<gh_stars>100-1000
import blingfire
import nltk
import pysbd
import spacy
import stanza

from syntok.tokenizer import Tokenizer
import syntok.segmenter as syntok_segmenter

pysbd_segmenter = pysbd.Segmenter(language="en", clean=False, char_span=False)

nlp = spacy.blank('en')
nlp.add_pipe(nlp.create_pipe("sentencizer"))
nlp_dep = spacy.load('en_core_web_sm', disable=["ner"])
#stanza.download('en')
stanza_nlp = stanza.Pipeline(lang='en', processors='tokenize')

syntok_tokenizer = Tokenizer()

def blingfire_tokenize(text):
    return blingfire.text_to_sentences(text).split('\n')

def nltk_tokenize(text):
    return nltk.sent_tokenize(text)

def pysbd_tokenize(text):
    segments = pysbd_segmenter.segment(text)
    segments = [s.strip() for s in segments]
    return segments

def spacy_tokenize(text):
    return [sent.text.strip("\n") for sent in nlp(text).sents]

def spacy_dep_tokenize(text):
    return [sent.text.strip("\n") for sent in nlp_dep(text).sents]

def stanza_tokenize(text):
    return [e.text for e in stanza_nlp(text).sentences]

def make_sentences(segmented_tokens):
    for sentence in segmented_tokens:
        yield "".join(str(token) for token in sentence).strip()

def syntok_tokenize(text):
    tokens = syntok_tokenizer.split(text)
    result = syntok_segmenter.split(iter(tokens))
    segments = [sent for sent in make_sentences(result)]
    return segments

def speed_benchmark(big_text, tokenize_func):
    segments = tokenize_func(big_text)
    return segments

if __name__ == "__main__":
    import time
    libraries = (
        blingfire_tokenize,
        nltk_tokenize,
        pysbd_tokenize,
        spacy_tokenize,
        spacy_dep_tokenize,
        stanza_tokenize,
        syntok_tokenize)

    for tokenize_func in libraries:
        t = time.time()
        # wget http://www.gutenberg.org/files/1661/1661-0.txt -P benchmarks/
        with open('benchmarks/1661-0.txt') as bigfile:
            big_text = bigfile.read()
        sentences = speed_benchmark(big_text, tokenize_func)

        time_taken = time.time() - t
        print()
        print(tokenize_func.__name__)
        print('Speed : {:>20.2f} ms'.format(time_taken * 1000))
