eliorc/node2vec

Health v2 · maintenance only

Adoption not part of the score

1301 stars · 253 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library implementing the node2vec algorithm for learning low-dimensional embeddings of nodes and edges in graphs. It integrates with networkx for graph input and gensim Word2Vec for training, supporting weighted graphs and parallel walk generation.

Use cases

• generate node embeddings for a networkx graph
• embed edges of a graph using the Hadamard method
• find nodes most similar to a given node in a network
• train node2vec on a weighted graph
• save node embeddings in word2vec format for downstream ML tasks

When to choose

• you need node or edge embeddings from a graph for machine learning tasks
• your graphs are already in networkx format
• you want a pip-installable, well-tested implementation of the node2vec paper

When to avoid

• you need active maintenance or timely bug fixes - the maintainer has stated they no longer have time
• you need GPU acceleration or very large-scale graph embedding
• you are on Windows and need multi-worker parallelism - only workers=1 is supported

Facets

library · maturity maintenance

machine-learning rag machine-learning data-science python cross-platform node2vec graph-embeddings network-embeddings networkx gensim word2vec graph-representation-learning random-walks algorithms

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markdown · JSON · MCP: product_card(name="eliorc/node2vec")