Added style #7

07-things/README.md

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+Style #7
+==============================
+
+Constraints:
+
+- The larger problem is decomposed into 'things' that make sense for
+  the problem domain 
+
+- Each 'thing' is a capsule of data that exposes procedures to the
+  rest of the world
+
+- Data is never accessed directly, only through these procedures
+
+- Capsules can reappropriate procedures defined in other capsules
+
+Possible names:
+
+- Object-oriented style
+- The Kingdom of Nouns

07-things/tf-07.py

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+import sys, re, operator, string
+from abc import ABCMeta
+
+#
+# The classes
+#
+class TFExercise(object):
+    __metaclass__ = ABCMeta
+
+    def info(self):
+        return self.__class__.__name__ + ": No major data structure"
+
+class DataStorageManager(TFExercise):
+    """ Models the contents of the file """
+    _data = ''
+    def __init__(self, path_to_file):
+        f = open(path_to_file)
+        self._data = f.read()
+        f.close()
+        self.__filter_chars()
+        self.__normalize()
+
+    def __filter_chars(self):
+        """
+        Takes a string and returns a copy with all nonalphanumeric chars
+        replaced by white space
+        """
+        pattern = re.compile('[\W_]+')
+        self._data = pattern.sub(' ', self._data)
+
+    def __normalize(self):
+        """
+        Takes a string and returns a copy with all characters in lower case
+        """
+        self._data = self._data.lower()
+
+    def words(self):
+        """
+        Returns the list words in storage
+        """
+        data_str = ''.join(self._data)
+        return data_str.split()
+
+    def info(self):
+        return self.__class__.__name__ + ": My major data structure is a " + self._data.__class__.__name__
+
+class StopWordManager(TFExercise):
+    """ Models the stop word filter """
+    _stop_words = []
+    def __init__(self):
+        f = open('../stop_words.txt')
+        self._stop_words = f.read().split(',')
+        f.close()
+        # add single-letter words
+        self._stop_words.extend(list(string.ascii_lowercase))
+
+    def is_stop_word(self, word):
+        return word in self._stop_words
+
+    def info(self):
+        return self.__class__.__name__ + ": My major data structure is a " + self._stop_words.__class__.__name__
+
+class WordFrequencyManager(TFExercise):
+    """ Keeps the word frequency data """
+    _word_freqs = {}
+
+    def increment_count(self, word):
+        if word in self._word_freqs:
+            self._word_freqs[word] += 1
+        else:
+            self._word_freqs[word] = 1
+
+    def sorted(self):
+        return sorted(self._word_freqs.iteritems(), key=operator.itemgetter(1), reverse=True)
+
+    def info(self):
+        return self.__class__.__name__ + ": My major data structure is a " + self._word_freqs.__class__.__name__
+
+
+class WordFrequencyController(TFExercise):
+    def __init__(self, path_to_file):
+        self._storage_manager = DataStorageManager(path_to_file)
+        self._stop_word_manager = StopWordManager()
+        self._word_freq_manager = WordFrequencyManager()
+
+    def run(self):
+        for w in self._storage_manager.words():
+            if not self._stop_word_manager.is_stop_word(w):
+                self._word_freq_manager.increment_count(w)
+
+        word_freqs = self._word_freq_manager.sorted()
+        for tf in word_freqs[0:25]:
+            print tf[0], ' - ', tf[1]
+
+#
+# The main function
+#
+WordFrequencyController(sys.argv[1]).run()