SafwaText

SafwaText is a Python package for cleaning, normalizing, and stemming Arabic text effortlessly. Whether you're working on NLP projects or need to preprocess Arabic text, SafwaText simplifies the process.

Features

• Remove Tashkeel (diacritics): Simplifies text by removing diacritical marks.
• Normalize Arabic text: Converts text into a consistent format.
• Filter Non-Arabic Characters: Removes any characters not part of the Arabic script, including numbers, punctuation, and symbols.
• Remove Arabic Articles: Strips common Arabic definite articles.
• Remove Arabic Prefixes: Removes common prefixes from words.
• Remove Arabic Suffixes: Removes common suffixes from words.
• Arabic Stemming: Applies a light stemming pipeline to Arabic words, including normalization, prefix/suffix removal, and article stripping.
• Remove Stopwords: Filters out common Arabic stopwords

Installation

Install the package directly from PyPI using pip: ```bash pip install safwaText

Usage

```bash
from safwaText.cleaner import remove_tashkeel, normalize_text, remove_non_arabic
from safwaText.stemmer import arabic_stemmer
from safwaText.stopwords import remove_stopwords

# Clean and normalize text
input = "يذهب مُحَمَّدٌ للمَدْرَسَةِ كل صباح"
cleaned_text = remove_tashkeel(input) 
normalized_text = normalize_text(cleaned_text) 
filtered_text = remove_non_arabic(normalized_text) 

# Apply light stemming
stemmed_text = arabic_stemmer(filtered_text)  

# Remove stopwords
final_output = remove_stopwords(stemmed_text)

print(final_output)  # Output: "ذهب محمد مدرس صباح"
```

Contributing

Contributions are welcome! If you'd like to improve this extension:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-name

3. Commit your changes and push to your branch :

   git commit -m "Add feature: feature-name"
   git push origin feature-name

4. Open a pull request.

License

SafwaText is licensed under the Apache-2.0 license.