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 andTis ani32of their employee ID then the node attributes might store their first and last names.
The doc.rs documentation is here.
Python bindings are available in the graphrs-python package.
GraphNodeEdge
algorithms::boundaryalgorithms::cutsalgorithms::centralityalgorithms::clusteralgorithms::communityalgorithms::componentsalgorithms::structural_holesalgorithms::shortest_pathgeneratorsreadwrite
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
);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"),
]);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,
}
);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);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);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);use graphrs::{algorithms::{community}, generators};
use graphrs::{algorithms::community::leiden::{leiden, QualityFunction}};
let graph = generators::social::karate_club_graph();
let partitions = community::louvain::louvain_partitions(&graph, false, None, None, Some(1));
let partitions = leiden(&graph, true, QualityFunction::CPM, None, None, None);use graphrs::{readwrite, GraphSpecs};
let graph = readwrite::graphml::read_graphml_file("/some/file.graphml", GraphSpecs::directed());
readwrite::graphml::write_graphml_file(&graph, "/some/other/file.graphml");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();A comparison of the performance of graphrs against NetworkX, igraph and graph-tool can be found here.
Some of the structure of the API and some of the algorithms were inspired by NetworkX.
MIT