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This primer contains several examples of iterators:

  • an iterator to generate the Fibonacci numbers,

  • an iterator defined by multiple loops

  • and a recursive iterator over a tree.

It also contains examples of the two kinds of parallel iteration:

  • data-parallel (forall), and

  • task-parallel (coforall).


Generates the first n Fibonacci numbers.

The state of this iterator is stored in the tuple (current, next). Each time the yield statement is reached, it yields, or generates, the current Fibonacci number. It then updates the state to the next one.

iter fibonacci(n: int) {
  var (current, next) = (0, 1);
  for 1..n {
    yield current;
    (current, next) = (next, current + next);

An iterator is typically invoked in a loop. Whenever an iterator’s yield statement is executed, the loop’s index variable is initialized with the yielded value and the loop body is executed for a single iteration before returning to the iterator.

When the iterator completes or encounters a return statement, the loop terminates.

write("The first few Fibonacci numbers are: ");

for indexVar in fibonacci(10) do
  write(indexVar, ", ");


This example uses zippered iteration to iterate over the fibonacci iterator with n set to ten and the unbounded range 1... Ranges, as well as arrays and domains, can be used as iterators in loops.

Zippered iteration means that each iterator is advanced to its next yield and the yielded values are combined into a tuple.

A zippered loop can have a single index variable, which will be a tuple of the yielded values; or a tuple of variables like (i, j), each of which is initialized with the value yielded by the corresponding iterator.

In zippered loops, the first iterand controls the behavior of the loop, and is referred to as the “leader”. Subsequent iterands must each either match the number of iterations or else be unbounded, as in this example. When iterating over multidimensional domains and arrays in a zippered iteration, they must match not only in terms of size, but also shape (i.e., the size in each dimension).

writeln("Fibonacci Numbers");

for (i, j) in zip(fibonacci(10), 1..) {
  write("The ", j);

  select j {
    when 1 do write("st");
    when 2 do write("nd");
    when 3 do write("rd");
    otherwise write("th");

  writeln(" Fibonacci number is ", i);



Generate the outer (Cartesian) product of indices in two ranges and yield them as tuples.

iter multiloop(n: int) {
  for i in 1..n do
    for j in 1..n do
      yield (i, j);

Below is an example of promotion. In this case, promotion means that a procedure which normally takes a single argument will be repeated for each value that the iterator returns.

In this case, writeln() is called with each value returned by the multiloop() iterator.

writeln("Multiloop Tuples");


Iterate over Tree in postorder using recursion.

Each yield statement returns a node, or equivalently the subtree rooted at that node.

class Tree : writeSerializable {
  var data: string;
  var left, right: owned Tree?;

iter postorder(tree: borrowed Tree?): borrowed Tree {
  if tree {
    if tree!.left {
      // Call the iterator recursively on the left subtree and expand.
      for child in postorder(tree!.left) do
        yield child;

    if tree!.right {
      // Call the iterator recursively on the right subtree and expand.
      for child in postorder(tree!.right) do
        yield child;

    // Finally, yield the node itself.
    yield tree!;

Initialize a Tree instance to:

 / \
b   c
   / \
  d   e
var tree = new Tree( "a",
  new Tree("b"),
  new Tree("c",
    new Tree("d"),
    new Tree("e")));

This method uses the postorder iterator to print out each node. It uses the “first” flag to avoid printing a leading space.

override proc Tree.serialize(writer, ref serializer)
  var first = true;

  for node in postorder(this) {
    if first then
      first = false;
      writer.write(" ");


Output the data in the tree using the postorder iterator.

writeln("Tree Data");

Iterators in parallel

When invoked in a forall loop (or semantically equivalent context), the iterator is required to create parallel tasks and assign work to them. Such iterators are a fairly big topic and are described in detail in the Parallel Iterators primer.

The coforall loop uses the serial iterator to spawn a separate task for each of the values it yields. If you use coforall, you are asserting that the manipulations done with each yielded value can be done in parallel. All of the spawned tasks will complete before execution continues at the end of the coforall statement body.

This code decorates each node in the tree in parallel, using a coforall. Then it writes out the resulting tree data using a postorder traversal.

proc decorate(s:string) do return "node_" + s;

writeln("Task parallel iteration");

coforall node in postorder(tree) do = decorate(;