Graph Types in Graphina

Graphina provides robust, statically typed graph structures. Select the appropriate type for your use case.

Main Types

Graphina focuses on simple graphs to maximize performance. Multiple edges between the same node pair are not supported.

Graph<A, W> (Undirected)

Graph represents an undirected graph.

• Edges: Bidirectional. Adding an edge from a to b implies a connection b to a.
• Use Cases: Social networks, road networks, molecular structures.

use graphina::core::types::Graph;

// Nodes store &str, Edges store f64 weights
let mut g = Graph::<&str, f64>::new();

Digraph<A, W> (Directed)

Digraph represents a directed graph.

• Edges: Directional. An edge from a to b does not imply b to a.
• Use Cases: Web pages, citation networks, dependency graphs.

use graphina::core::types::Digraph;

let mut dg = Digraph::<&str, f64>::new();

Performance and Memory Layout

Graphina uses a StableGraph backend from petgraph.

1. Vector-backed storage: Nodes and edges use Vec structures.
2. Stable Indices: Removing a node does not shift other indices. Safely retain NodeIds.
3. Cache Locality: Contiguous memory usage improves iteration performance.

NodeId vs Node Values

NetworkX adds nodes by value:

G.add_node("Alice")
G.add_edge("Alice", "Bob")

Graphina separates topology from data. "Alice" is an attribute; the node is identified by a lightweight NodeId.

let alice_id = graph.add_node("Alice");
let bob_id = graph.add_node("Bob");

// Connect using IDs, not strings
graph.add_edge(alice_id, bob_id, 1.0);

This design separates topology from data, enabling optimized integer-based algorithms.

Density

Check density (ratio of existing to possible edges).

let d = graph.density();
println!("Graph density: {:.2}", d);