Editing Iterator (section)

==Generator==
{{Main|Generator (computer science)}}

One way of implementing an iterator is via a restricted form of [[coroutine]], known as a [[Generator (computer science)|generator]]. By contrast with a [[subroutine]], a generator coroutine can ''yield'' values to its caller multiple times, instead of returning just once. Most iterators are naturally expressible as generators, but because generators preserve their local state between invocations, they're particularly well-suited for complicated, stateful iterators, such as [[tree traversal|tree traversers]]. There are subtle differences and distinctions in the use of the terms "generator" and "iterator", which vary between authors and languages.<ref>{{cite web
 |url          = http://www.csd.uwo.ca/
 |title        = A Technique for Generic Iteration and Its Optimization
 |last1        = Watt
 |first1       = Stephen M.
 |format       = PDF
 |publisher    = The University of Western Ontario, Department of Computer Science
 |archive-url  = https://web.archive.org/web/20120806072711/http://www.csd.uwo.ca/
 |archive-date = 2012-08-06
 |quote        = Some authors use the term iterator, and others the term generator. Some make subtle distinctions between the two.
 |access-date  = 2012-08-08
 |url-status   = bot: unknown
}}</ref> In [[Python (programming language)|Python]], a generator is an iterator [[Constructor (object-oriented programming)|constructor]]: a function that returns an iterator. An example of a Python generator returning an iterator for the [[Fibonacci number]]s using Python's <code>yield</code> statement follows:
<syntaxhighlight lang="python">
def fibonacci(limit):
    a, b = 0, 1
    for _ in range(limit):
        yield a
        a, b = b, a + b

for number in fibonacci(100):  # The generator constructs an iterator
    print(number)
</syntaxhighlight>