Plotly for Python
Plotly's Python graphing library makes interactive, publication-quality graphs — widely used for visualizing graph and network data.
Visit sitepython-igraph
igraph is available on the Python Package Index with pre-compiled wheels for most Python distributions and platforms, for fast network analysis.
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A Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
Visit sitePyTorch Geometric (PyG)
A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications on structured data.
Visit siteDeep Graph Library (DGL)
Fast and memory-efficient message passing primitives for training Graph Neural Networks, framework-agnostic across PyTorch, TensorFlow, and MXNet.
Visit siteGraph Nets
DeepMind's library for building graph networks in TensorFlow and Sonnet, with demos for shortest-path, sorting, and physics prediction tasks.
Visit siteSpektral
A Python library for graph deep learning, based on the Keras API and TensorFlow 2, implementing popular GNN and pooling layers.
Visit siteGeometricFlux.jl
A framework for geometric deep learning in Julia, providing classic graph neural network layers and utility constructs built on Flux.
Visit siteJraph
A lightweight library for working with graph neural networks in JAX, providing a graph data structure and a "zoo" of forkable GNN models.
Visit siteptgnn
A PyTorch GNN library containing code for creating graph neural network models, with sample implementations for PPI, VarMisuse, and more.
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