snap-stanford/deepsnap
Python library assists deep learning on graphs
This library helps machine learning engineers and researchers build and train deep learning models on graph-structured data more efficiently. It takes in graph data, such as social networks or molecular structures, and helps prepare it for training, then outputs trained graph neural network models. The primary users are Python developers working with graph deep learning frameworks.
568 stars. Available on PyPI.
Use this if you are a machine learning engineer or researcher already familiar with PyTorch Geometric and need to streamline the process of building and experimenting with graph neural networks.
Not ideal if you are new to deep learning or graph-based machine learning and are looking for an introductory tool.
Stars
568
Forks
56
Language
Python
License
MIT
Category
Last pushed
Nov 24, 2025
Commits (30d)
0
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