DGL (Deep Graph Library) is a framework-agnostic Python package for deep learning on graph-structured data. It provides efficient and customizable message passing primitives for implementing Graph Neural Networks, with support for GPU acceleration and scalability. The library integrates with major deep learning frameworks (PyTorch, Apache MXNet, TensorFlow) while offering specialized graph operations optimized for GNN training and inference.