hw

Unit_test.py

+from unittest import TestCase
+from sentiment import method_11
+from sentiment import first_input13
+
+
+class Unit_test(TestCase):
+    def test_method_11(self):
+        with open('sentiment.txt') as s:
+            reviews = list(s)
+        sentiments = {}
+        self.assertEqual(method_11(reviews,sentiments)['arty'], [3,1,1,0])
+
+    def test_first_Input13(self):
+        sentiments = {}
+        y=input()
+        self.assertEqual(first_input13(sentiments,y)['Invalid input'])
+

sentiment.py

 from __future__ import print_function, division
 from builtins import input
+import numpy as np
 
 
 def main():
     reviews = list()
 
+
     try:
         with open('sentiment.txt') as s:
             reviews = list(s)
-            # print(len(reviews))
+
     except OSError:
         print('Does not exist')
     sentiments = {}
@@ -25,7 +27,7 @@ def main():
     #         y=x, num=0, av='None'
     #     )
     # print(output)
-    y = None
+    #y = None
 
     while True:
         print('Enter your choice: \n'
@@ -45,67 +47,98 @@ def main():
         if y == 5:
             print('Goodbye')
             break
-        if y == 1:
-            x = input("Enter a word")
-            if x in sentiments:
+        first_input13(sentiments, y)
 
-                output = 'The word "{y}" appears "{num}" times with an average sentiment of {av}. '.format(
-                    y=x, num=len(sentiments[x]), av=sum(sentiments[x]) / len(sentiments[x]))
-
-            else:
-                output = 'The word "{y}" appears "{num}" times with an average sentiment of {av}. '.format(
-                    y=x, num=0, av='None'
-                )
-            print(output)
-        average = list()
-        if y == 2 or y == 3:
+        if y == 2 or y == 3 or y==4:
+            average = list()
             file = input('Enter a file')
         try:
             with open(file) as file_words:
                 user_file = file_words.read().split()
-                for word_in_file in user_file:
-                    if word_in_file in sentiments.keys():
-                        average.append(sum(sentiments[word]) / len(sentiments[word]))
-
-            if y == 2:
-                average.append(sum(sentiments[word_in_file]) / len(sentiments[word_in_file]))
-                if not average:
-                    print('The average score of words in {y} is None '.format(y=file))
-                else:
-                    average_words = sum(average) / len(average)
-
-                if average_words >= 2.01:
-                    print('The average score of words in {y} is {av}'.format(y=file, av=average_words))
-                    print('The overall sentiment of {y} is positive'.format(y=file))
-                elif average_words <= 1.99:
-                    print('The average score of words in {y} is {av}'.format(y=file, av=average_words))
-                    print('The overall sentiment of {y} is negative'.format(y=file))
-                else:
-                    print('The average score of words in {y} is  {av}'.format(y=file, av=average_words))
-                    print('The overall sentiment of {y} is neutral'.format(y=file))
-
-            if y == 3:
-                # rating = sum(sentiments[x])/len(sentiments[x])
-                split_file = file.split()
-                #
-                highest_score = max(average)
-                lowest_score = min(average)
-                p = average.append(sum_word)
-
-                for check_word in split_file:
-                    if check_word in sentiments:
-                        method_11(check_word)
-                        sum_word = sum(method_11(check_word)) / len(method_11(check_word))
-
-                for file_word, rate in sum_word.items():
-                    if rate == highest_score:
-                        j = file_word
-                    if rate == lowest_score:
-                        j == file_word
-                    print('The most positive word is {phrase} with a score of {j}'.format(phrase=j, j=highest_score))
-                    print('The most negative word is {phrase} with a score of {min}'.format(phrase=j, min=lowest_score))
         except IOError:
+            raise
             print('File could not be found')
+        for word_in_file in user_file:
+            if word_in_file in sentiments.keys():
+                average.append(sum(sentiments[word]) / len(sentiments[word]))
+
+        if y == 2:
+            average.append(sum(sentiments[word_in_file]) / len(sentiments[word_in_file]))
+            if not average:
+                print('The average score of words in {y} is None '.format(y=file))
+            else:
+                one_word_average = sum(average) / len(average)
+
+            if one_word_average >= 2.01:
+                print('The average score of words in {y} is {av}'.format(y=file, av=one_word_average))
+                print('The overall sentiment of {y} is positive'.format(y=file))
+            elif one_word_average <= 1.99:
+                print('The average score of words in {y} is {av}'.format(y=file, av=one_word_average))
+                print('The overall sentiment of {y} is negative'.format(y=file))
+            else:
+                print('The average score of words in {y} is  {av}'.format(y=file, av=one_word_average))
+                print('The overall sentiment of {y} is neutral'.format(y=file))
+
+        if y == 3:
+
+            max_score = None
+            min_score = None
+            max_word = None
+            min_Word = None
+            number = 0
+            score_of_one_word = sum(sentiments[word_in_file]) / len(sentiments[word_in_file])
+            for word_in_file in user_file:
+                if word_in_file in sentiments.keys():
+
+
+                    if max_score is None:
+
+                        max_score = score_of_one_word
+                        max_word = word_in_file
+                    if score_of_one_word> max_score:
+                        max_score = score_of_one_word
+                        max_word = word_in_file
+                    if min_score is None:
+                        min_score = score_of_one_word
+                        min_Word = word_in_file
+                    if score_of_one_word < min_score:
+                        min_score = word_in_file
+                        min_Word = word_in_file
+
+            print('The most positive word is {phrase} with a score of {max}'.format(phrase=max_word, max=max_score))
+            print('The most negative word is {phrase} with a score of {min}'.format(phrase=min_Word, min=min_score))
+        if y == 4:
+            lowest_scores= []
+            largest_scores =[]
+
+            score_of_one_word = sum(sentiments[word_in_file]) / len(sentiments[word_in_file])
+            for word_in_file in user_file:
+                if word_in_file in sentiments.keys():
+                    if score_of_one_word <= 1.99:
+                        lowest_scores.append(word_in_file)
+                    elif one_word_average>= 2.01:
+                        largest_scores.append(word_in_file)
+            lowest_scores = str([lowest_scores])
+            largest_scores = str([largest_scores])
+            with open('negative.txt', 'w') as negative_file:
+                negative_file.write(lowest_scores)
+            with open('positive.txt', 'w') as positive_file:
+                positive_file.write(largest_scores)
+
+
+def first_input13(sentiments, y):
+    if y == 1:
+        x = input("Enter a word")
+        if x in sentiments:
+
+            output = 'The word "{y}" appears "{num}" times with an average sentiment of {av}. '.format(
+                y=x, num=len(sentiments[x]), av=sum(sentiments[x]) / len(sentiments[x]))
+
+        else:
+            output = 'The word "{y}" appears "{num}" times with an average sentiment of {av}. '.format(
+                y=x, num=0, av='None'
+            )
+        print(output)
 
 
 def method_11(reviews, sentiments):

test_method_11.py

-from unittest import TestCase
-from sentiment import method_11
-
-
-class TestMethod_11(TestCase):
-    def test_method_11(self):
-        reviews = ['John', "jack "]
-        sentiments = [2,2]
-        self.assertEqual(method_11(reviews,sentiments)[3,0,1,1], ['arty'])
-