topolib 0.9.1

A compact Python library for modeling, analyzing, and visualizing optical network topologies.

Topolib 🚀

Topolib is a compact, modular Python library for modeling, analyzing, and visualizing optical network topologies.
Goal: Provide researchers and engineers with a simple, extensible toolkit for working with nodes, links, metrics, and map-based visualizations.

🌐 Model | 📊 Analyze | 🗺️ Visualize | 🧩 Extend

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📂 Examples

Explore ready-to-run usage examples in the examples/ folder!

• Show topology on a map 🗺️
• Show default topology in map 🗺️
• Export topology as PNG 🖼️
• Export topology to CSV and JSON 📄
• Export topology and k-shortest paths for FlexNetSim 🔀
• Generate traffic demand matrices 📊

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🧭 Overview

Topolib is organized into four main modules:

• 🧱 Elements: Node, Link — basic building blocks
• 🕸️ Topology: Topology, Path — manage nodes, links, paths, and adjacency
• 📈 Analysis: Metrics, TrafficMatrix — compute node degree, link stats, connection matrices, and traffic demand matrices
• 🖼️ Visualization: MapView — interactive maps with Folium and PyQt6, clean PNG exports

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✨ Features

• Modular, extensible design
• Easy-to-use classes for nodes, links, and paths
• Built-in metrics and analysis helpers
• Traffic demand matrix generation with three models (gravitational, DC/IXP, distribution probability)
• Returns NumPy arrays for efficient mathematical operations
• Interactive map visualization with Folium and PyQt6
• Clean PNG export without external dependencies (no Selenium required)
• Resource caching for faster map rendering
• JSON import/export and interoperability
• Ready for Sphinx, Read the Docs, and PyPI

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⚡ Quickstart

python -m venv .venv
source .venv/bin/activate
pip install -U pip
pip install topolib

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📚 Documentation

Full documentation: https://topolib.readthedocs.io/

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📝 Basic usage

Creating a topology

from topolib.elements.node import Node
from topolib.topology.topology import Topology

n1 = Node(1, 'A', 10.0, 20.0)
n2 = Node(2, 'B', 11.0, 21.0)
topo = Topology(nodes=[n1, n2])
# Add links, compute metrics, visualize, etc.

Generating traffic matrices

from topolib.topology import Topology
from topolib.analysis import TrafficMatrix

# Load a topology
topo = Topology.load_default_topology("Germany-14nodes")

# Generate traffic matrix using gravitational model
matrix = TrafficMatrix.gravitational(topo, rate=0.015)
# Returns NumPy array: matrix[i, j] = traffic from node i to j (Gbps)

# Export to CSV
TrafficMatrix.to_csv(matrix, topo, "traffic_matrix.csv")

# Export to JSON (list of demands with src, dst, required fields)
TrafficMatrix.to_json(matrix, topo, "traffic_matrix.json")

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🛠️ Development

See CONTRIBUTING.md for development guidelines, commit message rules, and pre-commit setup.

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📄 License

MIT — see LICENSE for details.