PyMyaNLP

A Python library for Myanmar (Burmese) language processing and natural language processing tasks.

မြန်မာဗျည်းအက္ခရာအခြေခံသော ဘာသာစကားများအတွက် NLP အရာ၌ အထွေထွေသုံးစွဲနိုင်ရန်ရည်ရွယ်၍ ရေးသားဖြစ်ခဲ့သည်။

Installation

pip install pymyanlp

Quick Start

import pymyanlp

# Word segmentation
segments = pymyanlp.segment_word("ရေပုံမှန်သောက်ပါ") # ['ရေ', 'ပုံမှန်', 'သောက်', 'ပါ']

# Part-of-speech tagging
tags = pymyanlp.pos_tag("မြန်မာ ဘာသာ") # [('မြန်မာ', <PartOfSpeech.Noun: 'n'>), ('ဘာသာ', <PartOfSpeech.Noun: 'n'>)]

# Text detection and validation
pymyanlp.is_burmese("မြန်မာ ဘာသာ")  # True

pymyanlp.contains_burmese("Hello မြန်မာ")  # True

pymyanlp.get_burmese_script("မြန်မာ")  # burmese
pymyanlp.get_burmese_script("တမၟာ")  # mon
pymyanlp.get_burmese_script("ၡးခွ့မဲၢ်")  # sgaw_karen
pymyanlp.get_burmese_script("ႁိူဝ်းမိၼ်")  # shan

# Number transliteration
pymyanlp.transliterate_numbers("2024")  # ၂၀၂၄

# Text processing pipeline
processed = pymyanlp.apply_written_suite("Hello 2024, မြန်မာ!") # Normalized text

Features

Feature	Description
Word Segmentation	Multiple models (Viterbi, CRF-based)
POS Tagging	Part-of-speech tagging for Myanmar text
Text Normalization	Clean and standardize text
Transliteration	Convert English to Myanmar
Script Detection	Identify Burmese text and script variants
Punctuation Handling	Remove or process punctuation
Spacing Normalization	Handle mixed script spacing
Text Style Detection	Identify different Myanmar text styles
Sentiment Analysis*	Score-based sentiment classification
Grammar Analysis*	Myanmar particle and grammar detection
Spell Checking*	Basic spell checking functionality

*means not yet implemented

Constants and Enums

# POS tag enums
pymyanlp.PartOfSpeech.Noun.value  # "n"

# Built-in constants
pymyanlp.NUMBER_MAP  # {'0': '၀', '1': '၁', ...}
pymyanlp.PUNCTUATION  # ['။', '၊', ',', '.', ...]

Testing

Run the test suite:

# Run all tests
pytest tests/

Documentation

• API Reference: See module docstrings for detailed API documentation
• Test Examples: Check tests/ directory for usage examples

Project Structure

pymyanlp/
├── text/           # Text processing modules
├── analysis/       # Analysis and NLP modules
├── utils/          # Utility functions
├── resources/      # Language resources
└── lib/            # Core algorithms and models

License

MIT License - see LICENSE.txt for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Run the test suite
5. Submit a pull request

For bug reports and feature requests, please use the GitHub issue tracker.