proces is a Python library (version 0.1.7) designed for efficient text preprocessing. It offers a flexible `TextCleaner` class with various options to clean, normalize, and prepare raw text data for natural language processing (NLP) tasks, including removing HTML, URLs, mentions, hashtags, numbers, punctuation, and handling case conversion and whitespace. As a 0.x.x release, its API might evolve.
pip install procesVerified import paths — ran on the pinned version, not inferred.
Demonstrates basic and advanced usage of the TextCleaner class to preprocess a sample string, applying various cleaning rules and replacement tokens.
Pin your project's dependency to a specific patch version (e.g., 'proces==0.1.7') or be prepared to adapt code when upgrading to new minor versions.
Always use specific imports like `from proces import TextCleaner` to avoid namespace collisions and clarify intent. Double-check your `pip install` command to ensure you're installing 'proces' from PyPI (text preprocessing) and not a similarly named package.
To enable stopwords removal, you must provide your own list of stopwords (e.g., `cleaner = TextCleaner(remove_stopwords=True, stopwords_list=['a', 'the', 'is'])`) or download them via `nltk` and pass them in.