Clea dust out of 09

09-the-one/tf-09.py

@@ -1,9 +1,8 @@
 #!/usr/bin/env python
-
 import sys, re, operator, string
 
 #
-# The monadic class for this example
+# The One class for this example
 #
 class TFTheOne:
     def __init__(self, v):
@@ -20,49 +19,28 @@ def printm(monad):
 # The functions
 #
 def read_file(path_to_file):
-    """
+    with open(path_to_file) as f:
-    Takes a path to a file and returns the entire
+        data = f.read()
-    contents of the file as a string
-    """
-    f = open(path_to_file)
-    data = f.read()
-    f.close()
     return data
 
 def filter_chars(str_data):
-    """
-    Takes a string and returns a copy with all nonalphanumeric chars
-    replaced by white space
-    """
     pattern = re.compile('[\W_]+')
     return pattern.sub(' ', str_data)
 
 def normalize(str_data):
-    """
-    Takes a string and returns a copy with all characters in lower case """
     return str_data.lower()
 
 def scan(str_data):
-    """
-    Takes a string and scans for words, returning
-    a list of words.
-    """
     return str_data.split()
 
 def remove_stop_words(word_list):
-    """ Takes a list of words and returns a copy with all stop words removed """
+    with open('../stop_words.txt') as f:
-    f = open('../stop_words.txt')
+        stop_words = f.read().split(',')
-    stop_words = f.read().split(',')
-    f.close()
     # add single-letter words
     stop_words.extend(list(string.ascii_lowercase))
     return [w for w in word_list if not w in stop_words]
 
 def frequencies(word_list):
-    """
-    Takes a list of words and returns a dictionary associating
-    words with frequencies of occurrence
-    """
     word_freqs = {}
     for w in word_list:
         if w in word_freqs:
@@ -72,16 +50,8 @@ def frequencies(word_list):
     return word_freqs
 
 def sort(word_freq):
-    """
-    Takes a dictionary of words and their frequencies and returns a list 
-    of pairs where the entries are sorted by frequency 
-    """
     return sorted(word_freq.iteritems(), key=operator.itemgetter(1), reverse=True)
 
-def print_freqs(word_freqs):
-    for tf in word_freqs[0:25]:
-        print tf[0], ' - ', tf[1]
-
 def top25_freqs(word_freqs):
     top25 = ""
     for tf in word_freqs[0:25]: