# Hedgehogs: They Have a Lot of Edges

Posted on 2023-04-03
Tags: scala, open source, personal project, graphs

This is a quick introduction to a library I made called Hedgehogs, it’s for cyclic graph traversal, and is cross-built for scala.js for use in frontends.

## Creation

So, to show off what we can do, let’s make a quick graph: A graph showing 3 nodes, A, B and C, with A->B weight 3, A->C weight 5 and B->C weight 1

It’s your classic graph where there’s an expensive route from `A` to `C`, or a cheaper route via `B`.

So let’s construct it with `hedgehogs`:

``````import net.andimiller.hedgehogs._

// We could store some data in these nodes, but for now it's Unit
val nodes: List[Node[String, Unit]] =
List("A", "B", "C").map(name => Node(name, ()))
// nodes: List[Node[String, Unit]] = List(
//   Node(id = "A", data = ()),
//   Node(id = "B", data = ()),
//   Node(id = "C", data = ())
// )

// And these are our edges
val edges: List[Edge[String, Int]] =
List(
Edge("A", "B", 3),
Edge("A", "C", 5),
Edge("B", "C", 1)
)
// edges: List[Edge[String, Int]] = List(
//   Edge(from = "A", to = "B", weight = 3),
//   Edge(from = "A", to = "C", weight = 5),
//   Edge(from = "B", to = "C", weight = 1)
// )

Graph.fromIterables(nodes, edges, bidirectional = false)
// res0: cats.data.package.ValidatedNel[String, Graph[String, Unit, Int]] = Valid(
//   a = Graph(
//     nodes = Map("A" -> (), "B" -> (), "C" -> ()),
//     edges = Map("A" -> Vector(("B", 3), ("C", 5)), "B" -> Vector(("C", 1)))
//   )
// )``````

You’ll see it validated the graph as we made it, and it would’ve returned errors if we did something wrong:

``````val badNodes: List[Node[String, Unit]] =
List("A", "A", "B", "C").map(name => Node(name, ()))
// badNodes: List[Node[String, Unit]] = List(
//   Node(id = "A", data = ()),
//   Node(id = "A", data = ()),
//   Node(id = "B", data = ()),
//   Node(id = "C", data = ())
// )

// res1: cats.data.package.ValidatedNel[String, Graph[String, Unit, Int]] = Invalid(
//   e = NonEmptyList(head = "A has 2 nodes, required at most 1", tail = List())
// )

List(
Edge("A", "B", 3),
Edge("A", "D", 5),
Edge("Y", "Z", 1)
)
// badEdges: List[Edge[String, Int]] = List(
//   Edge(from = "A", to = "B", weight = 3),
//   Edge(from = "A", to = "D", weight = 5),
//   Edge(from = "Y", to = "Z", weight = 1)
// )

// res2: cats.data.package.ValidatedNel[String, Graph[String, Unit, Int]] = Invalid(
//   e = NonEmptyList(
//     head = "Y is not a known node",
//     tail = List("D is not a known node")
//   )
// )``````

So, returning to our valid graph:

``````graph
// res3: Graph[String, Unit, Int] = Graph(
//   nodes = Map("A" -> (), "B" -> (), "C" -> ()),
//   edges = Map("A" -> Vector(("B", 3), ("C", 5)), "B" -> Vector(("C", 1)))
// )``````

## Routefinding

`Hedgehogs` comes with an implementation of Dijkstra’s Algorithm for finding routes between nodes.

The first way you can use it is to ask for the optimal path between two nodes:

``````Dijkstra(graph)("A", "C")
// res4: Option[(Int, List[String])] = Some(value = (4, List("A", "B", "C")))``````

As you can see this returned us the distance of `4` between the two nodes, and tells us the path is `List("A", "B", "C")`.

Since Dijkstra’s calculates optimal routes from the origin to any number of nodes, there is also a `multi` version where we can ask for the optimal routes to multiple destinations at once:

``````Dijkstra.multi(graph)("A", Set("B", "C"))
// res5: Map[String, (Int, List[String])] = Map(
//   "B" -> (3, List("A", "B")),
//   "C" -> (4, List("A", "B", "C"))
// )``````

You can see this returns a map with our optimal routes to `B` and `C`.

## Why?

I originally made this library to solve a few problems in tooling for EVE Online, it is fairly common to need to measure routes between places and so one of the examples in the hedgehogs repo is in fact the solar system for EVE Online:

Once the graph’s been loaded we have thousands of solar systems and stargates:

``````val solarSystems = eveOnlineMap.nodes.size
// solarSystems: Int = 8485
val stargates    = eveOnlineMap.edges.size
// stargates: Int = 5214``````

And `Hedgehogs` allows us to routefind optimally around the graph very quickly, even in javascript:

``````Dijkstra(eveOnlineMap)(karan, jita)
// res6: Option[(Int, List[Long])] = Some(
//   value = (
//     34,
//     List(
//       30004306L,
//       30004309L,
//       30004626L,
//       30004625L,
//       30004624L,
//       30004562L,
//       30004561L,
//       30004560L,
//       30004559L,
//       30004557L,
//       30004555L,
//       30004553L,
//       30004552L,
//       30004554L,
//       30004584L,
//       30004586L,
//       30004589L,
//       30004040L,
//       30004042L,
//       30004043L,
//       30004044L,
//       30004046L,
//       30003841L,
//       30003836L,
//       30003837L,
//       30045344L,
//       30045338L,
//       30045353L,
//       30045345L,
//       30045346L,
//       30002813L,
//       30001376L,
//       30001379L,
//       30000143L,
//       30000142L
//     )
//   )
// )
Dijkstra.multi(eveOnlineMap)(karan, Set(jita, amarr))
// res7: Map[Long, (Int, List[Long])] = Map(
//   30002187L -> (
//     29,
//     List(
//       30004306L,
//       30004303L,
//       30004296L,
//       30004293L,
//       30004288L,
//       30004287L,
//       30004286L,
//       30004285L,
//       30004283L,
//       30004280L,
//       30004270L,
//       30004268L,
//       30004267L,
//       30004240L,
//       30004242L,
//       30004244L,
//       30004245L,
//       30004246L,
//       30005055L,
//       30005054L,
//       30005052L,
//       30005050L,
//       30003881L,
//       30003880L,
//       30003878L,
//       30003877L,
//       30003876L,
//       30005043L,
//       30005038L,
//       30002187L
//     )
//   ),
//   30000142L -> (
//     34,
//     List(
//       30004306L,
//       30004309L,
//       30004626L,
//       30004625L,
//       30004624L,
//       30004562L,
//       30004561L,
//       30004560L,
//       30004559L,
//       30004557L,
// ...``````