Another feature of the "Tokenize" extension is its handling of special characters. Special characters, such as punctuation marks and symbols, can sometimes interfere with text analysis tasks. The extension removes these special characters from the text, ensuring that your subsequent operations, such as tokenization or word frequency analysis, are not affected by them.
Additionally, the extension takes care of empty strings. Empty strings are strings that contain no characters or only whitespace. These empty strings can arise from various sources, such as accidental extra spaces or empty lines. The "Tokenize" extension filters out these empty strings, ensuring that they do not interfere with the analysis or processing of your text.
By combining these features, the "Tokenize" extension empowers you to preprocess and prepare your text data for various tasks, such as natural language processing, machine learning, or data analysis. It saves you time and effort by automating the handling of contractions, special characters, and empty strings, allowing you to focus on the core aspects of your text analysis workflow.
With the "Tokenize" extension installed, you can activate it through the provided command or by assigning a keyboard shortcut. Once activated, the extension operates on the active text editor in Visual Studio Code, processing the text and displaying the results in an information message and an output channel. The information message shows the processed text as an array of tokens, while the output channel provides a more detailed view of the processed text.
If you have any requirements or dependencies, add a section describing those and how to install and configure them.
This extension contributes the following settings:
This is the first release
For more information