How do static site generators work? That’s the question I had when I began building my own static site generator for learning purposes.

With over 100 static site generatores listed on staticgen.com, there must be something interesting going on there.

This post looks at a 2 popular static site generators, Jekyll and Hakyll, and dig into their inner workings.


Build a Configuration, create a Site, call Reader, run Generator, run Converter, write to disk.

Jekyll is really easy to use, you install the gem, run Jekyll from the command line, and it will generate your site into the _site folder.

$ jekyll build

The build command is found in build.rb. There are 3 top level steps are:

  1. Build a Configuration
  2. Initialize a Site with configuration
  3. Calls process on Site object

In this single command we see the 2 most important classes in Jekyll: Configuration and Site.

A Configuration specifies where to find your files, plugins, layouts, data, where to write output, etc.

A Site is the orchestrator object that knows how to call other classes to build a site. The main method of Site is process, and it shows clearly the steps taken.

  1. reset
  2. read
  3. generate
  4. render
  5. cleanup
  6. write
  7. print_stats

Let’s dive deeper in to some of the more interesting methods.


Jekyll knows about different kinds of files, such as layout, data, collections, posts, pages. The class that does this work is Reader. Each of this file has a specialized class to take care of finding the file and reading it, for example PostReader, DataReader, PageReader, etc. They can be found in readers. File contents are read into attributes on the Site object.


Renderer takes the file contents read in by the readers and run them through converters. Converters can do things like convert markdown to html, or render templates using liquid renderer.


PluginManager uses ruby’s require feature to load plugins from _plugins, as gems specified in _config.yml, or gems specified in Gemfile. Plugins are initialized when initializing Site.

To write a plugin, you can extend various Jekyll base classes, such as Generator, Converter, and implementing some methods.


Hakyll relies heavily on the Haskell type system, if you are not familiar with Haskell at all, this might be a difficult read. I try to describe things without talking too much about types, so I hope it is still understandable.

Hakyll takes a different approach of building your site.

You first install Hakyll using stack, and use hakyll to initialize a site, which will generate a simple site.hs.

This file is the entry point for configuring your build. You write haskell, calling classes and functions provided by the Hakyll library, but it looks like you’re configuring because Hakyll provides a DSL that makes it look like you’re configuring your build. Finally, to build your file, you run that configuration using stack.

By default, files are read from current directory and written to _site/.

Again, we’ll take a top down approach.

In haskell, the main function is called main, and in this case it is calling hakyllWith with a Configuration and Rules.

If you are unfamiliar with haskell, the $ basically means, “evaluate everything to my right first”

If we trace hakyllWith, we find that it eventually calls Runtime.run with a Configuration, Logger, and Rules.

We can think of Rules as a set of rules, which is made up of

  1. Match pattern (match),
  2. Route (route), and
  3. Compiler (compile)

A match pattern specifies glob expressions to match file paths.

A route specifies where to write output to.

A compiler specifies what to do to the input before writing it out.

These 3 functions are defined in Core/Rules.hs.

If we look at the types of these 3 functions, they all return Rules (). You can find the definition of Rules in Core/Rules/Internal.hs>

The definition looks strange, but I think of Rules as an abstract data type that contains computation.

All computations can read from a shared enviroment, output to a shared space, and share state.

In that way, Rules is a composite data structure, made up of 3 other types:

  1. RulesRead - shared environment that values can be read from
  2. RuleSet - place where computation can write output
  3. RulesState - the current status of computation

route and compile set the state (RulesState), setting the current route and compiler to use.

match fills up the RuleSet structure, which is made up of routes, compilers, resources and pattern, then clears the state (RulesState). A list of matched Identifiers is retrieved from the environment. A route is retrieved from RulesState that route set up, and added to the RuleSet. The compiler is retrieved from the RulesState that compile set up, and a compiler is assigned to each matched Identifier. This mapping is set on RuleSet.

The multiple match expressions all return Rules, and I like to think that all the Rules are squashed into a single Rules, like how many Int can be summed into a single Int.

Finally after all this explanation, we return to the run function. At this point we have a RuleSet to work with, and using that we build a Runtime.

Runtime is similar to Rules in that it has 3 components:

  1. RuntimeRead - shared environment
  2. () - place to output to, in this case this means that we don’t save the output
  3. RuntimeState - current status of computation

run eventually calls build which calls pickAndChase.

chase will pick from a list of Identifier that represents todos, and try to run the compiler on it.

A compilation can be successful, in that case the we can write routes, save to store (cache), and update states. If this compilation requires some dependency, then run the dependencies first.

When all this completes running, you’ll have your input files transformed by the specified compilers, and written to paths specified by your route!