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Below, there is view of each step of the mapping process for a list of integers X = [0, 5, 8, 3, 2, 1] mapping into a new list X' according to the function () = + : . View of processing steps when applying map function on a list
Example C-like code using indices for top-down merge sort algorithm that recursively splits the list (called runs in this example) into sublists until sublist size is 1, then merges those sublists to produce a sorted list. The copy back step is avoided with alternating the direction of the merge with each level of recursion (except for an ...
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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: >>>
Merge-insertion sort performs the following steps, on an input of elements: [6]. Group the elements of into ⌊ / ⌋ pairs of elements, arbitrarily, leaving one element unpaired if there is an odd number of elements.
For example, bubble sort is () on a list that is already sorted, while quicksort would still perform its entire () sorting process. While any sorting algorithm can be made O ( n ) {\displaystyle O(n)} on a presorted list simply by checking the list before the algorithm runs, improved performance on almost-sorted lists is harder to replicate.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
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