topoindex 0.1.0

A Python library for computing topological indices from SMILES using NetworkX

🧠 TopoIndex

TopoIndex is a Python library for computing topological indices of molecular and graph structures using NetworkX. It supports input via SMILES strings and is designed for mathematical chemistry, cheminformatics, and graph theory applications.

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📦 Features

• ✅ Wiener Index
• ✅ Zagreb Indices (First & Second)
• ✅ Hyper-Wiener Index
• ✅ Randic Index
• ✅ Balaban Index
• ✅ Eccentric Connectivity Index
• 📘 More indices coming soon!

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🚀 Installation

Once released on PyPI:

pip install topoindex

For now (manual installation):

git clone https://github.com/YOUR_USERNAME/topoindex.git
cd topoindex
pip install .

⚠️ Requires networkx. RDKit must be installed separately via Conda:

conda install -c rdkit rdkit

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🧪 Example Usage

from topoindex.indices.wiener import wiener_index
from topoindex.indices.zagreb import first_zagreb_index, second_zagreb_index
from topoindex.indices.hyper_wiener import hyper_wiener_index
from topoindex.indices.randic import randic_index
from topoindex.indices.balaban import balaban_index
from topoindex.indices.eccentric_connectivity import eccentric_connectivity_index

smiles = "CCO"  # Ethanol

print("Wiener:", wiener_index(smiles))
print("Zagreb-1:", first_zagreb_index(smiles))
print("Zagreb-2:", second_zagreb_index(smiles))
print("Hyper-Wiener:", hyper_wiener_index(smiles))
print("Randic:", randic_index(smiles))
print("Balaban:", balaban_index(smiles))
print("Eccentric Connectivity:", eccentric_connectivity_index(smiles))

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🧠 What are Topological Indices?

Topological indices are numerical descriptors of graph structure widely used in:

• Molecular property prediction
• Graph similarity comparison
• Cheminformatics and QSPR/QSAR
• Network analysis

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📁 Project Structure

topoindex/
├── indices/           # Core index computations
├── utils/             # SMILES to graph conversion
├── tests/             # Unit tests (Pytest)
├── examples/          # Example usage scripts

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📝 License

Licensed under the MIT License.

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🤝 Contributing

Pull requests are welcome. If you'd like to contribute a new index or optimization, please open an issue first.

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👨‍💻 Author

Developed by Avinash Mallick.