import nltk
from nltk.util import ngrams
 
# Function to generate n-grams from sentences.
def extract_ngrams(data, num):
    n_grams = ngrams(nltk.word_tokenize(data), num)
    return [ ' '.join(grams) for grams in n_grams]
 
data = 'A class is a blueprint for the object.'
print('using nltk..........')
print("1-gram: ", extract_ngrams(data, 1))
print("2-gram: ", extract_ngrams(data, 2))
print("3-gram: ", extract_ngrams(data, 3))
print("4-gram: ", extract_ngrams(data, 4))

from textblob import TextBlob
 
# Function to generate n-grams from sentences.
def extract_ngrams(data, num):
    n_grams = TextBlob(data).ngrams(num)
    return [ ' '.join(grams) for grams in n_grams]
 
data = 'A class is a blueprint for the object.'
print('using textblob..........') 
print("1-gram: ", extract_ngrams(data, 1))
print("2-gram: ", extract_ngrams(data, 2))
print("3-gram: ", extract_ngrams(data, 3))
print("4-gram: ", extract_ngrams(data, 4))