Gigahorse 0.3.0


Gigahorse 0.3.0 is now released. See documentation on what it is.

OkHttp support

0.3.0 adds Square OkHttp support. Gigahorse-OkHttp is availble for Scala 2.10, 2.11, and 2.12.

According to the JavaDoc you actually don't have to close the OkHttpClient instance.

scala> import gigahorse._, support.okhttp.Gigahorse
import gigahorse._
import support.okhttp.Gigahorse
scala> import scala.concurrent._, duration._
import scala.concurrent._
import duration._

sbt 1.0 roadmap and beta-1


Wrote sbt 1.0 roadmap and beta-1 on Tech Hub blog.

downloading and running app on the side with sbt-sidedish


I've been asked by a few people on downloading JARs, and then running them from an sbt plugin.
Most recently, Shane Delmore (@shanedelmore) asked me about this at nescala in Brooklyn.

During an unconference session I hacked together a demo, and I continued some more after I came home.


herding cats: day 16


Contraband, an alternative to case class


Here are a few questions I've been thinking about:

  • How should I express data or API?
  • How should the data be represented in Java or Scala?
  • How do I convert the data into wire formats such as JSON?
  • How do I evolve the data without breaking binary compatibility?

limitation of case class

The sealed trait and case class is the idiomatic way to represent datatypes in Scala, but it's impossible to add fields in binary compatible way. Take for example a simple case class Greeting, and see how it would expand into a class and a companion object:


The state of sbt 0.13, sbt server, and sbt 1.0


I gave a talk at ScalaSphere with Dale Wijnand (@dwijnand). The state of sbt 0.13, sbt server, and sbt 1.0 (ScalaSphere ver):

Gigahorse 0.2.0


Gigahorse 0.2.0 is now released. The new change is that it abstracts over two backends. @alexdupre contributed migration from AHC 1.9 to AHC 2.0, which is based on Netty 4 in #12.

In addition, there's now an experimental Akka HTTP support that I added. #15

Please see Gigahorse docs for the details.

gigahorse-github 0.1.0


gigahorse-github 0.1.0 is released. This is a Gigahorse plugin for Github API v3.

Here’s a quick example of how to get repository info:

scala> import gigahorse._, gigahorse.github.Github, scala.concurrent._, duration._
scala> val client = Github.localConfigClient
client: gigahorse.github.LocalConfigClient = LocalConfigClient(OAuthClient(****, List(StringMediaType(application/json), GithubMediaType(Some(v3),None,Some(json)))))
scala> Gigahorse.withHttp { http =>
         val f ="eed3si9n", "gigahorse-github")), Github.asRepo)
         Await.result(f, 2.minutes)
res0: gigahorse.github.response.Repo = Repo(, gigahorse-github, 64614221, User(, eed3si9n, 184683, Some(, Some(, Some(), Some(User), Some(true), None, None), eed3si9n/gigahorse-github, Some(Gigahorse plugin for Github API v3),...

If you're interested in gigahorse-github itself, README contains the full documentation.

extending Gigahorse

I also wrote Extending Gigahorse page describing the overview of how to write a Gigahorse plugin, which is more or less the same as how one would write a Dispach plugin. As I wrote there, the JSON data binding is auto generated from a schema.

For me, gigahorse-github was as much a proof of concept for sbt-datatype as it was for Gigahorse. It did end up exposing minor bugs on all components along the stack, so it was a fruitful exercise.

Gigahorse 0.1.0


Update: please use Gigahorse 0.1.1

Gigahorse 0.1.0 is now released. It is an HTTP client for Scala with Async Http Client underneath. Please see Gigahorse docs for the details. Here's an example snippet to get the feel of the library.

scala> import gigahorse._
scala> import scala.concurrent._, duration._
scala> Gigahorse.withHttp(Gigahorse.config) { http =>
         val r = Gigahorse.url("").get.
             "q" -> "1 + 1",
             "format" -> "json"
         val f =, Gigahorse.asString andThen {_.take(60)})
         Await.result(f, 120.seconds)

registry and reference pattern


There's a "pattern" that I've been thinking about, which arises in some situation while persisting/serializing objects.

To motivate this, consider the following case class:

scala> case class User(name: String, parents: List[User])
defined class User
scala> val alice = User("Alice", Nil)
alice: User = User(Alice,List())
scala> val bob = User("Bob", alice :: Nil)
bob: User = User(Bob,List(User(Alice,List())))
scala> val charles = User("Charles", bob :: Nil)
charles: User = User(Charles,List(User(Bob,List(User(Alice,List())))))
scala> val users = List(alice, bob, charles)
users: List[User] = List(User(Alice,List()), User(Bob,List(User(Alice,List()))),

The important part is that it contains parents field, which contains a list of other users.
Now let's say you want to turn users list of users into JSON.

[{ "name": "Alice", "parents": [] },
{ "name": "Bob",
  "parents": [{ "name": "Alice", "parents": [] }] },
{ "name": "Charles",
  "parents": [{ "name": "Bob", "parents": [{ "name": "Alice", "parents": [] }] }] }]
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