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There are subtle differences and distinctions in the use of the terms "generator" and "iterator", which vary between authors and languages. [5] In Python, a generator is an iterator constructor: a function that returns an iterator. An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement ...
Python does not contain the classical for loop, rather a foreach loop is used to iterate over the output of the built-in range() function which returns an iterable sequence of integers. for i in range ( 1 , 6 ): # gives i values from 1 to 5 inclusive (but not 6) # statements print ( i ) # if we want 6 we must do the following for i in range ( 1 ...
The loop calls the Iterator::next method on the iterator before executing the loop body. If Iterator::next returns Some(_), the value inside is assigned to the pattern and the loop body is executed; if it returns None, the loop is terminated.
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, 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.
It should be possible to define a new operation for (some) classes of an object structure without changing the classes. When new operations are needed frequently and the object structure consists of many unrelated classes, it's inflexible to add new subclasses each time a new operation is required because "[..] distributing all these operations across the various node classes leads to a system ...
Clients use an iterator to access and traverse an aggregate without knowing its representation (data structures). Different iterators can be used to access and traverse an aggregate in different ways. New access and traversal operations can be defined independently by defining new iterators. See also the UML class and sequence diagram below.
In mathematics, iteration may refer to the process of iterating a function, i.e. applying a function repeatedly, using the output from one iteration as the input to the next. Iteration of apparently simple functions can produce complex behaviors and difficult problems – for examples, see the Collatz conjecture and juggler sequences .
Modified bytecode. Coroutine functionality is possible by rewriting regular Java bytecode, either on the fly or at compile time. Toolkits include Javaflow, Java Coroutines, and Coroutines. Platform-specific JNI mechanisms. These use JNI methods implemented in the OS or C libraries to provide the functionality to the JVM. [citation needed]