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Little Ball of Fur
Little Ball of Fur provides graph sampling extensions for NetworKit and NetworkX.

About Little Ball of Fur
Little Ball of Fur is an open source Python library that extends NetworKit and NetworkX with methods for sampling graph-structured data. It is distributed as a GitHub repository and is described as a graph sampling extension library for both libraries.
The library groups its sampling methods into node (vertex) sampling, edge sampling, and exploration-based sampling. It provides a unified interface for applying these algorithms, and the repository includes a short example that samples a NetworkX graph using a diffusion sampler. The implemented methods are based on papers published at networking and data mining venues, and the library is cited as a CIKM 2020 paper.
Key features
- Node sampling methods, including degree-based, random, and PageRank-based samplers
- Edge sampling methods, including random edge, random node-edge, and hybrid node-edge samplers
- Exploration-based methods, including snowball, forest fire, and random walk samplers
- Unified application interface for applying sampling algorithms to graphs
- Example usage with NetworkX graphs, such as a diffusion sampler on a Watts-Strogatz graph
- Methods implemented from published networking and data mining research papers
- Open source, with the source code and license available in the GitHub repository
- Offers a large set of vertex, edge, and exploration sampling techniques in one library
- Provides a single interface so that sampling algorithms can be applied with little code
- Works as an extension of NetworKit and NetworkX, so those libraries are needed for use
Little Ball of Fur at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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