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A library for creating generic graph data structures and modifying, analyzing, and visualizing them.

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dominikbraun/graph

A library for creating generic graph data structures and modifying, analyzing, and visualizing them.

Features

  • Generic vertices of any type, such as int or City.
  • Graph traits with corresponding validations, such as cycle checks in acyclic graphs.
  • Algorithms for finding paths or components, such as shortest paths or strongly connected components.
  • Algorithms for transformations and representations, such as transitive reduction or topological order.
  • Algorithms for non-recursive graph traversal, such as DFS or BFS.
  • Edges with optional metadata, such as weights or custom attributes.
  • Visualization of graphs using the DOT language and Graphviz.
  • Extensive tests with ~90% coverage, and zero dependencies.

Status: Because graph is in version 0, the public API shouldn't be considered stable.

Getting started

go get github.com/dominikbraun/graph

Quick examples

Create a graph of integers

graph of integers

g := graph.New(graph.IntHash)

g.AddVertex(1)
g.AddVertex(2)
g.AddVertex(3)
g.AddVertex(4)
g.AddVertex(5)

_ = g.AddEdge(1, 2)
_ = g.AddEdge(1, 4)
_ = g.AddEdge(2, 3)
_ = g.AddEdge(2, 4)
_ = g.AddEdge(2, 5)
_ = g.AddEdge(3, 5)

Create a directed acyclic graph of integers

directed acyclic graph

g := graph.New(graph.IntHash, graph.Directed(), graph.Acyclic())

g.AddVertex(1)
g.AddVertex(2)
g.AddVertex(3)
g.AddVertex(4)

_ = g.AddEdge(1, 2)
_ = g.AddEdge(1, 3)
_ = g.AddEdge(2, 3)
_ = g.AddEdge(2, 4)
_ = g.AddEdge(3, 4)

Create a graph of a custom type

To understand this example in detail, see the concept of hashes.

type City struct {
    Name string
}

cityHash := func(c City) string {
    return c.Name
}

g := graph.New(cityHash)

g.AddVertex(london)

Create a weighted graph

weighted graph

g := graph.New(cityHash, graph.Weighted())

g.AddVertex(london)
g.AddVertex(munich)
g.AddVertex(paris)
g.AddVertex(madrid)

_ = g.AddEdge("london", "munich", graph.EdgeWeight(3))
_ = g.AddEdge("london", "paris", graph.EdgeWeight(2))
_ = g.AddEdge("london", "madrid", graph.EdgeWeight(5))
_ = g.AddEdge("munich", "madrid", graph.EdgeWeight(6))
_ = g.AddEdge("munich", "paris", graph.EdgeWeight(2))
_ = g.AddEdge("paris", "madrid", graph.EdgeWeight(4))

Perform a Depth-First Search

This example traverses and prints all vertices in the graph in DFS order.

depth-first search

g := graph.New(graph.IntHash, graph.Directed())

g.AddVertex(1)
g.AddVertex(2)
g.AddVertex(3)
g.AddVertex(4)

_ = g.AddEdge(1, 2)
_ = g.AddEdge(1, 3)
_ = g.AddEdge(3, 4)

_ = graph.DFS(g, 1, func(value int) bool {
    fmt.Println(value)
    return false
})
1 3 4 2

Find strongly connected components

strongly connected components

g := graph.New(graph.IntHash)

// Add vertices and edges ...

scc, _ := graph.StronglyConnectedComponents(g)

fmt.Println(scc)
[[1 2 5] [3 4 8] [6 7]]

Find the shortest path

shortest path algorithm

g := graph.New(graph.StringHash, graph.Weighted())

// Add vertices and weighted edges ...

path, _ := graph.ShortestPath(g, "A", "B")

fmt.Println(path)
[A C E B]

Perform a topological sort

topological sort

g := graph.New(graph.IntHash, graph.Directed(), graph.PermitCycles())

// Add vertices and edges ...

order, _ := graph.TopologicalSort(g)

fmt.Println(order)
[1 2 3 4 5]

Perform a transitive reduction

transitive reduction

g := graph.New(graph.StringHash, graph.Directed(), graph.PermitCycles())

// Add vertices and edges ...

_ := graph.TransitiveReduction(g)

Prevent the creation of cycles

cycle checks

g := graph.New(graph.IntHash, graph.PermitCycles())

g.AddVertex(1)
g.AddVertex(2)
g.AddVertex(3)

_ = g.AddEdge(1, 2)
_ = g.AddEdge(1, 3)

if err := g.AddEdge(2, 3); err != nil {
    panic(err)
}
panic: an edge between 2 and 3 would introduce a cycle

Visualize a graph using Graphviz

The following example will generate a DOT description for g and write it into the given file.

g := graph.New(graph.IntHash, graph.Directed())

g.AddVertex(1)
g.AddVertex(2)
g.AddVertex(3)

_ = g.AddEdge(1, 2)
_ = g.AddEdge(1, 3)

file, _ := os.Create("./mygraph.gv")
_ = draw.DOT(g, file)

To generate an SVG from the created file using Graphviz, use a command such as the following:

dot -Tsvg -O mygraph.gv

Setting edge attributes

Edges may have one or more attributes which can be used to store metadata. Attributes will be taken into account when visualizing a graph. For example, this edge will be rendered in red color:

_ = g.AddEdge(1, 2, graph.EdgeAttribute("color", "red"))

To get an overview of all supported attributes, take a look at the DOT documentation.

Concepts

Hashes

A graph consists of nodes (or vertices) of type T, which are identified by a hash value of type K. The hash value is obtained using the hashing function passed to graph.New.

Primitive types

For primitive types such as string or int, you may use a predefined hashing function such as graph.IntHash – a function that takes an integer and uses it as a hash value at the same time:

g := graph.New(graph.IntHash)

This also means that only one vertex with a value like 5 can exist in the graph if graph.IntHash used.

Custom types

For storing custom data types, you need to provide your own hashing function. This example function takes a City and returns the city name as an unique hash value:

cityHash := func(c City) string {
    return c.Name
}

Creating a graph using this hashing function will yield a graph with vertices of type City identified by hash values of type string.

g := graph.New(cityHash)

Traits

The behavior of a graph, for example when adding or retrieving edges, depends on its traits. You can set the graph's traits using the functional options provided by this library:

g := graph.New(graph.IntHash, graph.Directed(), graph.Weighted())

Documentation

The full documentation is available at pkg.go.dev.

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A library for creating generic graph data structures and modifying, analyzing, and visualizing them.

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