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.

Major structs

• Graph
• Node
• Edge

Modules

• algorithms::centrality
• algorithms::centrality
• algorithms::cluster
• algorithms::community
• algorithms::components
• 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 for crate. 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