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  • a binary search operates on a (sorted) contiguous sequence with a specified left and right index (this is called the search space).

  • binary searching is composed of 3 sections:

    • pre-processing: sort if collection is unsorted
    • binary search: using a loop or recursion to divide search space in half after each comparison (O(log(N))
    • **post-processing`: determine viable candidates in the remaining space
  • there are 3 "templates" when writing a binary search:

    • while left < right, with left = mid + 1 and right = mid - 1
    • while left < right, with left = mid + 1 and right = mid, and left is returned
    • while left + 1 < right, with left = mid and right = mid, and left and right are returned


iterative


    if lens(nums) == 0:
        return False
        
    lower, higher = 0, len(array)

    while lower < higher:
        mid = (higher + lower) // 2
        
        if array[mid] == item:
            return mid 
        elif array[mid] > item:
            higher = mid - 1
        else:
            lower = mid + 1
            
    return False


recursive


def binary_search_recursive(array, item, higher=None, lower=0):

    higher = higher or len(array)
    
    if higher < lower:
        return False
    
    mid = (higher + lower) // 2
    
    if  item == array[mid]:
        return mid
        
    elif item < array[mid]:
        return binary_search_recursive(array, item, mid - 1, lower)
        
    else:
        return binary_search_recursive(array, item, higher, mid + 1)


in a matrix


def binary_search_matrix(matrix, item, lower=0, higher=None):

    if not matrix:
        return False
    
    rows = len(matrix)
    cols = len(matrix[0])
    higher = higher or rows * cols

    if higher > lower:
        mid = (higher + lower) // 2
        row = mid // cols
        col = mid % cols

        if item == matrix[row][col]:
            return row, col
        elif item < matrix[row][col]:
            return binary_search_matrix(matrix, item, lower, mid - 1)
        else:
            return binary_search_matrix(matrix, item, mid + 1, higher)
        
    return False


find the square root



def sqrt(x) -> int:
    
        if x < 2:
            return x
        
        left, right = 2, x // 2
        
        while left <= right:
            
            mid = (right + left) // 2
            num = mid * mid
            
            if num > x:
                right = mid - 1
                
            elif num < x:
                left = mid + 1
                
            else:
                return mid
            
        return right


find min in a rotated array


def find_min(nums):
        
        left, right = 0, len(nums) - 1
        
        while nums[left] > nums[right]:
            
            mid = (left + right) // 2
            
            if nums[mid] < nums[right]:
                right = mid
            else:
                left =  mid + 1
                
        return nums[left]


find a peak element


  • a peak element is an element that is strictly greater than its neighbors.

def peak_element(nums):

        left, right = 0, len(nums) - 1

        while left < right:

            mid = (left + right) // 2

            if nums[mid + 1] < nums[mid]:
                right = mid
            else:
                left = mid + 1

        return left