textcleaner2305 1.0.0

A simple text cleaning library that converts text to clean word arrays

Your README.md for TextCleaner is off to a solid start—clear, well-organized, and functional. Below is an improved version with a few refinements to grammar, formatting, clarity, and overall polish. I also incorporated your authorship at the end, as you mentioned “my name Emmanuel.”

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TextCleaner

A simple Python library for cleaning text and converting it into arrays of clean, lowercase words.

Installation

Install via pip:

pip install textcleaner

Or install from source:

git clone https://github.com/yourusername/textcleaner.git
cd textcleaner
pip install -e .

Usage

from textcleaner import clean

# Basic usage
result = clean("Hello, WORLD!! This is an example.")
print(result)
# Output: ['hello', 'world', 'this', 'is', 'an', 'example']

# More examples
print(clean("Python is AWESOME!!! Let's code..."))
# Output: ['python', 'is', 'awesome', 'let', 's', 'code']

print(clean("Remove @#$% special characters & numbers 123"))
# Output: ['remove', 'special', 'characters', 'numbers', '123']

Features

• Converts text to lowercase
• Removes punctuation and special characters
• Tokenizes text into words
• Handles numbers as valid tokens
• Manages empty strings and edge cases gracefully
• Returns a clean list of words

API Reference

clean(text)

Cleans input text and returns a list of lowercase words.

Parameters:

• text (str): The input string to clean

Returns:

• list: A list of cleaned, lowercase words

Example:

clean("Hello, World!")  
# Returns: ['hello', 'world']

Contributing

Contributions are welcome! Here's how to get started:

1. Fork the repository

2. Create a feature branch:

   git checkout -b feature/amazing-feature
   

3. Commit your changes:

   git commit -m 'Add some amazing feature'
   

4. Push to your branch:

   git push origin feature/amazing-feature
   

5. Open a Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Changelog

Version 1.0.0

• Initial release
• Basic text cleaning functionality
• Word tokenization
• Punctuation and special character removal

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Author: Emmanuel