graphrs

graphrs is a Rust package for the creation, manipulation and analysis of graphs.

It allows graphs to be created with support for:

• directed and undirected edges
• multiple edges between two nodes
• self-loops

A Graph has two generic arguments:

• T: Specifies the type to use for node names.
• A: Specifies the type to use for node and edge attributes. Attributes are optional extra data that are associated with a node or an edge. For example, if nodes represent people and T is an i32 of their employee ID then the node attributes might store their first and last names.

Documentation

The doc.rs documentation is here.

Python bindings

Python bindings are available in the graphrs-python package.

Major structs

• Graph
• Node
• Edge

Modules

• algorithms::centrality
• algorithms::cluster
• algorithms::community
• algorithms::components
• algorithms::structural_holes
• algorithms::shortest_path
• generators
• readwrite

Examples

Create a weighted, directed graph

use graphrs::{Edge, Graph, GraphSpecs, Node};

let nodes = vec![
    Node::from_name("n1"),
    Node::from_name("n2"),
    Node::from_name("n3"),
];

let edges = vec![
    Edge::with_weight("n1", "n2", 1.0),
    Edge::with_weight("n2", "n1", 2.0),
    Edge::with_weight("n1", "n3", 3.0),
    Edge::with_weight("n2", "n3", 3.0),
];

let specs = GraphSpecs::directed();

let graph = Graph::<&str, ()>::new_from_nodes_and_edges(
    nodes,
    edges,
    specs
);

Create an undirected graph from just edges

use graphrs::{Edge, Graph, GraphSpecs};

let mut graph: Graph<&str, ()> = Graph::new(GraphSpecs::undirected_create_missing());
let result = graph.add_edges(vec![
    Edge::new("n1", "n2"),
    Edge::new("n2", "n3"),
]);

Create an empty graph with all possible specifications

use graphrs::{Graph, GraphSpecs, EdgeDedupeStrategy, MissingNodeStrategy, SelfLoopsFalseStrategy};

let graph = Graph::<&str, ()>::new(
    GraphSpecs {
        directed: true,
        edge_dedupe_strategy: EdgeDedupeStrategy::Error,
        missing_node_strategy: MissingNodeStrategy::Error,
        multi_edges: false,
        self_loops: false,
        self_loops_false_strategy: SelfLoopsFalseStrategy::Error,
    }
);

Generate graphs

use graphrs::{generators};
let graph_complete = generators::classic::complete_graph(5, true);
let graph_random = generators::random::fast_gnp_random_graph(250, 0.25, true, None);

Find the shortest path between two nodes

use graphrs::{Edge, Graph, GraphSpecs, Node};
use graphrs::{algorithms::{shortest_path::{dijkstra}}};

let mut graph = Graph::<&str, ()>::new(GraphSpecs::directed_create_missing());
graph.add_edges(vec![
    Edge::with_weight("n1", "n2", 1.0),
    Edge::with_weight("n2", "n1", 2.0),
    Edge::with_weight("n1", "n3", 3.0),
    Edge::with_weight("n2", "n3", 1.1),
]);

let shortest_paths = dijkstra::single_source(&graph, true, "n1", Some("n3"), None, false, true);
assert_eq!(shortest_paths.unwrap().get("n3").unwrap().distance, 2.1);

Compute the betweenness, closeness and eigenvector centrality for all nodes

use graphrs::{algorithms::centrality, generators};
let graph = generators::social::karate_club_graph();
let centralities = centrality::betweenness::betweenness_centrality(&graph, false, true);
let closeness = centrality::closeness::closeness_centrality(&graph, false, true);
let centralities = centrality::eigenvector::eigenvector_centrality(&graph, false, None, None);

Detect communities within a graph

use graphrs::{algorithms::{community}, generators};
let graph = generators::social::karate_club_graph();
let partitions = community::louvain::louvain_partitions(&graph, false, None, None, Some(1));

Read and write graphml files

use graphrs::{readwrite, GraphSpecs};
let graph = readwrite::graphml::read_graphml_file("/some/file.graphml", GraphSpecs::directed());
readwrite::graphml::write_graphml(&graph, "/some/other/file.graphml");

Get an adjacency matrix

This is an optional feature. Enable in Cargo.toml with: graphrs = { version = "x.y.z", features = ["adjacency_matrix"] }

use graphrs::generators;
let graph = generators::social::karate_club_graph();
let matrix = graph.get_sparse_adjacency_matrix().unwrap();

Performance

A comparison of the performance of graphrs against NetworkX, igraph and graph-tool can be found here.

Credits

Some of the structure of the API and some of the algorithms were inspired by NetworkX.

License

MIT