Generator (computer science)

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For other uses, see Generator (disambiguation).

In computer science, a generator is a special routine that can be used to control the iteration behaviour of a loop. A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values. However, instead of building an array containing all the values and returning them all at once, a generator yields the values one at a time, which requires less memory and allows the caller to get started processing the first few values immediately. In short, a generator looks like a function but behaves like an iterator.

Generators first appeared in CLU (1975)^[1] and are now available in Python^[2], C#, and JavaScript^[3]. (In CLU and C#, generators are called iterators.)

Generators are usually invoked inside loops. The first time that a generator invocation is reached in a loop, an iterator object is created that encapsulates the state of the generator routine at its beginning, with arguments bound to the corresponding parameters. The generator's body is then executed in the context of that iterator until a special yield action is encountered; at that time, the value provided with the yield action is used as the value of the invocation expression. The next time the same generator invocation is reached in a subsequent iteration, the execution of the generator's body is resumed after the yield action, until yet another yield action is encountered. In addition to the yield action, execution of the generator body can also be terminated by a finish action, at which time the innermost loop enclosing the generator invocation is terminated.

Because generators compute their yielded values only on demand, they are useful for representing sequences that are expensive to compute, or even infinite.

In the presence of generators, loop constructs of a language can be reduced into a single loop ... end loop construct; all the usual loop constructs can then be comfortably simulated by using suitable generators in the right way.

An example Python generator:

def countfrom(n):
    while True:
        yield n
        n += 1

# Example use: printing out the integers from 10 to 20.
# Note that this iteration terminates normally, despite countfrom() being
# written as an infinite loop.

for i in countfrom(10):
    if i <= 20:
        print i
    else:
        break

In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever the iterator's next() method is called, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.

Generators can be implemented in terms of more expressive control flow constructs, such as coroutines or first-class continuations.^[4]

[edit] See also

• List comprehension for another construct that generates a sequence of values
• Iterator for the concept of producing a list one element at a time
• Lazy evaluation for producing values when needed
• Corecursion for potentially infinite data by recursion instead of yield
• Coroutine for even more generalization from subroutine
• Continuation for generalization of control flow

[edit] References

1. ^ Liskov, Barbara (April 1992). A History of CLU (pdf).
2. ^ Python Enhancement Proposals: PEP 255: Simple Generators, PEP 289: Generator Expressions, PEP 342: Coroutines via Enhanced Generators
3. ^ New In JavaScript 1.7. Retrieved on 2006-10-10.
4. ^ Kiselyov, Oleg (January 2004). General ways to traverse collections in Scheme.

• Stephan Murer, Stephen Omohundro, David Stoutamire and Clemens Szyperski: Iteration abstraction in Sather. ACM Transactions on Programming Languages and Systems, 18(1):1-15 (1996) [1]