With the help of
NLTK tokenize.regexp() module, we are able to extract the tokens from string by using regular expression with
Return : Return array of tokens using regular expression
Example #1 :
In this example we are using
RegexpTokenizer() method to extract the stream of tokens with the help of regular expressions.
[‘I’, ‘love’, ‘Python’]
Example #2 :
[‘Geeks’, ‘for’, ‘Geeks’]
- Python NLTK | nltk.tokenize.TabTokenizer()
- Python NLTK | nltk.tokenize.SpaceTokenizer()
- Python NLTK | nltk.tokenize.StanfordTokenizer()
- Python NLTK | nltk.tokenizer.word_tokenize()
- Python NLTK | nltk.TweetTokenizer()
- Python NLTK | nltk.tokenize.mwe()
- Python NLTK | nltk.WhitespaceTokenizer
- Python NLTK | nltk.tokenize.LineTokenizer
- Python NLTK | nltk.tokenize.SExprTokenizer()
- Python | NLTK nltk.tokenize.ConditionalFreqDist()
- Tokenize text using NLTK in python
- Removing stop words with NLTK in Python
- How to get synonyms/antonyms from NLTK WordNet in Python?
- Part of Speech Tagging with Stop words using NLTK in python
- Python | Stemming words with NLTK
- Python | Lemmatization with NLTK
- Python | Gender Identification by name using NLTK
- Python NLTK | tokenize.WordPunctTokenizer()
- Creating a Basic hardcoded ChatBot using Python-NLTK
- Important differences between Python 2.x and Python 3.x with examples
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.