Graph Neural Network Python Packages

pgl

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

egnn-pytorch

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

matgraph-cli

Deep Learning toolkit for Materials Science. Predict properties (CGCNN, MEGNet, M3GNet), discover new materials (GNoME-inspired), simulate XRD, and serve via GraphQL API.

molcraft

A python package for building powerful GNN models for molecules.

solitairenet

Solitaire deep learning library.

dive-into-graphs

A library for graph deep learning research

dhl-mm

Sparse Lie algebra engine for G₂, F₄, E₆, E₇, E₈ — 913× compression, lattice gauge theory, equivariant GNN layers. pip install dhl-mm

chemicalx

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

bigraph

Bipartite-network link prediction in Python

crslab

CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).

graphids

Graph-based cloud intrusion detection using GCN, Transformer autoencoder, and contrastive learning — Scientific Reports 2025

gigl

Gigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks

graphsite

Generate graph representations of protein binding sites.