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Path algorithms find routes between nodes in a graph. They return GraphPath objects containing the source node and ordered steps (edge + node pairs).

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Shortest Paths

Shortest path algorithms find paths with minimum total weight. Use BFS for unweighted graphs or Dijkstra for weighted graphs.

​
hasPath

function hasPath(
  graph: Graph,
  sourceId: string,
  targetId: string
): boolean
Checks whether a path exists between two nodes. Complexity: O(V + E) When to use:
  • Reachability testing
  • Validating connections before path computation

​
Example

import { createGraph, hasPath } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [{ id: 'ab', sourceId: 'a', targetId: 'b' }],
});

hasPath(graph, 'a', 'b'); // true
hasPath(graph, 'a', 'c'); // false

​
getShortestPath

function getShortestPath<N, E>(
  graph: Graph<N, E>,
  opts: SinglePathOptions<E>
): GraphPath<N, E> | undefined
Returns a single shortest path from source to target, or undefined if unreachable. Complexity:
  • O(V + E) for unweighted graphs (BFS)
  • O((V + E) log V) for weighted graphs (Dijkstra)
When to use:
  • Finding the shortest route between two points
  • Navigation and routing
  • Dependency resolution

​
Example

import { createGraph, getShortestPath } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

const path = getShortestPath(graph, { to: 'c' });
// path.steps -> [{node: nodeB, edge: ...}, {node: nodeC, edge: ...}]

​
Weighted graphs

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b', data: { weight: 5 } },
    { id: 'ac', sourceId: 'a', targetId: 'c', data: { weight: 10 } },
    { id: 'bc', sourceId: 'b', targetId: 'c', data: { weight: 2 } },
  ],
  initialNodeId: 'a',
});

const path = getShortestPath(graph, {
  to: 'c',
  getWeight: (edge) => edge.data.weight,
});
// path goes a -> b -> c (total weight: 7)

​
getShortestPaths

function getShortestPaths<N, E>(
  graph: Graph<N, E>,
  opts?: PathOptions<E>
): GraphPath<N, E>[]
Returns all shortest paths from a source node. When multiple paths have equal minimum length, all are returned. Complexity:
  • O(V + E) for unweighted graphs
  • O((V + E) log V) for weighted graphs
When to use:
  • Finding all alternative routes of equal length
  • Analyzing path redundancy
  • Building path tables

​
Example

import { createGraph, getShortestPaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

const paths = getShortestPaths(graph);
// Returns paths to 'b' and 'c' from 'a'

​
genShortestPaths

function genShortestPaths<N, E>(
  graph: Graph<N, E>,
  opts?: PathOptions<E>
): Generator<GraphPath<N, E>>
Lazily yields all shortest paths from a source node. Use getShortestPaths() for the full array. When to use:
  • Processing paths without loading all into memory
  • Early termination when finding acceptable path

​
Example

import { createGraph, genShortestPaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

for (const path of genShortestPaths(graph)) {
  console.log(path.steps.map(s => s.node.id));
}

​
getAllPairsShortestPaths

function getAllPairsShortestPaths<N, E>(
  graph: Graph<N, E>,
  opts?: AllPairsShortestPathsOptions<E>
): GraphPath<N, E>[]
Returns shortest paths between all pairs of nodes. Algorithms:
  • 'dijkstra' (default): Runs Dijkstra from each source. O(V * (V + E) log V)
  • 'floyd-warshall': Dynamic programming. O(V³)
When to use:
  • Precomputing all-pairs distances
  • Network diameter calculation
  • Building complete routing tables
Complexity:
  • Dijkstra: O(V² + VE log V) for sparse graphs
  • Floyd-Warshall: O(V³) always, better for dense graphs

​
Example

import { createGraph, getAllPairsShortestPaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
});

const allPaths = getAllPairsShortestPaths(graph);
// Paths for every reachable (source, target) pair

​
Using Floyd-Warshall

const allPaths = getAllPairsShortestPaths(graph, {
  algorithm: 'floyd-warshall',
  getWeight: (edge) => edge.data?.weight ?? 1,
});

​
Simple Paths

Simple paths are acyclic paths that don’t revisit nodes. These algorithms use DFS backtracking.

​
getSimplePath

function getSimplePath<N, E>(
  graph: Graph<N, E>,
  opts: SinglePathOptions<E>
): GraphPath<N, E> | undefined
Returns a single simple (acyclic) path from source to target, or undefined if unreachable. Complexity: O(V + E) in best case, exponential in worst case When to use:
  • Finding any path without cycles
  • When shortest path might contain cycles (in directed graphs with negative weights)

​
Example

import { createGraph, getSimplePath } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

const path = getSimplePath(graph, { to: 'c' });
// path.steps -> [{node: nodeB, edge: ...}, {node: nodeC, edge: ...}]

​
getSimplePaths

function getSimplePaths<N, E>(
  graph: Graph<N, E>,
  opts?: PathOptions<E>
): GraphPath<N, E>[]
Returns all simple (acyclic) paths from a source node. Complexity: Exponential (can be V! paths in complete graph) When to use:
  • Enumerating all possible routes
  • Finding alternative paths
  • Network reliability analysis
Warning: Can produce exponentially many paths. Use with caution on large graphs.

​
Example

import { createGraph, getSimplePaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
    { id: 'ac', sourceId: 'a', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

const paths = getSimplePaths(graph, { to: 'c' });
// Two paths: a->b->c and a->c

​
genSimplePaths

function genSimplePaths<N, E>(
  graph: Graph<N, E>,
  opts?: PathOptions<E>
): Generator<GraphPath<N, E>>
Lazily yields all simple (acyclic) paths from a source node via DFS backtracking. When to use:
  • Processing paths one at a time
  • Early termination when finding acceptable path
  • Avoiding memory issues with many paths

​
Example

import { createGraph, genSimplePaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
    { id: 'ac', sourceId: 'a', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

for (const path of genSimplePaths(graph, { to: 'c' })) {
  console.log(path.steps.map(s => s.node.id));
  // ['b', 'c'] or ['c']
}

​
Path Operations

​
joinPaths

function joinPaths<N, E>(
  headPath: GraphPath<N, E>,
  tailPath: GraphPath<N, E>
): GraphPath<N, E>
Joins two paths end-to-end. The last node of the head path must equal the source of the tail path. When to use:
  • Combining path segments
  • Building longer routes from cached sub-paths

​
Example

import { createGraph, getShortestPath, joinPaths } from '@statelyai/graph';

const graph = createGraph({
  nodes: [{ id: 'a' }, { id: 'b' }, { id: 'c' }],
  edges: [
    { id: 'ab', sourceId: 'a', targetId: 'b' },
    { id: 'bc', sourceId: 'b', targetId: 'c' },
  ],
  initialNodeId: 'a',
});

const ab = getShortestPath(graph, { to: 'b' })!;
const bc = getShortestPath(graph, { from: 'b', to: 'c' })!;
const ac = joinPaths(ab, bc);
// ac: a -> b -> c

​
Options

​
PathOptions

interface PathOptions<TEdgeData = any> {
  from?: string;
  to?: string;
  getWeight?: (edge: GraphEdge<TEdgeData>) => number;
}
Properties:
  • from - Source node ID. Default: graph.initialNodeId, else the sole node with in-degree 0
  • to - Target node ID. If omitted, returns paths to all reachable nodes
  • getWeight - Edge weight function. Default: every edge has weight 1. Used by Dijkstra’s algorithm when provided

​
SinglePathOptions

interface SinglePathOptions<TEdgeData = any> {
  from?: string;
  to: string;
  getWeight?: (edge: GraphEdge<TEdgeData>) => number;
}
Properties:
  • from - Source node ID. Default: graph.initialNodeId, else the sole node with in-degree 0
  • to - Target node ID. Required for single-path queries
  • getWeight - Edge weight function. Default: every edge has weight 1

​
AllPairsShortestPathsOptions

interface AllPairsShortestPathsOptions<TEdgeData = any> {
  algorithm?: 'floyd-warshall' | 'dijkstra';
  getWeight?: (edge: GraphEdge<TEdgeData>) => number;
}
Properties:
  • algorithm - Algorithm to use. Default: 'dijkstra'. Use 'floyd-warshall' for dense graphs
  • getWeight - Edge weight function. Default: every edge has weight 1

​
Path Types

​
GraphPath

interface GraphPath<TNodeData = any, TEdgeData = any> {
  source: GraphNode<TNodeData>;
  steps: GraphStep<TNodeData, TEdgeData>[];
}
Properties:
  • source - The source node where this path begins
  • steps - Ordered steps from source to target. path.steps.at(-1)?.node is the final node. Empty steps means source-only path

​
GraphStep

interface GraphStep<TNodeData = any, TEdgeData = any> {
  edge: GraphEdge<TEdgeData>;
  node: GraphNode<TNodeData>;
}
Properties:
  • edge - Edge traversed to reach this node
  • node - Node reached after traversing the edge

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