Tokenizing With NLTK
Use a real tokenizer for messy text.
Tokenizing With NLTK is a free NLP Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the NLP Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
A Real Tokenizer
Time to upgrade. NLTK is a classic Python library that gives you a proper tokenizer for messy, real-world text. 🛠️
Install and Import
You install it once with pip, then import it in your script. From there, NLTK's word_tokenize is one function call away.
from nltk import word_tokenizeOne Time Setup
NLTK ships extra data separately. Before tokenizing, you download the punkt model once, and then it just works.
import nltk
nltk.download("punkt")Tokenize a Sentence
Now pass any string to word_tokenize. It returns a clean list of word and punctuation tokens, ready to count or filter.
word_tokenize("I love cats!")
# ['I', 'love', 'cats', '!']Punctuation Split Out
Notice the win: the exclamation mark is now its own token. So cats and cats! finally count as the same word.
Contractions Handled
NLTK is smart about contractions. It splits don't into do and n't, keeping the hidden negation visible to your code.
word_tokenize("don't")
# ['do', "n't"]Why It Is Smarter
Under the hood, NLTK follows linguistic rules learned from real text. That is why it beats a plain whitespace split every time.
Sentences Too
NLTK also segments sentences. Pair sent_tokenize with word_tokenize to split a document into sentences, then each into words.
from nltk import sent_tokenize
sent_tokenize("Hi there. Bye now.")Combine the Two
A common pattern loops over sentences and tokenizes each. This gives you a tidy list of lists, one token list per sentence.
Not the Only Option
NLTK is great for learning, but it is not alone. Libraries like spaCy offer faster tokenizers you will meet later on.
From Raw Text to Tokens
You now have the full move: raw text in, a clean token list out. This is the foundation every later NLP step builds on.
Quick Check
How does NLTK improve on naive splitting?
Recap
You used NLTK to tokenize real text: install, download punkt, then call word_tokenize. It splits punctuation and contractions cleanly for you.
Frequently asked questions
Is the “Tokenizing With NLTK” lesson free?
Yes — the full text of “Tokenizing With NLTK” is free to read here on the web, and the NLP Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the NLP Academy course, upgrade to CoddyKit PRO.
What will I learn in “Tokenizing With NLTK”?
Use a real tokenizer for messy text. You practise NLP Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start NLP Academy?
No prior experience is required. NLP Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Tokenizing With NLTK” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this NLP Academy lesson?
Yes. Every NLP Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.