Why Elm is awesome for building a static site framework

Dillon Kearns

Isomorphic by design#

With JavaScript-based frameworks, the Node and Browser ecosystems are intertwined. In fact, it's not uncommon to include shims for Node's filesystem package to make NPM packages run on the browser.

The main places these language features happen are:

  • Global variables (like window vs. globals)
  • Import syntax (require vs. import)
  • Runtime-specific bindings (like fetch, fs.writeFile, localStorage)

For an Elm-based framework, there is a lot less to think about here because:

  • Elm doesn't have global variables (everything must be passed in explicitly)
  • Elm doesn't have different import syntax options
  • Elm has managed effects, i.e. side-effects as data - you can't run side-effects anywhere, so elm-pages is able to explicitly choose what side-effects can happen and from where

Determinism#

You can be sure that you don't depend on environment, you can pass in exactly what the use should have access to and that's all their code can depend on. No need to have discipline, the types give guardrails and then you can do anything you want within them.

Elm is amazing for transforming data#

Validate data for more guarantees#

Not only is Elm amazing at working with and transforming data, but it excels at giving guarantees. Once you've checked the data's integrity, you can represent that with the type (think a ValidatedEmail type, or a NonEmptyList). Ideally, you will [[make-impossible-states-impossible]] in the process.

Once your elm-pages build command succeeds, you know that all of your validations checked out!

Often Elm code will use the pattern to [[conditionally return a validated type]]. This is great because you can provide strong guarantees that your Elm type is valid and then work with it beyond that point. But it's not good because you split your code into lots of code paths, and you have no way to guarantee that the user won't go down the bad code paths - you just know that if they do, those bad cases are handled explicitly, and you won't get any implicit failures where things silently fail in surprising ways.

Elm is great at giving you errors up front because it checks the contract before passing data along. For example, with a JSON decoder, the decoding fails if there is an unexpected null anywhere. This means you can trust your data integrity before you ever pass it down the line. You don't have to wonder whether you ran through the right code paths to find out whether there was a problem with your data or not. This pairs even better with elm-pages because you can find out about these problems at build-time rather than at runtime!

Elm combined with a build phase, like elm-pages provides, is an incredible combination because now you can guarantee the happy code path! For pre-rendered pages, you know that the data was solid if the build succeeded. The error code paths are easily handled because you can use DataSource.fail to give a custom build error message at any point. Or if anything goes wrong reading a file, decoding frontmatter, performing an HTTP DataSource, then you handle that error as a build error, not an error code path that the user may encounter.

elm-pages can also give you great error feedback for free. In the dev server, any time you change your Elm code you get quick feedback showing you any DataSource failures for the current page. In a regular application, you would need to do some wiring to present these errors in a usable way, but with the elm-pages architecture it comes for free as part of the core experience.

Easier wiring#

Elm's sound type system, immutability, and explicitness (no magic) make it very easy to trace code. With elm-pages, you get those same benefits for reasoning about your code, but the abstraction of a DataSource gives you a declarative way to wire in that type-safe data with a lot less wiring.

Optimizing Data#

Because we write our JSON decoders explicitly in Elm, we can use the step of building up a Decoder to also keep track of which fields are used, then discard all unused data in our build step. This is exactly what the OptimizedDecoder API does in elm-pages. This also has the benefit that any sensitive data that comes back from an API response can only end up on a pre-rendered page if we explicitly include it in our JSON decoder, because we're not pulling in full API responses, we're pulling in just the data we decode from our API responses.

Note: this is only for build-time data. Since there's a build step, and we're including our DataSources on the page during this stage, we know at build time exactly what data we will use. At runtime, elm-pages gives you a regular Elm app, so you can pull in any data you want dynamically at runtime and it works exactly as it would in a vanilla Elm app.

Nice APIs for extracting the data you need#

I really enjoy working with data in Elm because you can think of individual parts independently, and compose them together. You can split off the data you want in a type-safe way.

Take regex captures, for example.

const regexpSize = /([0-9]+)×([0-9]+)/;
const match = imageDescription.match(regexpSize);
console.log(`Width: ${match[1]} / Height: ${match[2]}.`);

This is pretty quick to write, but becomes hard to maintain over time.

In elm-pages, we could grab all of our blog post markdown files in our my-blog-posts folder, and we can also

blogPosts =
Glob.succeed (\slug -> Route.Blog__Slug_ { slug = slug })
|> Glob.match (Glob.literal "my-blog-posts/")
|> Glob.capture Glob.wildcard
|> Glob.match (Glob.literal ".md")
|> Glob.toDataSource

If our filenames are in snake_case, but we want our URL slugs in kebab-case, then we could transform it in-place

blogPosts =
Glob.succeed (\slug -> Route.Blog__Slug_ { slug = slug })
|> Glob.match (Glob.literal "my-blog-posts/")
|> Glob.capture (Glob.map snakeCaseToKebabCase Glob.wildcard)
|> Glob.match (Glob.literal ".md")
|> Glob.toDataSource