#import nltk
#nltk.download('punkt')

from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lex_rank import LexRankSummarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words

def getSummary(text, nr_sentences):
    summary=[]
    LANGUAGE = "english"
    SENTENCES_COUNT = nr_sentences
    #parser = PlaintextParser.from_file("/Users/hujo/Downloads/Channel_Summaries/wholesaleted.srt.pnct.txt", Tokenizer(LANGUAGE))
    parser = PlaintextParser.from_string(text, Tokenizer(LANGUAGE))
    #print(parser.document)
    stemmer = Stemmer(LANGUAGE)
    summarizer = LexRankSummarizer(stemmer)
    summarizer.stop_words = get_stop_words(LANGUAGE)
    for sentence in summarizer(parser.document, SENTENCES_COUNT):
        summary.append(sentence)

    return summary