chanda 0.1.1

Sanskrit meter identification and analysis library

Chanda

Sanskrit Meter Identification and Analysis Library

A comprehensive Python library for identifying and analyzing Sanskrit poetic meters. Supports 200+ meters including Sama-vṛtta, Ardhasama-vṛtta, Viṣama-vṛtta, and Mātrā-vṛtta.

• Chandojñānam Web Interface: https://sanskrit.iitk.ac.in/jnanasangraha/chanda/
• Chandojñānam Web Interface Source Code: https://github.com/hrishikeshrt/chandojnanam/

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Features

• 200+ Meter Database: Comprehensive coverage of Sanskrit meters

  • Sama-vṛtta (meters with identical padas)
  • Ardhasama-vṛtta & Viṣama-vṛtta (meters with varying padas)
  • Mātrā-vṛtta (matra-based meters like Āryā, Gīti)

• Smart Identification:

  • Exact pattern matching
  • Fuzzy matching with syllable-level correction suggestions
  • Verse-level analysis (4-line grouping)

• Multi-Script Support: 15+ scripts and transliteration schemes

  • Devanagari, IAST, ITRANS, Harvard-Kyoto, SLP1, WX, Velthuis, and more

• Detailed Analysis:

  • Syllable segmentation
  • Laghu-Guru (light-heavy) marking
  • Gana notation conversion
  • Mātrā (morae) counting
  • Jāti (classification) identification

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Installation

From PyPI

pip install chanda

From Source

git clone https://github.com/hrishikeshrt/chanda.git
cd chanda
pip install -e .

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Quick Start

Python API

from chanda import identify_meter

# Simple example - Anuṣṭubh (most common meter)
text = "को न्वस्मिन् साम्प्रतं लोके गुणवान् कश्च वीर्यवान्"
result = identify_meter(text)
print(result['display_chanda'])  # Output: अनुष्टुभ् (पाद 1-2)

# Gana-based meter example - shows gana pattern
text = "नमस्ते सदा वत्सले मातृभूमे"
result = identify_meter(text)
print(result['display_chanda'])  # Output: भुजङ्गप्रयात
print(result['gana'])            # Output: यययय

Command-Line Interface

# Analyze a single line
chanda "को न्वस्मिन् साम्प्रतं लोके गुणवान् कश्च वीर्यवान्"

# Analyze a file
chanda -f bhagavad_gita.txt --verse --summary

# Interactive mode
chanda -i

# Get help
chanda --help

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Detailed Usage

Single Line Analysis

from chanda import identify_meter

text = "रामो राजमणिः सदा विजयते रामं रमेशं भजे"
result = identify_meter(text, fuzzy=True)

if result['found']:
    print(f"Meter: {result['display_chanda']}")
    print(f"Syllables: {result['syllables']}")
    print(f"Pattern (LG): {' '.join(result['lg'])}")
    print(f"Gana: {result['gana']}")
    print(f"Syllable count: {result['length']}")
    print(f"Mātrā count: {result['matra']}")
else:
    # Check fuzzy matches
    if result['fuzzy']:
        best_match = result['fuzzy'][0]
        print(f"Closest meter: {best_match['display_chanda']}")
        print(f"Similarity: {best_match['similarity']:.2%}")

Verse Analysis

from chanda import analyze_text

verse = """को न्वस्मिन् साम्प्रतं लोके गुणवान् कश्च वीर्यवान्।
धर्मज्ञश्च कृतज्ञश्च सत्यवाक्यो दृढव्रतः॥"""

results = analyze_text(verse, verse_mode=True, fuzzy=True)

# Access verse-level results
for verse in results['result']['verse']:
    best_meters, score = verse['chanda']
    print(f"Verse meter: {' / '.join(best_meters)} (score: {score})")

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Documentation

Full documentation is available at chanda.readthedocs.io

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Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Run the test suite
5. Submit a pull request

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Citation

If you use Chandojñānam in your research, please cite:

@inproceedings{terdalkar2023chandojnanam,
    title = "Chandojnanam: A {S}anskrit Meter Identification and Utilization System",
    author = "Terdalkar, Hrishikesh  and
      Bhattacharya, Arnab",
    booktitle = "Proceedings of the Computational {S}anskrit {\&} Digital Humanities: Selected papers presented at the 18th World {S}anskrit Conference",
    month = jan,
    year = "2023",
    address = "Canberra, Australia (Online mode)",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.wsc-csdh.8",
    pages = "113--127",
}

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License

GNU Affero General Public License v3.0 - see LICENSE file for details.

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Acknowledgments

• Based on traditional chandaśāstra texts
• Meter definitions compiled from various classical sources
• Built on the excellent sanskrit-text and indic-transliteration libraries

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Links

• PyPI: https://pypi.org/project/chanda/
• GitHub: https://github.com/hrishikeshrt/chanda
• Documentation: https://chanda.readthedocs.io
• Issues: https://github.com/hrishikeshrt/chanda/issues