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An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement follows: 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 )
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.
Maple has two forms of for-loop, one for iterating over a range of values, and the other for iterating over the contents of a container. The value range form is as follows: for i from f by b to t while w do # loop body od; All parts except do and od are optional. The for I part, if present, must come first.
It implicitly calls the IntoIterator::into_iter method on the expression, and uses the resulting value, which must implement the Iterator trait. If the expression is itself an iterator, it is used directly by the for loop through an implementation of IntoIterator for all Iterators that returns the iterator unchanged.
Iterators constitute alternative language constructs to loops, which ensure consistent iterations over specific data structures. They can eventually save time and effort in later coding attempts. In particular, an iterator allows one to repeat the same kind of operation at each node of such a data structure, often in some pre-defined order.
This scheme, handy for creating simple caches, ensures that the most recently used items are also the quickest to find again. Another common approach is to "index" a linked list using a more efficient external data structure. For example, one can build a red–black tree or hash table whose elements are references to the linked list nodes ...
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
Because the notation f n may refer to both iteration (composition) of the function f or exponentiation of the function f (the latter is commonly used in trigonometry), some mathematicians [citation needed] choose to use ∘ to denote the compositional meaning, writing f ∘n (x) for the n-th iterate of the function f(x), as in, for example, f ...