Async Virtual Collections

Note this is a Work In Progress feature

In most applications the UI shows only a small fraction of the data residing on the server. For example in GitHub you have organizations that have repositories that have issues that consist of events. The data can be viewed as a large, directional graph or a hierarchy. At any point of time, the UI requires just a small subset of this graph to be able to display the data correctly.

Making explicit calls for data is both tedious and bad for performance, because the client is doing no caching whatsoever. Adding caching makes requests even more tedious and also error prone. Systems like GraphQL and Falcor work around these problems by presenting the data as virtual collections.

As we already have the application model represented as an immutable hierarchy, wouldn't it be nice to automatically represent data on the server in the model itself?

Pot Collections

Diode defines a PotCollection[K, V] trait which is implemented in PotMap and PotVector. These represent virtual collections where the data is fetched asynchronously when needed. Collections do not handle fetching themselves, but require an implementation of the Fetch[K] trait to be passed in the constructor.

PotCollection works much like a normal immutable Scala collection as you can get values, remove them and get an updated collection with new values. In addition to these basic features there are also methods for refreshing the content of selected values. Note that PotCollection does not implement any of the Scala collection traits, so they are not compatible with native collections as such. For example get returns a Pot[V] instead of an Option[Pot[V]] as a normal collection would.

The values in PotCollection are always of type Pot[V], giving you the multi-state functionality you are already familiar with. If your application is already using Pot values, you can easily plug in PotCollections without much effort.


def renderUser(userId: String, users: PotMap[String, User]) = {
  users(userId).map { user =>
    div(span(cls := "name",, img(cls := "profile", src := user.picUrl))
  } getOrElse div()

In this example function the users collection is a PotMap using String as a key. We simply get the value out of the collection by using apply(key) and use map to transform it into a Scalatags element. In case there is no value (at the moment), an empty div is returned.

Assuming the userId does not exist in the PotMap, the call to apply (or get) will result in a call to fetch its content. As this is an asynchronous call (typically dispatching an appropriate action), we will not get the value right away but will return a Pending instead. When the fetch is completed, the PotMap is updated with the new value, which is returned in the next call to apply. As with Pots in general, a model update does not automatically trigger a view rendering, so you need to use a listener to track model changes.

Fetch Actions

As with a regular Pot it makes sense to use AsyncAction to handle the details of fetching data for a PotCollection. AsyncAction provides handlers for both PotMap and PotVector, to update values given a set of keys.

def mapHandler[K, V, A <: Traversable[(K, Pot[V])], M, P <: AsyncAction[A, P]](keys: Set[K])
  (implicit ec: ExecutionContext) = {
  (action: AsyncAction[A, P], handler: ActionHandler[M, PotMap[K, V]], updateEffect: Effect) => {
    import PotState._
    import handler._
    // updates/adds only those values whose key is in the `keys` set
    def updateInCollection(f: Pot[V] => Pot[V], default: Pot[V]): PotMap[K, V] = {
      // update existing values { (k, v) =>
        if (keys.contains(k))
      } ++ (keys -- value.keySet).map(k => k -> default) // add new ones
    action.state match {
      case PotEmpty =>
        updated(updateInCollection(_.pending(), Pending()), updateEffect)
      case PotPending =>
      case PotUnavailable =>
      case PotReady =>
      case PotFailed =>
        val ex = action.result.failed.get
        updated(updateInCollection(, Failed(ex)))

It works quite similarly to the regular AsyncAction.handler but instead of updating the whole collection, only a subset of values in the collection are updated, based on the set of given keys. The updateEffect must update values for all the keys, otherwise some of them will be left in Pending state. It's ok to have multiple simultaneous updates running for the same PotCollection but you should make sure they do not use overlapping key sets.

An example fetch implementation could be like following:

case class User(id:String, name: String)

// define a AsyncAction for updating users
case class UpdateUsers(
  keys: Set[String],
  state: PotState = PotState.PotEmpty,
  result: Try[Map[String, Pot[User]]] = Failure(new AsyncAction.PendingException)
) extends AsyncAction[Map[String, Pot[User]], UpdateUsers] {
  def next(newState: PotState, newValue: Try[Map[String, Pot[User]]]) =
    UpdateUsers(keys, newState, newValue)

// an implementation of Fetch for users
class UserFetch(dispatch: Dispatcher) extends Fetch[String] {
  override def fetch(key: String): Unit =
    dispatch(UpdateUsers(keys = Set(key)))
  override def fetch(keys: Traversable[String]): Unit =
    dispatch(UpdateUsers(keys = Set() ++ keys))

// function to load a set of users based on keys
def loadUsers(keys: Set[String]): Future[Map[String, Pot[User]]]

// handle the action
override def handle = {
  case action: UpdateUsers =>
    val updateEffect = action.effect(loadUsers(action.keys))(identity)
    action.handleWith(this, updateEffect)(AsyncAction.mapHandler(action.keys))

Pot Streams

Similar to PotCollection but with a slightly different API, Diode provides a PotStream for handling streaming data. Its use cases include things like chat room messages, monitoring events or infinite scrollers. Unlike PotMap or PotVector that allow more or less random access to the remote data, a PotStream always consists of consecutive entries with unique identifiers. The values stored in a PotStream are not automatically Pot[V]s but direct values because PotStream does not allow access to entries that are not currently present. You may of course choose to store Pot[V] if you wish to do so.

Each value in PotStream is wrapped in a StreamValue case class that provides indices to previous and next entries in the stream.

case class StreamValue[K, V](key: K, value: Pot[V], stream: PotStream[K, V], prevKey: Option[K], nextKey: Option[K])

You can call get(key) to get a reference to a StreamValue that you can use to navigate up and down the stream with next and prev methods. If you need to iterate over all present entries in the stream, use iterator to get an instance of Iterator[(K, V)]

To update data in a PotStream use update (only for existing entries), append or prepend. In a typical scenario the client is not directly adding new data to the stream but is requesting updates from the server, or updates are automatically delivered over WebSocket or so. The client can, however, initiate updates by calling refresh, refreshNext or refreshPrev methods.

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