Python NLTK | nltk.tokenize.TabTokenizer()

The nltk.tokenize.TabTokenizer() is a class in the Natural Language Toolkit (NLTK) library for Python that is used for tokenizing text based on tab spaces. This tokenizer can be used to convert text data into individual tokens that can be analyzed and processed further.

Usage

To use the TabTokenizer() class, we need to first import the nltk module and create an object of the TabTokenizer() class. We can then use this object to tokenize text based on tab spaces.

import nltk
from nltk.tokenize import TabTokenizer

tokenizer = TabTokenizer()
text = "This is\ta sample\ttext with\ttabs."
tokens = tokenizer.tokenize(text)
print(tokens)

Here, we first import the nltk module and the TabTokenizer() class from the nltk.tokenize module. We then create an object of the TabTokenizer() class and use it to tokenize the sample text that contains tabs. Finally, we print the tokens that are generated by the tokenizer.

The output of the above code snippet will be as follows:

['This is', 'a sample', 'text with', 'tabs.']

This shows that the TabTokenizer() has successfully tokenized the text based on tab spaces.

Conclusion

The TabTokenizer() is a useful tokenizer class in the nltk library for tokenizing text based on tab spaces. It is easy to use and can be a useful tool in natural language processing tasks that involve text tokenization.