Individual skill
torch-geometric
PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX analytics or non-graph PyTorch models.
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# PyTorch Geometric (PyG)
PyG is the standard library for Graph Neural Networks built on PyTorch. It provides data structures for graphs, 60+ GNN layer implementations, scalable mini-batch training, and support for heterogeneous graphs.
## Installation
Tested against **torch-geometric 2.7.x** (Oct 2025). Requires **Python 3.10+** and **PyTorch 2.6+**.
```bash
# 1. Install PyTorch first (match your CUDA/CPU setup — see https://pytorch.org/get-started/locally/)
uv pip install torch
# 2. Core PyG (no extension wheels required for basic usage)
uv pip install torch_geometric