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https://github.com/bitwalker/libgraph

A graph data structure library for Elixir projects
https://github.com/bitwalker/libgraph

data-structures elixir graphs

Last synced: 4 days ago
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A graph data structure library for Elixir projects

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README 

        
# libgraph



[![Master](https://travis-ci.org/bitwalker/libgraph.svg?branch=master)](https://travis-ci.org/bitwalker/libgraph)

[![Hex.pm Version](http://img.shields.io/hexpm/v/libgraph.svg?style=flat)](https://hex.pm/packages/libgraph)

[![Coverage Status](https://coveralls.io/repos/github/bitwalker/libgraph/badge.svg?branch=master)](https://coveralls.io/github/bitwalker/libgraph?branch=master)



[Documentation](https://hexdocs.pm/libgraph)



## About



This library provides:



- An implementation of a graph datastructure, `Graph`, designed for both directed and undirected graphs. The API supports

  undirected graphs, but I'm still getting the tests updated to cover properties of undirected graphs.

- A priority queue implementation `PriorityQueue`, oriented towards graphs (it prioritizes lower integer values over high),

  it is the fastest priority queue I know of which allows arbitrary priorities, and is more or less at parity with

  `pqueue3` from [the pqueue library](https://github.com/okeuday/pqueue/), which supports priorities from 0 to 65535.

- An idiomatic Elixir API for creating, modifying, and querying its graph structure. Creating and modifying a graph

  can be done in a single pipeline, and all queries take a Graph as their first parameter (one of my complaints with `:digraph`

  is that there is some inconsistency with the API between `:digraph` and `:digraph_utils` for no apparent reason).

- Two "Reducer" implementations for mapping/reducing over a graph. I am trying to figure out the best way to make these

extendable and part of the API, so that you can drop in your own shortest path algorithms, etc - but I have yet to come up with an

approach that feels good on that front.

- A `Serializer` behaviour, for defining custom serialization of graphs, with a Graphviz DOT format serializer

  provided out of the box.



It is backed by a large suite of tests, including several QuickCheck properties for the graph model. Its

API shares some similarity with `:digraph`, but diverges in favor of a more idiomatic Elixir interface. In

addition, over time I'm adding new functions to query the graph in ways not previously supported via `:digraph`,

and introducing support for classifying a graph as undirected if so desired, so that queries over such graphs

become easier.



If you are interested in reading more about how you can make use of `libgraph`, 

there is an [excellent blog post](https://medium.com/@tonyhammond/native-graph-data-in-elixir-8c0bb325d451) written by Tony Hammond

which is a very helpful walkthrough of the library and what can be built with it.



## Installation



If [available in Hex](https://hex.pm/docs/publish), the package can be installed

by adding `libgraph` to your list of dependencies in `mix.exs`:



```elixir

def deps do

  [{:libgraph, "~> 0.16.0"}]

end

```



## Rationale



The original motivation for me to start working on this library is the fact that `:digraph` requires a

minimum of 3 ETS tables per graph, and up to 6 depending on the operations you are performing on the graph.

If you are working with a lot of graphs concurrently, as I am, this means you can find yourself in a situation

where you hit the system limit for the maximum number of ETS table, and bring your system down. Seeing as how

it is ridiculous that trying to use a simple graph could potentially kill my system, and not wanting to hack

around the problem, I decided to see if I could build an alternative which was competitive performance-wise,

without requiring any ETS tables at all.



The result turned out better than I hoped - it is possible to build a graph datastructure without ETS that

is both equally performant (and in many of my benchmarks, better performing), and supports all of the same

functionality.



Additionally, I also had a few other things I wanted to address:



- Inconsistency with argument order in the API between `:digraph` and `:digraph_utils`

- The fact that there are two modules to work with the same datastructure to begin with, and trying to remember

  what lives where.

- The lack of extensibility, for example, there is no API with which you can implement your own

  traversal algorithms. This means you are stuck with whatever way the Erlang maintainers decided was

  ideal, regardless of whether it suits your use case or not. A great example is single-source shortest path

  algorithms, where you may want a simple breadth-first search, or perhaps you want to use Dijkstra's algorithm -

  you are stuck with just one approach with `:digraph`, which as I understand it, is a breadth-first search.

- `:digraph` as the name implies, only supports directed graphs

- `:digraph` graphs are unweighted, with no way to supported weighted graphs

- `:digraph` graphs are not "inspect-friendly", you get a tuple with the underlying ETS table ids, but that's it,

  not necessarily a big deal, but it's nice for playing around in the shell if you can see how your code affects the

  structure.

  

My speculation as to why `:digraph` is the way it is, is that when `:digraph` was originally written, there was

no efficient key/value datastructure in Erlang that could support large numbers of keys. At that time, maps

weren't even a speck in the eye of the language maintainers. Even after the initial introduction of maps in OTP 18,

maps still weren't efficient enough to work with large numbers of keys. It wasn't until OTP 19 that the performance

of maps with millions of keys became reasonable. So, it's not that `:digraph` sucks - it was the best possible implementation

at the time; but now that the language has come so far, we can take advantage of some of the new hotness and reinvent

it from the ground up :).



## Benchmarks



Feel free to take a look under the `bench` folder in the project root. There a few benchmarks I threw together to

keep an eye on a few key areas I wanted to ensure parity with `:digraph` on. You can run them yourself as well, but

I would encourage you to use them as a template to construct a benchmark based on your own use case, and compare them

that way, as it will give you a better basis to make your decision on. However, if you do find that `libgraph` is behind

`:digraph` with a benchmark, please let me know so that I can improve the library!



NOTE: While this library is primarily focused on the `Graph` data structure it defines, it also contains an implementation

of a priority queue (you can find it under the `PriorityQueue` module), designed for use with graphs specifically, as it

considers lower integer values higher priority, which is perfect for the kinds of graph algorithms you need a priority queue for.



## Contributing



To run the test suite you will need to run `mix eqc.install --mini` once you've cloned the repo and fetched dependencies.



If you have changes in mind that are significant or potentially time consuming, please open a RFC-style PR first, where we

can discuss your plans first. I don't want you to spend all your time crafting a PR that I ultimately reject because I don't

think it's a good fit or is too large for me to review. Not that I plan to reject PRs in general, but I have to be careful to

balance features with maintenance burden, or I will quickly be unable to manage the project.



Please ensure that you adhere to a commit style where logically related changes are in a single commit, or broken up in a way that

eases review if necessary. Keep commit subject lines informative, but short, and provide additional detail in the extended message text

if needed. If you can, mention relevant issue numbers in either the subject or the extended message.



## Roadmap



Please open an issue if you have a feature request!



## License



MIT (See the LICENSE file)