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In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation: >>>
A function. May be unary or n-ary (or always unary for languages without n-ary functions). func1, func2, etc. functions of specific arity. func (with no number) is the same as func1, also known as a projection in many languages. pred Unary function returning a Boolean value. (ML type: 'a -> bool) (C-like type: bool pred < T > (T t)). list The ...
The types of objects that can be iterated across (my_list in the example) are based on classes that inherit from the library class ITERABLE. The iteration form of the Eiffel loop can also be used as a boolean expression when the keyword loop is replaced by either all (effecting universal quantification) or some (effecting existential ...
In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...
The following example is done in Ada which supports both early exit from loops and loops with test in the middle. Both features are very similar and comparing both code snippets will show the difference: early exit must be combined with an if statement while a condition in the middle is a self-contained construct.
If control exits the function without a return value having been explicitly specified, the function returns the default value for the return type. Sub Main(««ByVal »args() As String») instructions End Subor Function Main(««ByVal »args() As String») As Integer instructions End Function: Xojo: Python: foo(«parameters») def foo ...
In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop.All generators are also iterators. [1] 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.
In Python, functions are first-class objects that can be created and passed around dynamically. Python's limited support for anonymous functions is the lambda construct. An example is the anonymous function which squares its input, called with the argument of 5: