text_plain_output_1.png
from nltk.tokenize import TreebankWordTokenizer

from nltk.tokenize import WordPunctTokenizer

from nltk.tokenize import sent_tokenize

import nltk

import nltk

import re

import string

text1 = "ThIs's   ã sent tokenize test  .  this's sent two. is this sent three? sent 4 is cool! Now it's your turn."

"""
Sentence tokenize in NLTK with sent_tokenize 
The sent_tokenize function uses an instance of NLTK known as PunktSentenceTokenizer
This instance of NLTK has already been trained to perform tokenization on different European languages on the basis of letters or punctuation that mark the beginning and end of sentences
"""
from nltk.tokenize import sent_tokenize
'\nAutres manières \n'
punkt_st = nltk.tokenize.PunktSentenceTokenizer()
sample_sentences = punkt_st.tokenize(text1)

""" Autre manière de procéder """
import nltk.data
tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
french_tokenizer = nltk.data.load('tokenizers/punkt/french.pickle')

""" 
Naive Split
"""
'\nTokenizing text into words\n'
import nltk
tokens = nltk.word_tokenize(text1)
'\nEquivalent method with TreebankWordTokenizer\n'
from nltk.tokenize import TreebankWordTokenizer
tokenizer = TreebankWordTokenizer()
'\nEquivalent method with WordPunctTokenizer  \n'
from nltk.tokenize import WordPunctTokenizer
tokenizer = WordPunctTokenizer()

def tokenize_word_text(text):
    tokens = nltk.word_tokenize(text)
    tokens = [token.strip() for token in tokens]
    return tokens

"""
Starting point : tokens
"""
tokens = tokenize_word_text(text1)

"""
Converting all letters to lower or upper case (common : lower case)
"""
def convert_letters(tokens, style='lower'):
    if style == 'lower':
        tokens = [token.lower() for token in tokens]
    else:
        tokens = [token.upper() for token in tokens]
    return tokens
tokens = convert_letters(tokens)

"""
Remove blancs
"""
def remove_blanc(tokens):
    tokens = [token.strip() for token in tokens]
    return tokens
tokens = remove_blanc(tokens)

def remove_before_token(sentence, keep_apostrophe=False):
    sentence = sentence.strip()
    if keep_apostrophe:
        PATTERN = '[?|$|&|*|%|@|(|)|~]'
        filtered_sentence = re.sub(PATTERN, ' ', sentence)
    else:
        PATTERN = '[^a-zA-Z0-9]'
        filtered_sentence = re.sub(PATTERN, ' ', sentence)
    return filtered_sentence
remove_before_token(text1)

def remove_after_token(tokens):
    pattern = re.compile('[{}]'.format(re.escape(string.punctuation)))
    filtered_tokens = filter(None, [pattern.sub('', token) for token in tokens])
    filtered_text = ' '.join(filtered_tokens)
    return filtered_text
remove_special_characters(tokens)

"""
Expanding contraction 
"""
CONTRACTION_MAP = {"ain't": 'is not', "aren't": 'are not', "can't": 'cannot', "can't've": 'cannot have', "'cause": 'because', "could've": 'could have', "couldn't": 'could not', "couldn't've": 'could not have', "didn't": 'did not', "doesn't": 'does not', "don't": 'do not', "hadn't": 'had not', "hadn't've": 'had not have', "hasn't": 'has not', "haven't": 'have not', "he'd": 'he would', "he'd've": 'he would have', "he'll": 'he will', "he'll've": 'he he will have', "he's": 'he is', "how'd": 'how did', "how'd'y": 'how do you', "how'll": 'how will', "how's": 'how is', "I'd": 'I would', "I'd've": 'I would have', "I'll": 'I will', "I'll've": 'I will have', "I'm": 'I am', "I've": 'I have', "i'd": 'i would', "i'd've": 'i would have', "i'll": 'i will', "i'll've": 'i will have', "i'm": 'i am', "i've": 'i have', "isn't": 'is not', "it'd": 'it would', "it'd've": 'it would have', "it'll": 'it will', "it'll've": 'it will have', "it's": 'it is', "let's": 'let us', "ma'am": 'madam', "mayn't": 'may not', "might've": 'might have', "mightn't": 'might not', "mightn't've": 'might not have', "must've": 'must have', "mustn't": 'must not', "mustn't've": 'must not have', "needn't": 'need not', "needn't've": 'need not have', "o'clock": 'of the clock', "oughtn't": 'ought not', "oughtn't've": 'ought not have', "shan't": 'shall not', "sha'n't": 'shall not', "shan't've": 'shall not have', "she'd": 'she would', "she'd've": 'she would have', "she'll": 'she will', "she'll've": 'she will have', "she's": 'she is', "should've": 'should have', "shouldn't": 'should not', "shouldn't've": 'should not have', "so've": 'so have', "so's": 'so as', "this's": 'this is', "that'd": 'that would', "that'd've": 'that would have', "that's": 'that is', "there'd": 'there would', "there'd've": 'there would have', "there's": 'there is', "they'd": 'they would', "they'd've": 'they would have', "they'll": 'they will', "they'll've": 'they will have', "they're": 'they are', "they've": 'they have', "to've": 'to have', "wasn't": 'was not', "we'd": 'we would', "we'd've": 'we would have', "we'll": 'we will', "we'll've": 'we will have', "we're": 'we are', "we've": 'we have', "weren't": 'were not', "what'll": 'what will', "what'll've": 'what will have', "what're": 'what are', "what's": 'what is', "what've": 'what have', "when's": 'when is', "when've": 'when have', "where'd": 'where did', "where's": 'where is', "where've": 'where have', "who'll": 'who will', "who'll've": 'who will have', "who's": 'who is', "who've": 'who have', "why's": 'why is', "why've": 'why have', "will've": 'will have', "won't": 'will not', "won't've": 'will not have', "would've": 'would have', "wouldn't": 'would not', "wouldn't've": 'would not have', "y'all": 'you all', "y'all'd": 'you all would', "y'all'd've": 'you all would have', "y'all're": 'you all are', "y'all've": 'you all have', "you'd": 'you would', "you'd've": 'you would have', "you'll": 'you will', "you'll've": 'you will have', "you're": 'you are', "you've": 'you have'}

def expand_contractions(sentence, contraction_mapping):
    contractions_pattern = re.compile('({})'.format('|'.join(contraction_mapping.keys())), flags=re.IGNORECASE | re.DOTALL)
    def expand_match(contraction):
        match = contraction.group(0)
        first_char = match[0]
        expanded_contraction = contraction_mapping.get(match) if contraction_mapping.get(match) else contraction_mapping.get(match.lower())
        expanded_contraction = first_char + expanded_contraction[1:]
        return expanded_contraction
    expanded_sentence = contractions_pattern.sub(expand_match, sentence)
    return expanded_sentence
expanded_corpus = [expand_contractions(txt, CONTRACTION_MAP) for txt in sent_tokenize(text1)]
print('Text before expanding contraction : \n ', text1)
print('\n Text after expanding contraction : \n ', expanded_corpus)