Upload Main class

main.py

+import spacy
+import string
+from collections import Counter
+from spacy.lang.en.stop_words import STOP_WORDS
+from string import punctuation
+
+nlp = spacy.load("en_core_web_sm")
+
+# reading text file
+text1 = open("student_answer.txt", encoding="utf-8").read()
+text2 = open("teacher_answer.txt", encoding="utf-8").read()
+
+
+# converting to lowercase
+lower_case1 = text1.lower()
+lower_case2 = text2.lower()
+
+# Removing punctuations
+cleaned_text1 = lower_case1.translate(str.maketrans('', '', string.punctuation))
+cleaned_text2 = lower_case2.translate(str.maketrans('', '', string.punctuation))
+
+# assigning a name
+doc1 = nlp(cleaned_text1)
+doc2 = nlp(cleaned_text2)
+
+for sent in doc1.sents:
+    word_count = 0
+    print("Student's Answer: ")
+    print(sent.text)
+    for words in sent:
+        # print(words.text)
+
+        word_count = word_count + 1
+    print(f"\nWord count in the answer: {word_count}")
+
+print("Identified keywords in the given answer:")
+similar_word_list = []
+for token in doc1:
+    if token.text == "integration" or token.text == "virtually" or token.text == "internal":
+        a = token.text
+        similar_word_list.append(a)
+
+   #     print(f"\n** {a.upper()}")
+
+print(similar_word_list)
+w = Counter(similar_word_list)
+print(w)
+