Crate graphina 

Graphina Crate

A graph data science library that provides common graph types, algorithms, and data structures.

Module Overview

• core – Always enabled: basic graph types, builders, IO, serialization, paths, validation.
• centrality (feature: centrality) – Node/edge importance measures (Result-based APIs).
• community (feature: community) – Community detection and clustering (Result-based APIs).
• links (feature: links) – Link prediction algorithms.
• metrics (feature: metrics) – Graph and node metrics (diameter, radius, clustering, etc.).
• mst (feature: mst) – Minimum spanning tree algorithms.
• traversal (feature: traversal) – BFS/DFS and related traversal strategies.
• approximation (feature: approximation) – Heuristics for NP-hard problems.
• parallel (feature: parallel) – Parallel implementations for selected algorithms.
• subgraphs (feature: subgraphs) – Induced subgraph and ego network utilities.

API Conventions

Algorithms return Result<_, graphina::core::error::GraphinaError> for error handling. Selector-style helpers that pick nodes (like voterank) may return plain collections.

Enable only required features to minimize size and compile time.

Modules

approximationapproximation

Approximation algorithms for NP-hard problems.

centralitycentrality

Centrality algorithms facade.

communitycommunity

Community detection and clustering algorithms.

core

Core graph types and utilities.

linkslinks

Link prediction algorithms.

metricsmetrics

Graph metrics and metrics-based algorithms. Graph metrics module.

mstmst

Minimum spanning tree algorithms. Minimum Spanning Tree algorithms module.

parallelparallel

Parallel implementations of algorithms.

subgraphssubgraphs

Induced subgraph and ego network utilities. Subgraph operations module.

traversaltraversal

Graph traversal algorithms. Graph traversal algorithms module.