Dart Language Asynchrony Support: Phase 2

Async*, sync*, and all the rest

Written by Gilad Bracha
March 2015

In a previous article, we discussed asynchronous methods and await expressions. These features are part of a complete initiative to support asynchronous programming and generators in Dart.


Dart 1.9 introduced generator functions. These are functions that lazily compute a sequence of results. There are two kinds of generators—synchronous and asynchronous. A synchronous generator produces values on demand—consumers pull the values from the generator. An asynchronous generator produces values at its own pace, and pushes them out where consumers can find them.

Why support generators in the language?

One can implement generators by hand, but that can be tricky and is certainly tedious.

To implement a synchronous generator, you need to define your own iterable class. You can subclass IterableBase but you’ll still need to declare the class and implement the iterator method which will have to return a new iterator. To do that, you’ll have to declare your own iterator class. You’ll need to implement the members moveNext() and current which track and update the position of the iterator, detecting when the you’ve reached the end of the underlying iterable (and whether it was empty to begin with). It’s no big deal—we know you love programming and this is a great CS101 exercise. However, maybe, just maybe, you want to spend your time programming something else. Synchronous generator functions are sugar for implementing such iterables.

Asynchronous generators are even more fun to write by hand. Instead of just boilerplate, you get to write tricky boilerplate. You have to ensure that everything works when your stream gets paused or canceled, for example.

Dart’s new built-in generator support makes things much easier, as we’ll see below.

Synchronous generators: sync*

Marking a function body with the sync* modifier identifies the function as a synchronous generator, and relieves the programmer of much of the boilerplate involved in defining an iterable manually.

Suppose we want to produce the first n natural numbers. It is quite easy to do this with a synchronous generator.

Iterable naturalsTo(n) sync* {
  int k = 0;
  while (k < n) yield k++;

When called, naturalsTo immediately returns an iterable (much like a function marked async immediately returns a future), from which you can extract an iterator. The body of the function won’t start running until one calls moveNext on that iterator. It will run until it hits the yield statement the first time. The yield statement contains an expression, which it evaluates. Then, the function suspends, and moveNext returns true to its caller.

The function will resume execution the next time moveNext is called. When the loop ends, the method implicitly executes a return, which causes it to terminate. At that point, moveNext returns false to its caller.

Using ordinary iterators, this can be surprisingly tedious, as one has to define specialized iterator and iterable classes and implement the complete Iterable API.

The devil’s details

You can separate the sync from the *; they are distinct tokens. If you have existing code that used sync as an identifier, you can continue to do so. The word sync is not a true reserved word. Similar comments apply to async, await, and yield. They are only treated as reserved words inside asynchronous or generator functions (i.e., those marked async, sync* or async*).

Bear in mind that this adherence to strict compatibility comes at a cost. Say you forget to use a modifier such as sync* on a function, and use a yield statement inside. The parser may get very confused and give rather bewildering error messages.

Asynchronous generators: async*

To asynchronously produce a sequence, we use streams. One can implement streams manually using Stream and allied classes. Asynchronous generator functions are sugar for implementing such streams. Marking a function body with the async* modifier identifies the function as an asynchronous generator.

Let’s try generating natural numbers again, asynchronously this time.

Stream asynchronousNaturalsTo(n) async* {
  int k = 0;
  while (k < n) yield k++;

Invoking this function immediately returns a stream—just as invoking a sync* function immediately returns an iterable, and invoking an async function immediately returns a future (perhaps you discern a pattern here).

Once you listen to the stream, execution of the body begins. When the yield statement executes, it adds the result of evaluating its expression to the stream. It doesn’t necessarily suspend (though in the current implementations it does).

In any event, whatever function is listening on the stream will get called with each new value at some point. The initiative is not the consumer’s, however; the stream pushes the value to the listener function at its pleasure.

Fine print

As a variant, consider

Stream get naturals async* {
  int k = 0; while (true) { yield await k++; }

This example raises an interesting question: since the code runs in a tight, infinite loop and yield doesn’t suspend, when is any listener going to get to run to look at the results? We could require that yield always suspend, but that can hurt performance. The only requirement is that the function does suspend eventually so that some other code can run and pull values out of the stream.

The stream associated with an async* function could get paused or canceled. If an async* function executes a yield and its stream has been canceled, control transfers to the nearest enclosing finally clause. If the stream has been paused, execution suspends before the yield, until the stream is resumed. Refer to the Dart language spec for all the gory details.


As every Dart programmer knows, the for-in loop plays well with iterables. Similarly, the await-for loop is designed to play well with streams.

Given a stream, one can loop over its values:

await for (int i in naturals) { print(‘event loop $i’); }

Every time an element is added to the stream, the loop body is run. After each iteration, the function enclosing the loop suspends until the next element is available or the stream is done. Just like await expressions, await-for loops can only appear inside asynchronous functions.


While the use of yield is attractive, you can run into problems. If you are writing a recursive function, you can get quadratic behavior. Consider the following function, designed to count backwards from n to 1.

Iterable naturalsDownFrom(n) sync* {
  if (n > 0) {
     yield n;
     for (int i in naturalsDownFrom(n-1)) { yield i; }

The code above is functionally correct, but runs in quadratic time. Notice that yield i; is executed n − 1 times for the nth element in the sequence: once at each level of recursion; the first element, 3, is only yielded by the yield n; statement; the second element, 2, is yielded once by yield n; and once by yield i; The third element is 1, which is yielded once by yield n; and twice by yield i;. Altogether we have n(n − 1) executions of yield i;, which is O(n2).

The yield* (pronounced yield-each) statement is designed to get around this problem. The expression following yield* must denote another (sub)sequence. What yield* does is to insert all the elements of the subsequence into the sequence currently being constructed, as if we had an individual yield for each element. We can rewrite our code using yield-each as follows:

Iterable naturalsDownFrom(n) sync* {
  if ( n > 0) {
    yield n;
    yield* naturalsDownFrom(n-1);

The latter version runs in linear time.

Fine print

In a sync* function, the subsequence must be an iterable; in an async* method, the subsequence must be a stream. It is a runtime error if they are not. Of course, you will also get a static warning in such a case.

The subsequence can be empty. In that case, yield* skips over it without suspending.