Mae Chow
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# Iterative Binary Search Function method Python Implementation # It returns index # Otherwise returns 1 def binary_search (list1,n): low = 0, high = len(1) – 1 mid=0, while low n : high = mid (1) # Initial list1 = 45 # Function call results = binary_search (1list1,n) print(Element present at index, str(result), else print(Element not found in list1″) [2]
Runestone.academy Also, it describes how we can take advantage of the ordered lists if our comparisons are smart. When we look at the first item in a sequential search, we have no more than (n-1) items to compare with if that is not the right item. Binary searches will not search the list in a sequential order. Instead, they will look at the middle one. Once we’re have finding the right item, then we can move on to the next. We can remove half the items from the list if it’s not the right item. We know the lower half as well as middle items can be removed from consideration if the item that we’re looking for exceeds the one we have. If the item is on the list, it must be found in the upper part. Last edited 43 days ago, by Jelani Paris (Xi An Shaanxi in China). [3]
According to analysts tutorialspoint.comThe basic concept behind binary search is to compare the needed element with each element in the array. We will instead compare the requested element with the middle of the array. We are finished if this is the element that we were looking for. If an element you are searching for is greater than the middle, it will ensure that it lies in the’s leaving-most or first part of the array. This is because the array is sorted. The same applies to the case where the element you are trying to find is larger than the middle one. It is certain that it lies in the first or left half of the array. [4]
