Better passive aggressive style -- catch precondition failure too, and treat them all as annoying things that put us in a bad mood.

23-passive-aggressive/tf-23.py

@@ -1,6 +1,8 @@
 #!/usr/bin/env python
 import sys, re, operator, string
 
+angry = "^*(&%#@^! (I don't want this)"
+
 #
 # The PassiveAggressive class for this example
 #
@@ -14,6 +16,8 @@ class TFPassiveAggressive:
         if self._e == None:
             try:
                 self._value = func(self._value)
+                if self._value == angry:
+                    raise AssertionError(angry)
             except Exception as e:
                 self._e = e
                 self._offending_func = func
@@ -29,9 +33,15 @@ class TFPassiveAggressive:
 # The functions
 #
 def get_input(arg):
+    if len(sys.argv) <= 1:
+        return angry
+
     return sys.argv[1]
 
 def extract_words(path_to_file):
+    if type(path_to_file) != str or not path_to_file:
+        return angry
+
     with open(path_to_file) as f:
         data = f.read()
     pattern = re.compile('[\W_]+')
@@ -39,6 +49,9 @@ def extract_words(path_to_file):
     return word_list
 
 def remove_stop_words(word_list):
+    if type(word_list) != list or not word_list:
+        return angry
+
     with open('../stop_words.txt') as f:
         stop_words = f.read().split(',')
     # add single-letter words
@@ -46,6 +59,9 @@ def remove_stop_words(word_list):
     return [w for w in word_list if not w in stop_words]
 
 def frequencies(word_list):
+    if type(word_list) != list or not word_list:
+        return angry
+
     word_freqs = {}
     for w in word_list:
         if w in word_freqs:
@@ -54,10 +70,16 @@ def frequencies(word_list):
             word_freqs[w] = 1
     return word_freqs
 
-def sort(word_freq):
+def sort(word_freqs):
-    return sorted(word_freq.iteritems(), key=operator.itemgetter(1), reverse=True)
+    if type(word_freqs) != dict or not word_freqs:
+        return angry
+
+    return sorted(word_freqs.iteritems(), key=operator.itemgetter(1), reverse=True)
 
 def top25_freqs(word_freqs):
+    if type(word_freqs) != dict or not word_freqs:
+        return angry
+
     top25 = ""
     for tf in word_freqs[0:25]:
         top25 += str(tf[0]) + ' - ' + str(tf[1]) + '\n'