Dart Isolates give you a way to perform real multi-threading in Dart applications, the ability to truly run code on another thread. (For more information on that statement, see Dart futures are NOT run in a separate thread.)
When I first read that Isolates were like actors I was very interested in them, but then I was surprised to see that (IMHO) they are implemented in a more low-level/primitive way than something like the Akka Actors library. (The entrepreneur out there might see this as an opportunity to create an Akka-like port for Dart and Flutter.)
I’ve been working with Flutter and Dart for several weeks now, and I was surprised to read several times that Dart is single-threaded, knowing that it has a concept of a Future (or futures) and async methods. Last night I read this excellent article about Dart’s event loop, which sums up Dart futures very nicely in that statement:
“the code of these Futures will be run as soon as the Event Loop has some time. This will give the user the feeling that things are being processed in parallel (while we now know it is not the case).”
Earlier in the article the author also states:
“An async method is NOT executed in parallel but following the regular sequence of events, handled by the Event Loop, too.”
So, in summary, Dart has a single-threaded event loop, and futures and async methods aren’t handled by a separate thread; they’re handled by the single-threaded event loop whenever it has nothing else to do.
I just wanted to note this here for myself today, but for many more details, please see that article, which also discusses Dart isolates, which are like a more primitive form of Akka actors.
Table of Contents
- Run one task, but block
- Run one thing, but don’t block, use callback
- The onSuccess and onFailure callback methods
- Creating a method to return a Future[T]
- How to use multiple Futures in a for loop
- A future and ExecutionContext
- Callback methods
- For-comprehensions (combinators: map, flatMap, filter, foreach, recoverWith, fallbackTo, andThen)
- See Also
You want a simple way to run one or more tasks concurrently in a Scala application, including a way to handle their results when the tasks finish. For instance, you may want to make several web service calls in parallel, and then work with their results after they all return.Back to top
Future gives you a simple way to run an algorithm concurrently. A future starts running concurrently when you create it and returns a result at some point, well, in the future. In Scala, it’s said that a future returns “eventually.”
I’ll write more about this shortly, but yesterday I created a little video of a demo application I call Futureboard. It’s a Scala/Swing application, but it works like Flipboard in that it updates a number of panels — in this case Java JInternalFrames — simultaneously every time you ask it to update.
The “update” process works by creating Scala futures, one for each internal frame. When you select File>Update, a Future is created for each news source, and then simultaneous calls are made to each news source, and their frames are updated when the data returns. (Remember that Futures are good for one-shot, “handle this relatively slow and potentially long-running computation, and call me back with a result when you’re done” uses.)
Here’s the two-minute demo video:
In this short blog post I will try, in 10 minutes or less, to present what Monix library is and convince you that it is good to know it.
Formerly known as Monifu, Monix is a library for asynchronous programming in Scala and Scala.js
typelevel.org has a nice article on shared state in functional programming.
“In Erlang, processes share no memory and can interact with each other only by sending messages. This is exactly how objects in the real world behave.”
“Processes interact by one method, and one method only, by exchanging messages. Processes share no data with other processes. This is the reason why we can easily distribute Erlang programs over multicores or networks.”
Joe Armstrong, in his book,
Programming Erlang: Software for a Concurrent World
“In Erlang (Akka), it’s OK to mutate state within an individual process (actor), but not for one process to tinker with the state of another process.”