How to use the sumy.summarizers.lsa.LsaSummarizer function in sumy

def test_real_example():
    """Source: http://www.prevko.cz/dite/skutecne-pribehy-deti"""
    parser = PlaintextParser.from_string(
        load_resource("snippets/prevko.txt"),
        Tokenizer("czech")
    )
    summarizer = LsaSummarizer(Stemmer("czech"))
    summarizer.stop_words = get_stop_words("czech")

    sentences = summarizer(parser.document, 2)
    assert len(sentences) == 2

def test_issue_5_svd_converges():
    """Source: https://github.com/miso-belica/sumy/issues/5"""
    pytest.skip("Can't reproduce the issue.")

    parser = PlaintextParser.from_string(
        load_resource("articles/svd_converges.txt"),
        Tokenizer("english")
    )
    summarizer = LsaSummarizer(Stemmer("english"))
    summarizer.stop_words = get_stop_words("english")

    sentences = summarizer(parser.document, 20)
    assert len(sentences) == 20

def test_article_example():
    """Source: http://www.prevko.cz/dite/skutecne-pribehy-deti"""
    parser = PlaintextParser.from_string(
        load_resource("articles/prevko_cz_1.txt"),
        Tokenizer("czech")
    )
    summarizer = LsaSummarizer(Stemmer("czech"))
    summarizer.stop_words = get_stop_words("czech")

    sentences = summarizer(parser.document, 20)
    assert len(sentences) == 20

def build_lsa(parser, language):
    summarizer = LsaSummarizer(Stemmer(language))
    summarizer.stop_words = get_stop_words(language)

    return summarizer

if '\\/' not in message:
                inputLine = inputLine + message['message'] + '. '
        # blob = TextBlob(inputLine)
        # wordCounts = blob.word_counts
        # sortedWordCounts = sorted(wordCounts, key=wordCounts.get, reverse=True)
        # outputLine = " ".join(sortedWordCounts[:5])
        # outputLine = groupName.capitalize() + " summarized as " + outputLine
        # self.send_to_whatsapp_id("WACAO!",outputLine)

        LANGUAGE = "english"
        SENTENCES_COUNT = '20%'

        outputLine = groupName.capitalize() + " summarized as: \n"
        parser = PlaintextParser.from_string(inputLine, Tokenizer(LANGUAGE))
        stemmer = Stemmer(LANGUAGE)
        summarizer = LsaSummarizer(stemmer)
        summarizer.stop_words = get_stop_words(LANGUAGE)
        for sentence in summarizer(parser.document, SENTENCES_COUNT):
            outputLine = outputLine + unicode(str(sentence), "utf-8") + "\n"
        self.send_to_whatsapp_id("WACAO!",outputLine)
        # print "sum_basic:"

def get_summary(long_text, sentences=SENTENCES_COUNT):
    parser = PlaintextParser.from_string(chinese_normalnize(long_text), Tokenizer(LANGUAGE))
    stemmer = Stemmer(LANGUAGE)
    summarizer = Summarizer(stemmer)
    summarizer.stop_words = get_stop_words(LANGUAGE)
    return [str(sentence) for sentence in summarizer(parser.document, sentences)]

def summarize(srt_file, n_sentences, language="english"):
    """ Generate segmented summary

    Args:
        srt_file(str) : The name of the SRT FILE
        n_sentences(int): No of sentences
        language(str) : Language of subtitles (default to English)

    Returns:
        list: segment of subtitles

    """
    parser = PlaintextParser.from_string(
        srt_to_txt(srt_file), Tokenizer(language))
    stemmer = Stemmer(language)
    summarizer = LsaSummarizer(stemmer)
    summarizer.stop_words = get_stop_words(language)
    segment = []
    for sentence in summarizer(parser.document, n_sentences):
        index = int(re.findall("\(([0-9]+)\)", str(sentence))[0])
        item = srt_file[index]
        segment.append(srt_segment_to_range(item))
    return segment

stemmer = Stemmer(LANGUAGE)

print("\n====== Luhn ======")
summarizerLuhn = LuhnSummarizer(stemmer)
summarizerLuhn.stop_words = get_stop_words(LANGUAGE)
for sentenceLuhn in summarizerLuhn(parser.document, SENTENCES_COUNT):
    print(sentenceLuhn, "\n")

print("====== TextRank ======")
summarizerTR = TextRankSummarizer(stemmer)
summarizerTR.stop_words = get_stop_words(LANGUAGE)
for sentenceTR in summarizerTR(parser.document, SENTENCES_COUNT):
    print(sentenceTR, "\n")

print("====== LSA ======")
summarizerLSA = LsaSummarizer(stemmer)
summarizerLSA.stop_words = get_stop_words(LANGUAGE)
for sentenceLSA in summarizerLSA(parser.document, SENTENCES_COUNT):
    print(sentenceLSA, "\n")

print("====== Edmonson ======")
summarizerEd = EdmundsonSummarizer(stemmer)
summarizerEd.bonus_words = ('focus', 'proposed', 'method', 'describes')
summarizerEd.stigma_words = ('example')
summarizerEd.null_words = ('literature', 'however')
for sentenceEd in summarizerEd(parser.document, SENTENCES_COUNT):
    print(sentenceEd, "\n")

def get_summary(self,num_sentence):
        out = ''
        try:
            try:
                parser = HtmlParser.from_url(self.url, Tokenizer("english"))
            except:
                try:
                    parser = PlaintextParser.from_string(self.body, Tokenizer("english"))
                except Exception as e:
                    raise(e)

            stemmer = Stemmer('english')
            summarizer = Summarizer(stemmer)
            summarizer.stop_words = get_stop_words('english')

            for sentence in summarizer(parser.document, num_sentence):
                out+=str(sentence)
        except:
            return self.body

        return out

if '\\/' not in message:
                inputLine = inputLine + message['message'] + '. '
        # blob = TextBlob(inputLine)
        # wordCounts = blob.word_counts
        # sortedWordCounts = sorted(wordCounts, key=wordCounts.get, reverse=True)
        # outputLine = " ".join(sortedWordCounts[:5])
        # outputLine = groupName.capitalize() + " summarized as " + outputLine
        # self.send_to_whatsapp_id("WACAO!",outputLine)

        LANGUAGE = "english"
        SENTENCES_COUNT = '20%'

        outputLine = groupName.capitalize() + " summarized as: \n"
        parser = PlaintextParser.from_string(inputLine, Tokenizer(LANGUAGE))
        stemmer = Stemmer(LANGUAGE)
        summarizer = LsaSummarizer(stemmer)
        summarizer = Summarizer(stemmer)
        summarizer.stop_words = get_stop_words(LANGUAGE)
        for sentence in summarizer(parser.document, SENTENCES_COUNT):
            outputLine = outputLine + unicode(str(sentence), "utf-8") + "\n"
        self.send_to_whatsapp_id("WACAO!",outputLine)
        # print "sum_basic:"