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final.py

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+import os
+
+import nltk
+
+from nltk import *
+from nltk.corpus import stopwords
+from nltk.tokenize import RegexpTokenizer
+#
+#
+#
+# filepath = os.path.join(os.getcwd(), "file2.txt")
+# with open(filepath) as obj:
+#     fullData = obj.read()
+#     fullData = fullData.decode('utf8', 'ignore')
+
+def get_sentence(fullData):
+    sentence = fullData.replace("\n", ". ")
+    return sentence.split(". ")
+
+
+def re_order(output_sents, input):
+    output_sents.sort(lambda s1, s2:
+                      input.find(s1) - input.find(s2))
+    return output_sents
+
+# get_sentence(fullData)
+
+def summary(fullData, summary_length):
+    myregex = RegexpTokenizer('\w+')
+
+    # convert all the words to lowercase for ease of processing
+    words = [word.lower() for word in myregex.tokenize(fullData)]
+
+    #remove all stopwords
+    word = [withoutStopwords for withoutStopwords in words if withoutStopwords not in stopwords.words()]
+
+    frequency = FreqDist(word)
+    # print(frequency.most_common(50))
+
+    fifty_most_frequent = [wordd[0] for wordd in frequency.items()[:100]]
+
+    # actual_sents contains all the original sentences with the case intact
+    my_token = nltk.data.load('tokenizers/punkt/english.pickle')    #Visit http://www.nltk.org/_modules/nltk/tokenize/punkt.html for more information.
+    sentence = my_token.tokenize(fullData)
+    usable_sentence = [lines.lower() for lines in sentence]
+    # usable_sentence = get_sentence(fullData.lower())
+    # usable_sentence = [item for item in get_sentence(fullData) if item != '']
+    sentence_length = len(usable_sentence)
+    # usable_sentence = []
+    # for item in usable_sentence:
+    #     if item != '':
+    #         usable_sentence.append(item)
+
+    # total_sentences = len(usable_sentence)
+    #num_freqWords_inSents stores the number of times a frequent word occurs in each of the sentences
+    num_freqWords_inSents = [0] * sentence_length
+
+    output_sents = []
+    # Loop through all the sentences and all the words to see which sentences contain occurences of the most frequent words
+    for elem in fifty_most_frequent:
+        for i in range(0,sentence_length):
+            if elem in usable_sentence[i] and sentence[i] not in output_sents:
+                output_sents.append(usable_sentence[i])
+                break
+            if len(output_sents) >= summary_length: break
+        if len(output_sents) >= summary_length: break
+                # num_freqWords_inSents[i] = num_freqWords_inSents[i] + 1
+                # if (usable_sentence[i] not in output_sents):
+                #     output_sents.append(usable_sentence[i])
+
+    #store the contents of usable_sentence in a list so that it can be used later
+    # num_freqWords_inSents[:] = [something for something in num_freqWords_inSents if something != 0]
+
+    #map the elements in two lists using the zip function for easy comparision
+    # zipped = zip(num_freqWords_inSents, output_sents)
+
+    #sort the output so that the sentences which contain the most frequent words is displayed first.
+    # sorted_output = [two for (one,two) in sorted(zipped, reverse=True)]
+
+    #take the first two sentence with the most frequent words
+    # final_output = sorted_output[0:7]
+
+    # out_sentence = re_order(final_output, fullData)
+
+    # return " ".join(final_output)
+    return re_order(output_sents, fullData)
+
+def get_summary(fullData,summary_length):
+    print "\n".join(summary(fullData, summary_length))
+
+
+
+
+

runner11.py

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+import os
+from final import get_sentence, get_summary
+
+filepath = os.path.join(os.getcwd(), "file2.txt")
+with open(filepath) as obj:
+    fullData = obj.read()
+    fullData = fullData.decode('utf8', 'ignore')
+
+
+
+title_of_summary = get_sentence(fullData)
+title_of_summary = title_of_summary[0]
+# last_line = title_of_summary[-1]
+print "\t\t\t\t\t\t\t\t\t*---------------------------------Title------------------------------*\n%s"%title_of_summary
+
+summary_length = raw_input("Enter the number of lines you want your summary to be.\n")
+summary_length = int(summary_length)
+print("\n\t\t\t\t\t\t\t\t\t*---------------------------------Summary------------------------------*\n")
+ss = get_summary(fullData, summary_length)
+# print "\t\t\t\t\t\t\t\t\t*---------------------------------Title------------------------------*\n%s" % last_line
+
+