Understanding the Basics of Linear Search

This algorithm searches for an element in an array sequentially, one by one, until either the element is found or the end of the array is reached

• We start by taking the input array arr[] and the element to be searched x.

• We initialize a variable n to store the length of the array.

• We then traverse through each element of the array using a loop, starting from index 0 to n-1.

• At each iteration, we check if the current element of the array is equal to x. If it is, we return the index of that element.

• If we traverse the entire array without finding x, we return -1 to indicate that x is not present in the array.

  •     def linear_search(arr, x):
            n = len(arr)
            # Looping through all elements in the array
            for i from 0 to n-1:
                # If the current element is equal to x, return its index
                if arr[i] equals x:
                    return i
            # If x is not present in the array, return -1
            return -1
    

    In short, the linear search algorithm has a time complexity of O(n) and a space complexity of O(1). It's a simple algorithm but not the best for big datasets because its time complexity increases in line with the array's size.