nahiarhdNLP 1.0.1

Advanced Indonesian Natural Language Processing Library

nahiarhdNLP

nahiarhdNLP is an advanced Python library for Indonesian Natural Language Processing (NLP), providing easy-to-use tools for text preprocessing, normalization, tokenization, stemming, spell correction, and customizable pipelines.

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Installation

pip install nahiarhdNLP

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Features

• Preprocessing: Clean text from HTML, URLs, stopwords, slang, emoji, mentions, hashtags, numbers, punctuation, extra spaces, and special characters.
• Tokenization: Split sentences into tokens/words.
• Stemming: Convert words to their root form (using Sastrawi).
• Spell Correction: Automatic spelling correction.
• Pipeline: Chain multiple preprocessing functions easily.
• Normalization: Replace slang, emoji, and informal words with formal equivalents.

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Quick Usage Example

Basic Preprocessing

from nahiarhdNLP import preprocessing

text = "Halooo emg siapa yg nanya? 😀 <a href='#'>link</a> @user #trending 123"
cleaned = preprocessing.cleaning.text_cleaner.clean_text(text)
print(cleaned)

Custom Preprocessing Pipeline

from nahiarhdNLP.preprocessing import (
    pipeline, remove_html, remove_url, remove_mentions, remove_hashtags,
    remove_numbers, replace_word_elongation, emoji_to_words, replace_slang,
    remove_stopwords, remove_punctuation, remove_extra_spaces, to_lowercase
)

custom_pipe = pipeline([
    remove_html, remove_url, remove_mentions, remove_hashtags, remove_numbers,
    replace_word_elongation, emoji_to_words, replace_slang, remove_stopwords,
    remove_punctuation, remove_extra_spaces, to_lowercase
])

result = custom_pipe("Halooo emg siapa yg nanya? 😀 <a href='#'>link</a> @user #trending 123")
print(result)

Spell Correction

from nahiarhdNLP.preprocessing import correct_spelling
print(correct_spelling("sya suka mkn nasi"))  # "saya suka makan nasi"

Stemming

from nahiarhdNLP.preprocessing import stem_text
print(stem_text("bermain-main dengan senang"))  # "main dengan senang"

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Requirements

• Python 3.7+
• pandas, fsspec, huggingface_hub, sastrawi, datasets, rich

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Testing

pytest tests/

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Directory Structure

nahiarhdNLP/
├── main.py
├── requirements.txt
├── README.md
├── src/
│   ├── preprocessing/
│   ├── mydatasets/
└── tests/

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Contribution

Contributions are welcome! Please fork the repository, create a new branch, and submit a pull request.

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License

MIT License

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Acknowledgments

• Stopwords dataset from HuggingFace
• Emoji dataset from HuggingFace
• Slang dataset from HuggingFace
• Sastrawi for Indonesian stemming