PecanPy
github.com/krishnanlab/pecanpyPecanPy: A parallelized, efficient, and accelerated node2vec in Python. Learning low-dimensional representations (embeddings) of nodes in large graphs is key to applying machine learning on massive biological networks. Node2vec is the most widely used method for node embedding. PecanPy is a fast, parallelized, memory efficient, and cache optimized Python implementation of node2vec. It uses cache-optimized compact graph data structures and precomputing/parallelization to result in fast, high-quality node embeddings for biological networks of all sizes and densities.