Binary Search in Python
The binary search algorithm uses the divide and conquer approach to find a specific item in a list. The list is divided into two halves, and the item is compared with the middle element of the list. If the item is found at the middle element, its location is returned. If the item is not found, the algorithm searches into either of the halves depending on the result of the comparison.
Time complexities refer to the estimation of the amount of time taken by an algorithm to run as a function of the size of the input. It helps us analyze and compare the efficiency of different algorithms and choose the most optimal one for a given problem.
1. Best case complexity: O(1).
2. Average case complexity: O(log n).
3. Worst case complexity: O(log n).
Space Complexity is O(1).
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