Getting Started with Graphology

Key Points Graphology is a JavaScript library for creating and manipulating graph data structures, supporting various graph types like directed, undirected, or mixed, with or without self-loops and parallel edges. It seems likely that you can install it via npm with npm install graphology, and it includes a standard library for additional graph algorithms. The evidence leans toward it being used with sigma.js for interactive graph rendering, and it supports TypeScript with graphology-types. Getting Started with Graphology What is Graphology? Graphology is a robust and versatile library for working with graphs in JavaScript and TypeScript. It allows you to create graphs that can be directed, undirected, or mixed, and supports features like self-loops and parallel edges. It’s often used with sigma.js for visualizing graphs interactively, making it great for network analysis or data visualization projects. Installation To get started, install Graphology using npm: npm install graphology For additional graph algorithms, install the standard library: npm install graphology-library If you’re using TypeScript, you might need to install type declarations: npm install graphology-types You can also use standalone builds from the releases page on GitHub (releases) if you prefer script tags. Creating and Using a Graph Here’s how to create a basic graph and add nodes and edges: import Graph from 'graphology'; const graph = new Graph(); graph.addNode('node1', { label: 'Node One', color: 'blue' }); graph.addNode('node2', { label: 'Node Two', color: 'red' }); graph.addEdge('node1', 'node2', { weight: 5 }); You can check the number of nodes and edges: console.log('Nodes:', graph.order); // Number of nodes console.log('Edges:', graph.size); // Number of edges Graphology also lets you set and get attributes for nodes and edges, like size or color, and traverse the graph to find connected nodes. Unexpected Detail: Standard Library Features Beyond the basics, Graphology’s standard library offers advanced features like graph density calculations, layout algorithms (e.g., ForceAtlas2), and community detection, which might be useful for more complex projects. For example, calculate density: import * as metrics from 'graphology-library/metrics'; const density = metrics.graph.density(graph); Resources for Further Learning For more details, check the official website (Graphology) and the standard library documentation (standard-library). Comprehensive Survey Note on Using Graphology This survey note provides an in-depth exploration of Graphology, a robust and multipurpose Graph object for JavaScript and TypeScript, designed for creating and manipulating graph data structures. It covers installation, usage, and advanced features, drawing from official sources and examples to ensure a thorough understanding. The note is structured to mimic a professional article, offering detailed guidance for developers at all levels. Introduction to Graphology Graphology is a versatile library aimed at supporting various kinds of graphs under a unified interface. It can handle directed, undirected, or mixed graphs, with options for self-loops and parallel edges. This flexibility makes it suitable for a wide range of applications, from network analysis to interactive visualizations. Notably, it is used as the data backend for sigma.js, a WebGL-based graph renderer, enhancing its utility for browser-based interactive applications. The library also includes a comprehensive standard library, offering graph theory algorithms, utilities, generators, layouts, and traversals. This makes Graphology not just a data structure but a full ecosystem for graph-related tasks. Additionally, Graphology graphs emit various events, which are ideal for building dynamic, interactive renderers. Installation and Setup To begin using Graphology, installation is straightforward via npm. The primary command is: npm install graphology For access to additional algorithms and utilities, install the standard library: npm install graphology-library For TypeScript users, ensure compatibility by installing type declarations if needed: npm install graphology-types For projects that cannot use npm, standalone builds are available in the repository’s releases (releases). These can be loaded via script tags, with graphology.min.js exposing the graphology global and graphology-library.min.js exposing graphologyLibrary. Creating and Managing Graphs Instantiating a Graph To create a new graph, import the Graph class and instantiate it: import Graph from 'graphology'; const graph = new Graph(); This creates a default undirected, simple graph. You can specify options like type (e.g., 'directed', 'undirected', 'mixed') and allowSelfLoops when creating the graph for more control. Adding Nodes and Edges Node

Mar 17, 2025 - 19:44

Key Points

Graphology is a JavaScript library for creating and manipulating graph data structures, supporting various graph types like directed, undirected, or mixed, with or without self-loops and parallel edges.
It seems likely that you can install it via npm with npm install graphology, and it includes a standard library for additional graph algorithms.
The evidence leans toward it being used with sigma.js for interactive graph rendering, and it supports TypeScript with graphology-types.

Getting Started with Graphology

What is Graphology?

Graphology is a robust and versatile library for working with graphs in JavaScript and TypeScript. It allows you to create graphs that can be directed, undirected, or mixed, and supports features like self-loops and parallel edges. It’s often used with sigma.js for visualizing graphs interactively, making it great for network analysis or data visualization projects.

Installation

To get started, install Graphology using npm:

npm install graphology

For additional graph algorithms, install the standard library:

npm install graphology-library

If you’re using TypeScript, you might need to install type declarations:

npm install graphology-types

You can also use standalone builds from the releases page on GitHub (releases) if you prefer script tags.

Creating and Using a Graph

Here’s how to create a basic graph and add nodes and edges:

import Graph from 'graphology';

const graph = new Graph();
graph.addNode('node1', { label: 'Node One', color: 'blue' });
graph.addNode('node2', { label: 'Node Two', color: 'red' });
graph.addEdge('node1', 'node2', { weight: 5 });

You can check the number of nodes and edges:

console.log('Nodes:', graph.order); // Number of nodes
console.log('Edges:', graph.size); // Number of edges

Graphology also lets you set and get attributes for nodes and edges, like size or color, and traverse the graph to find connected nodes.

Unexpected Detail: Standard Library Features

Beyond the basics, Graphology’s standard library offers advanced features like graph density calculations, layout algorithms (e.g., ForceAtlas2), and community detection, which might be useful for more complex projects. For example, calculate density:

import * as metrics from 'graphology-library/metrics';
const density = metrics.graph.density(graph);

Resources for Further Learning

For more details, check the official website (Graphology) and the standard library documentation (standard-library).

Comprehensive Survey Note on Using Graphology

This survey note provides an in-depth exploration of Graphology, a robust and multipurpose Graph object for JavaScript and TypeScript, designed for creating and manipulating graph data structures. It covers installation, usage, and advanced features, drawing from official sources and examples to ensure a thorough understanding. The note is structured to mimic a professional article, offering detailed guidance for developers at all levels.

Introduction to Graphology

Graphology is a versatile library aimed at supporting various kinds of graphs under a unified interface. It can handle directed, undirected, or mixed graphs, with options for self-loops and parallel edges. This flexibility makes it suitable for a wide range of applications, from network analysis to interactive visualizations. Notably, it is used as the data backend for sigma.js, a WebGL-based graph renderer, enhancing its utility for browser-based interactive applications.

The library also includes a comprehensive standard library, offering graph theory algorithms, utilities, generators, layouts, and traversals. This makes Graphology not just a data structure but a full ecosystem for graph-related tasks. Additionally, Graphology graphs emit various events, which are ideal for building dynamic, interactive renderers.

Installation and Setup

To begin using Graphology, installation is straightforward via npm. The primary command is:

npm install graphology

For access to additional algorithms and utilities, install the standard library:

npm install graphology-library

For TypeScript users, ensure compatibility by installing type declarations if needed:

npm install graphology-types

For projects that cannot use npm, standalone builds are available in the repository’s releases (releases). These can be loaded via script tags, with graphology.min.js exposing the graphology global and graphology-library.min.js exposing graphologyLibrary.

Creating and Managing Graphs

Instantiating a Graph

To create a new graph, import the Graph class and instantiate it:

import Graph from 'graphology';

const graph = new Graph();

This creates a default undirected, simple graph. You can specify options like type (e.g., 'directed', 'undirected', 'mixed') and allowSelfLoops when creating the graph for more control.

Adding Nodes and Edges

Nodes and edges form the backbone of any graph. Add a node with:

graph.addNode('node1'); // Basic node
graph.addNode('node2', { label: 'Node Two', color: 'red', size: 10 }); // Node with attributes

Edges connect nodes, and can also have attributes:

graph.addEdge('node1', 'node2'); // Basic edge
graph.addEdge('node1', 'node2', { weight: 5, color: 'blue' }); // Edge with attributes

Attributes like label, color, and size are commonly used for visualization, especially when integrating with sigma.js.

Accessing Graph Properties

Graphology provides methods to query the graph’s structure. Get the number of nodes and edges:

console.log('Number of nodes:', graph.order);
console.log('Number of edges:', graph.size);

List all nodes and edges:

graph.nodes().forEach(node => console.log(node));
graph.edges().forEach(edge => console.log(edge));

These methods are essential for understanding the graph’s scale and structure.

Working with Node and Edge Attributes

Attributes enhance the graph’s data, allowing for richer representations. Set and get node attributes as follows:

graph.setNodeAttribute('node1', 'size', 10);
const size = graph.getNodeAttribute('node1', 'size');

Similarly, for edges:

graph.setEdgeAttribute('edge_id', 'weight', 3);
const weight = graph.getEdgeAttribute('edge_id', 'weight');

These attributes are crucial for visualizations, where properties like color or size can represent data like node importance or edge strength.

Traversing the Graph

Traversal is key for analyzing graph connectivity. For undirected graphs, use neighbors to find all connected nodes:

const neighbors = graph.neighbors('node1');

For directed graphs, Graphology offers outNeighbors for nodes the given node points to, and inNeighbors for nodes pointing to it:

const outNeighbors = graph.outNeighbors('node1');
const inNeighbors = graph.inNeighbors('node1');

These methods are particularly useful in directed graphs, such as social networks or dependency graphs, where direction matters.

Leveraging the Standard Library

Graphology’s standard library extends its functionality with various packages, each serving specific graph-related tasks. Below is a table summarizing key packages and their purposes, based on official documentation:

Package Name	Description
assertions	Miscellaneous assertions (same nodes, same edges etc.).
bipartite	Bipartite graph helper functions (coloring, projection etc.).
canvas	Canvas rendering routines for graphs.
communities-louvain	Louvain method for community detection.
components	Connected components (strong, weak etc.).
dag	Functions related to directed acyclic graphs (cycle detection, topological sorting etc.).
cores	Various utilities related to k-cores.
generators	Graph generators (random graphs, complete graphs etc.).
gexf	Parsers & writers for the GEXF file format.
graphml	Parsers & writers for the GRAPHML file format.
indices	Various specialized graph indices (neighborhood, louvain etc.)
layout	Basic graph layouts (random, circle etc.).
layout-force	Basic force layout algorithm.
layout-forceatlas2	ForceAtlas2 layout algorithm.
layout-noverlap	Noverlap anti-collision layout algorithm.
metrics	Modularity, density, centrality etc.
operators	Graph unary, binary & cast operators (reverse, union, intersection, conversion etc.)
shortest-path	Shortest path functions (Dijkstra, A* etc.).
simple-path	Simple path related functions (e.g. all paths between source & target)
svg	SVG export for graphs.
traversal	Traversal functions (DFS, BFS, etc.).
utils	Miscellaneous utils used by most of the other modules.

For example, to calculate graph density:

import * as metrics from 'graphology-library/metrics';
const density = metrics.graph.density(graph);

The standard library is accessible via graphology-library, with browser-specific versions available for certain packages like XML parsers and layouts with web workers. For interactive rendering, consider sigma.js (sigma.js).

Handling Events

Graphology graphs emit events, which are useful for building interactive applications. Listen to events like node addition:

graph.on('nodeAdded', (node, attributes) => {
  console.log(`Node ${node} added with attributes:`, attributes);
});

Other events include edge addition, node removal, and more, making it ideal for real-time updates in visualizations.

Advanced Considerations and Resources

While the core Graph class provides essential functionality, Graphology’s design allows for re-implementation for specialized needs, retaining the ability to use the standard library (implementing-graphology). This flexibility is particularly useful for performance optimization in specific use cases.

For further learning, the official website (Graphology) offers insights into design choices and implementation details. The changelog is available at (changelog), and citation information is provided for academic use, published on Zenodo with DOI (Zenodo DOI).

Conclusion

This essentials of getting started with Graphology, from installation to advanced usage with the standard library. It provides a foundation to build and manipulate graph data structures, with resources for deeper exploration. For those interested in visualization, integrating with sigma.js offers powerful rendering capabilities, enhancing the interactive experience.