webgraph

Python bindings for the Rust version of the WebGraph framework, built with PyO3.

WebGraph is a framework for graph compression that allows very large graphs (billions of nodes and arcs) to be stored in a compact representation while providing fast random access to successors.

Installation

pip install webgraph

Building from source

Pre-built wheels are compiled for a generic target. You should however enable native optimizations (e.g., BMI2 for faster succinct data structures) by building the wheel from source:

pip install maturin
git clone https://github.com/vigna/webgraph-py.git
cd webgraph-py/webgraph
maturin build --release -o dist
pip install dist/*.whl

The repository's .cargo/config.toml sets target-cpu=native, so the resulting wheel will be optimized for your CPU.

Quick start

import webgraph

# Load a compressed graph
g = webgraph.BvGraph("/PATH/TO/BASENAME")

print(f"Nodes: {g.num_nodes()}, Arcs: {g.num_arcs()}")

# Iterate over successors
for s in g.successors(42):
    print(s)

# Degree computation (returns a numpy array)
degrees = g.outdegrees()

# Top-k nodes by degree (returns a (k, 2) ndarray: column 0 = node, column 1 = degree)
top = g.top_k_out(10)
print(top[:, 0])  # node IDs

# Breadth-first search
for root, parent, node, distance in g.bfs_from_node(0):
    print(f"node={node} distance={distance}")

Project links

Data verified by PyPI on Jul 23, 2026
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Latest release

1 maintainer

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Avatar for vigna from gravatar.com vigna

Credits

Author: Sebastiano Vigna

GitHub Statistics

Data verified by PyPI on Jul 23, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0 OR MIT
View SPDX License List

Requires

Python >=3.10

Tags

graph compression webgraph bvgraph succinct

Classifiers

Report project as malware

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