This library implements the node2vec algorithm for scalable feature learning on networks. It generates random walks on graphs and uses Word2Vec (via gensim) to learn embeddings that capture graph structure. The algorithm supports tuning between BFS and DFS exploration strategies to capture homophily or structural equivalence, and can also embed edges using methods like Hadamard product.