)[0]
             d3[first] = sum(d2.values())
 
-        return d3.items()
+        return d3
 
     def generate_from_text(self, text):
         """Generate wordcloud from text.
 
         Calls process_text and generate_from_frequencies.
 
+        ..versionchanged:: 1.2.2
+            Argument of generate_from_frequencies() is not return of
+            process_text() any more.
+
         Returns
         -------
         self
         """
         words = self.process_text(text)
-        self.generate_from_frequencies(words)
+        self.generate_from_frequencies(words.items())
         return self
 
     def generate(self, text):