Use Text Summarization Algorithms to Help Aid the Writing of Meta Descriptions

metadesc.py

import csv
import os
from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Lsa
from sumy.summarizers.luhn import LuhnSummarizer as Luhn
from sumy.summarizers.text_rank import TextRankSummarizer as TxtRank
from sumy.summarizers.lex_rank import LexRankSummarizer as LexRank
from sumy.summarizers.sum_basic import SumBasicSummarizer as SumBasic
from sumy.summarizers.kl import KLSummarizer as KL
from sumy.summarizers.edmundson import EdmundsonSummarizer as Edmundson
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words

LANGUAGE = "english"
SENTENCES_COUNT = 1

urlinput = os.path.join(os.path.dirname(__file__), input('Enter input text file: '))
urls = open(urlinput, "r")

outputcsv = os.path.join(os.path.dirname(__file__), input('Enter a filename (minus file extension): ')+'.csv')

f = csv.writer(open(outputcsv, "w+", newline="\n", encoding="utf-8"))
f.writerow(["URL", "Copy", "Summarization Algorithm"])

for line in iter(urls):
	stemmer = Stemmer(LANGUAGE)
	
	lsaSummarizer = Lsa(stemmer)
	lsaSummarizer.stop_words = get_stop_words(LANGUAGE)
	
	luhnSummarizer = Luhn(stemmer)
	luhnSummarizer.stop_words = get_stop_words(LANGUAGE)
	# edmundsonSummarizer.bonus_words = get_bonus_words
	
	lexrankSummarizer = LexRank(stemmer)
	lexrankSummarizer.stop_words = get_stop_words(LANGUAGE)
	
	textrankSummarizer = TxtRank(stemmer)
	textrankSummarizer.stop_words = get_stop_words(LANGUAGE)
	
	sumbasicSummarizer = SumBasic(stemmer)
	sumbasicSummarizer.stop_words = get_stop_words(LANGUAGE)
	
	klSummarizer = KL(stemmer)
	klSummarizer.stop_words = get_stop_words(LANGUAGE)
	
	parser = HtmlParser.from_url(line, Tokenizer(LANGUAGE))
	
	for sentence in lsaSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"LSA"])
	print("Summarizing URL via LSA: " + line)
	
	for sentence in luhnSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"Luhn"])
	print("Summarizing URL via Luhn: " + line)	

	for sentence in lexrankSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"LexRank"])
	print("Summarizing URL via LexRank: " + line)	

	for sentence in textrankSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"TextRank"])
	print("Summarizing URL via TextRank: " + line)
	
	for sentence in sumbasicSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"SumBasic"])
	print("Summarizing URL via SumBasic: " + line)	

	for sentence in klSummarizer(parser.document, SENTENCES_COUNT):
		print(sentence)
		f.writerow([line,sentence,"KL-Sum"])
	print("Summarizing URL via KL-Sum: " + line)
	
urls.close()
print ("Writing to " + outputcsv + " complete.")