text_preprocessor_v1 0.1.0

An advance text pre-processor

Text Preprocessor

📝 Overview

Text Preprocessor is a powerful Python library designed for comprehensive text preprocessing tasks, particularly useful for natural language processing (NLP), sentiment analysis, and text classification projects.

✨ Features

• 🧹 Remove HTML tags
• 🛑 Remove stopwords
• 🔤 Lemmatization
• 🧼 Remove special characters
• 🔍 Remove duplicates
• 📏 Remove short texts
• 📊 Basic outlier detection

🚀 Installation

Using pip

pip install sentence-preprocessor

Using Poetry

poetry add sentence-preprocessor

💻 Usage

As a Python Module

from text_preprocessor.preprocessor import TextPreprocessor

# Preprocess a CSV file
preprocessor = TextPreprocessor('input.csv', 'output.csv')
preprocessed_df = preprocessor.preprocess()
preprocessor.save_preprocessed_data()

Command Line Interface

# Basic usage
text_preprocessor input.csv [output.csv]

🛠 Development Setup

Prerequisites

• Python 3.12+
• Poetry

Installation Steps

# Install Poetry (if not already installed)
pip install poetry

# Install dependencies
make install

# Activate virtual environment
make shell

🧪 Running Tests

# Run tests
make test

# Run tests with coverage
make test-cov

📦 Build and Publish

# Build distribution
make build

# Publish to PyPI
make publish

🔍 Preprocessing Pipeline

The preprocessor applies the following transformations:

1. Remove HTML tags
2. Convert to lowercase
3. Remove special characters
4. Remove stopwords
5. Lemmatize text
6. Remove single characters
7. Remove texts with fewer than 3 words
8. Remove duplicates
9. Basic outlier detection

📝 Configuration

You can customize preprocessing by modifying the preprocess() method parameters or extending the TextPreprocessingUtils class.

🤝 Contributing

Contributions are welcome! If you'd like to contribute to this project, please open an issue or submit a pull request.

📜 License

Distributed under the MIT License. See LICENSE for more information.

🛡 Disclaimer

This library is provided as-is. Always review and test thoroughly before using in production environments.

📞 Contact

Your Name - [e-mail]

Project Link:

🙌 Acknowledgements

• NLTK
• Pandas
• BeautifulSoup

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