pathfinding

pathfinding

This crate implements several pathfinding, flow, and graph algorithms in Rust. The algorithms are generic over their arguments. See the documentation for more information about the various algorithms.

Using this crate

In your Cargo.toml, put:

[dependencies]
pathfinding = "4.16.0"

You can then pull your preferred algorithm (BFS in this example) using:

use pathfinding::prelude::bfs;

Example

We will search the shortest path on a chess board to go from (1, 1) to (4, 6) doing only knight moves.

use pathfinding::prelude::bfs;

#[derive(Clone, Debug, Eq, Hash, Ord, PartialEq, PartialOrd)]
struct Pos(i32, i32);

impl Pos {
  fn successors(&self) -> Vec {
    let &Pos(x, y) = self;
    vec![Pos(x+1,y+2), Pos(x+1,y-2), Pos(x-1,y+2), Pos(x-1,y-2),
         Pos(x+2,y+1), Pos(x+2,y-1), Pos(x-2,y+1), Pos(x-2,y-1)]
  }
}

static GOAL: Pos = Pos(4, 6);
let result = bfs(&Pos(1, 1), |p| p.successors(), |p| *p == GOAL);
assert_eq!(result.expect("no path found").len(), 5);

Working with Graphs

If you want to use this library with traditional graph structures (nodes, edges, and weights), see the Graph Guide for comprehensive examples showing:

• How to represent graphs (adjacency lists, adjacency matrices, edge lists)
• Using A* and Dijkstra with weighted graphs
• Using BFS and DFS with unweighted graphs
• Practical examples for spatial shortest paths
• Converting from other languages (R, Python)
• Tips and best practices

License

This code is released under a dual Apache 2.0 / MIT free software license.

Benchmarking

This repository includes two types of benchmarks:

Wall-time Benchmarks (Criterion/CodSpeed)

Traditional wall-time benchmarks using Criterion (with CodSpeed compatibility) are located in benches/ with names like algos.rs, edmondskarp.rs, etc. These can be run with:

cargo bench --bench algos --bench edmondskarp --bench kuhn_munkres --bench separate_components

Deterministic Benchmarks (iai-callgrind)

For more precise and deterministic performance measurements, we use iai-callgrind which counts CPU instructions, cache hits/misses, and estimated cycles using Valgrind. These benchmarks are prefixed with iai_ and require the iai feature flag:

# Install valgrind first (required by iai-callgrind)
sudo apt-get install valgrind  # On Ubuntu/Debian

# Run the benchmarks with the feature flag
cargo bench --features iai --bench iai_algos --bench iai_edmondskarp --bench iai_kuhn_munkres --bench iai_separate_components

The iai-callgrind benchmarks provide consistent results across runs and are not affected by system load, making them ideal for detecting performance regressions. They run automatically in CI for all pull requests, comparing performance against the base branch.

Contributing

You are welcome to contribute by opening issues or submitting pull requests. Please open an issue before implementing a new feature, in case it is a work in progress already or it is fit for this repository.

In order to pass the continuous integration tests, your code must be formatted using the latest rustfmt with the nightly rust toolchain, and pass cargo clippy and pre-commit checks. Those will run automatically when you submit a pull request. You can install pre-commit to your checked out version of the repository by running:

$ pre-commit install --hook-type commit-msg

This repository uses the conventional commits commit message style, such as:

• feat(matrix): add Matrix::transpose()
• fix(tests): remove unused imports

Each commit must be self-sufficient and clean. If during inspection or code review you need to make further changes to a commit, please squash it. You may use git rebase -i, or more convenient tools such as jj in order to manipulate your git commits.

If a pull-request should automatically close an open issue, please include "Fix #xxx# or "Close #xxx" in the pull-request cover-letter.