lucidsoftware / lucid-android   0.10.1

Apache License 2.0 GitHub

A small collection of useful classes and helpers for using Scala on Android.

Scala versions: 2.11


Build Status

Lucid Android is designed to consolidate scala helpers for developing Android applications.

The following features are available:

  1. A logging trait
  2. A lifecycle management macro
  3. Android-centric ExecutionContexts
  4. View event handlers
  5. Javascript execution helpers


In Android when you want to log something like an error, you have to provide a tag for the log statement. Lucid Android provides to simplify this process. It is fairly common to use the current class name when tagging logs. If you extend DefaultLogTag, the class name log tag is automatically generated as an implicit value for you.

This log tag works with the trait, to allow easy logging with dependency injection. For example:

class Example(logger: Logger) extends DefaultLogTag {
  logger.debug("a debug statement")

For the default Android mapping of methods, you can use the class. To add the logger as a protected val of your class, you can use the trait

class MainActivity extends Activity with DefaultAndroidLogging {
  override def onCreate(state: Bundle): Unit = {
    logger.debug("a simple debug statement")


The mapping from Android's Log methods to DefaultAndroidLogger is as follows:

Log.d -> debug

Log.e -> error

Log.i -> info

Log.v -> verbose

Log.w -> warn -> wtf

You can extend the Logger trait or the DefaultAndroidLogger class to provide custom logging behavior (like sending logs to a server).

Lifecycle Mangement

A common pattern in Android is to create vars that get initialized during a particular lifecycle method:

class MainActivity extends Activity {

  var prefs: SharedPreferences = null

  override def onCreate(state: Bundle): Unit = {
    prefs = getSharedPreferences("prefs", Context.MODE_PRIVATE)


The downside here is that if you access prefs at the wrong time, you will get a NullPointerException. For onCreate that might not be so much of an issue, but for other lifecycle methods like onActivityCreated (for fragments) or onResume you have to be even more careful about when you access the value. You are also introducing mutable data. This is generally discouraged in scala.

The annotation helps address this by allowing you to annotate top-level members with the lifecycle method they should be initialized in. A new type is introduced to help with debugging and provide some guarantees around accessing lifecycle managed members. The above example becomes:

class MainActivity extends Activity {

  val prefs = LifecycleValue[SharedPreferences](getSharedPreferences("prefs", Context.MODE_PRIVATE))


Since the type of prefs is LifecycleValue[SharedPreferences] you have to "unwrap" the value to access it in a way that isn't too different from an Option:

prefs.require { p =>
  // p is the SharedPreferences here

LifecycleValue.require is analogous to By default, when the value hasn't been initialized an error (with a stacktrace) is logged, using an implicit and, and the body of the require call is skipped.

Unfortunately, it's sometimes necessary to return the value you want to store in a LifecycleValue in one of the lifecycle methods. For instance, it's common to store a reference to the views from onCreateView. However, accessing a LifecycleValue's wrapped value as a return value in that method would essentially require using option.get, an anti-pattern and an inconvenience. Additionally, creating the views in onCreateView requires the view inflater and container which are passed in as arguments to the method. A LifecycleValue defined externally to that method would have no way to access those arguments. For these instances you can use a different version of the LifecycleManaged macro.

class ExampleFragment extends Fragment {
  val view = new EmptyLifecycleValue[View](Lifecycles.OnCreateView, Build.DEBUG) with Logging

  override def onCreateView(inflater: LayoutInflater, container: ViewGroup, state: Bundle): View = {
    val rootView = inflater.inflate(, container)


The initLifecycleValue annotation allows the LifecycleValue to be initialized in the correct context without unnecessarily wrapping and unwrapping the value. Furthermore, the LifecycleValue can only be initialized once in its respective method, and it must be initialized. This allows it to be treated in the same manner as LifecycleValues created directly on the class.

When creating a lifecycle value, sometimes you will have to reference other lifecycle values. To facilitate this kind of composition, a cats.Monad instance is provided for LifecycleValue. Operations like map and flatMap demonstrate the same behavior as require (map is identical, in fact) but have the type semantics that you would except from those methods.

Values can be composed in a few different ways:

val prefs = LifecycleValue[SharedPreferences](getSharedPreferences("prefs", Context.MODE_PRIVATE))

// import cats.syntax.functor._
val settings: LifecycleValue[CustomSettings] = CustomSettings(_))

// import cats.syntax.apply._
val unrelatedDeps: LifecycleValue[HasDependencies] = (prefs, settings).mapN((p, s) => new HasDependencies(p, s))

// import cats.syntax.functor._
// import cats.syntax.flatMap._
val multipleDeps2: LifecycleValue[HasOtherDeps] = for {
  prefs <- prefs
  settings <- LifecycleValue(new CustomSettings(prefs))
} yield new HasDependencies(prefs, settings)

It's important to take care when mixing lifecycles that you only depend on data from lifecycles that are the same as or happen earlier than the current lifecycle. You wouldn't want an @onCreate value depending on an @onStart value but the other way around is okay.

You can also customize some behavior of @LifecycleManaged. It currently supports specifying the debug parameter:

  debug = true

When debug is set to true (default is false), the app will crash when a LifecycleValue is accessed before that lifecycle has been hit. It is common to set this value to BuildConfig.DEBUG:

  debug = BuildConfig.DEBUG

A crash is often much easier to notice in development than an error log but you wouldn't necessarily want the user to experience the crash in cases where it accidentally leaks into production.


Typically to run something asynchronously in Android it is typical to leverage AsyncTask. For simple operations where you don't need fine grained control over reporting progress and want to avoid the boilerplate (and weirdness) around passing data into a call to an AsyncTask you probably will have a much better experience using Scala's Future.

You will need an ExecutionContext to do this successfully. Lucid Android provides two options: AsyncTaskExecutionContext and UiThreadExecutionContext. will run tasks on the same background thread pool that AsyncTask uses. UiThreadExecutionContext is a trait that provides an ExecutionContext that processes tasks on the main thread. This is useful for switching back to the UI thread when you need to update ui. Only is marked as implicit. This example runs getUserDataFromNetwork() on a background thread and then switches to the UI thread in .onComplete.


class MainActiivty extends Activity with UiThreadExecutionContext with DefaultLogging {
  override def onCreate(state: Bundle): Unit = {

    Future(getUserDataFromNetwork()).onComplete {
      case Success(userData) => updateUi(userData)
      case Failure(e) => error("something bad happened", e)

Note that UiThreadExecutionContext can only be mixed in to an activity that also mixes in Logging.

Event handlers

All View.setOn*Listener methods that take an interface with a single method can be called with View.on* passing in an anonymous method with the same parameters as the single interface method:

val button: Button = ???
button.onClick { view =>
  // on click logic here

Javascript Execution Helpers

Under import a new string interpolater is introduced for safely interpolating scala values into javascript function parameters. Typically if you have a javascript function that takes a string like this:

function jsFunction(str) { /* ... */ }

When an Android application needs to call this function passing in a Scala string you will end up with something like this:

val value = "hello"
webView.evaluateJavascript(s"""jsFunction("$value")""", null)

You have to manually add the quotes. Because of some weird parsing issues with Scala you are also required to use the triple quoted strings in the example above (escaping the quotes around an interpolated value doesn't work).

Lucid Android adds the js interpolater and the JsParameter type class to simplify this a little bit and make it safer at compile time. The above evaluateJavascript call can be rewritten as follows:

val value = "hello"
webView.evaluateJavascript(js"jsFunction($value)", null)

Because an implicit JsParameter[String] is available, the js interpolator can translate this call into syntactically valid javascript (adding the quotes in this case). Numbers, booleans, and collections all work correctly as well. You can also provide implict instances of JsParameter[A] for custom types you'd like to be able to interpolate. Collections were the original motivation for this:

val list = List("hello", "world")
val jsList = => "\"" + str + "\"").mkString("[", ",", "]")
webView.evaluateJavascript(s"jsFunction($jsList)", null)

Gets translated into simply:

val list = List("hello", "world")
webView.evaluateJavascript(js"jsFunction($list)", null)

The js interpolator returns a JsInterpolatedString. At compile time this is a simple wrapper for a (and subclass of) String. At runtime, the extra allocation of the wrapper doesn't actually happen so memory allocations are not negatively impacted when using js. See scala-newtype for more details. You do end up with an extra allocation of a JsParameter when interpolating collections.


// build.sbt
libraryDependencies += "com.lucidchart" %% "lucid-android" % "0.9.0"

// if you are using @LifecycleManaged
addCompilerPlugin("org.scalamacros" % "paradise" % "2.1.0" cross CrossVersion.full)