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Python's tuple assignment, fully available in its foreach loop, also makes it trivial to iterate on (key, value) pairs in dictionaries: for key , value in some_dict . items (): # Direct iteration on a dict iterates on its keys # Do stuff
In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
In modern JavaScript it's considered bad form to use the Array type as an associative array. Consensus is that the Object type and Map / WeakMap classes are best for this purpose. The reasoning behind this is that if Array is extended via prototype and Object is kept pristine, for and for-in loops will work as expected on associative 'arrays'.
Iterating over a container is done using this form of loop: for e in c while w do # loop body od; The in c clause specifies the container, which may be a list, set, sum, product, unevaluated function, array, or object implementing an iterator. A for-loop may be terminated by od, end, or end do.
In computer programming, an iterator is an object that progressively provides access to each item of a collection, in order. [1] [2] [3]A collection may provide multiple iterators via its interface that provide items in different orders, such as forwards and backwards.
In this example, a true dependence exists between statement S1 in the jth iteration and S1 in the j+1th iteration. There is a true dependence because a value will be written to a[j] in one iteration and then a read occurs by a[j-1] in the next iteration. This true dependence can be represented by S1[j] →T S1[j+1].
In array languages, operations are generalized to apply to both scalars and arrays. Thus, a+b expresses the sum of two scalars if a and b are scalars, or the sum of two arrays if they are arrays. An array language simplifies programming but possibly at a cost known as the abstraction penalty.
Loop unrolling, also known as loop unwinding, is a loop transformation technique that attempts to optimize a program's execution speed at the expense of its binary size, which is an approach known as space–time tradeoff.