summarizer.py

import nltk
nltk.download('stopwords')
nltk.download('punkt')
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize, sent_tokenize

print("Enter Text")
text = input()
stopWords = set(stopwords.words("english"))
words = word_tokenize(text)

freqTable = dict()
for word in words:
    word = word.lower()
    if word in stopWords:
        continue
    if word in freqTable:
        freqTable[word] += 1
    else:
        freqTable[word] = 1
sentences = sent_tokenize(text)
sentenceValue = dict()

for sentence in sentences:
    for word, freq in freqTable.items():
        if word in sentence.lower():
            if sentence in sentenceValue:
                sentenceValue[sentence] += freq
            else:
                sentenceValue[sentence] = freq


sumValues = 0
for sentence in sentenceValue:
    sumValues += sentenceValue[sentence]


average = int(sumValues / len(sentenceValue))

summary = ''
for sentence in sentences:
    if (sentence in sentenceValue) and (sentenceValue[sentence] > (1.2 * average)):
        summary += " " + sentence
print(summary)