Question

I have a function that sums the elements of a nested list.

data = [1, 2, [3, 4], [5, 6]]

#Big O for this is O(N)?
def sum_list_recursive(data):
    if len(data) == 0:
        return 0
    current_number = 0
    if isinstance(data[0], list):
        current_number = sum_list_recursive(data[0])
    else:
        current_number = data[0]
    data.remove(data[0])
    return current_number + sum_list_recursive(data)


if __name__ == "__main__":
    print("Recursive sum: ", sum_list_recursive(data))

What would be the Big O for this? I think it's O(N), because even though there's an if statement to go inside the nested list, it's still just calculating through the N elements. Also, what would be the Big Theta and Big Omega. Are they also just Theta(N) and Omega(N), because you can just multiply N by K?

Answer 1

You're right as far as your argument goes. However, look at what happens with arbitrary list nesting. How many calls do you make if the input is as below?

data = [[[[[1]], [[[[2]]]]], [3, [[[4]]]], [[[5, 6]]]]]

It's still linear, but I believe it's linear on N+P, where N is the quantity of numbers to add, and P is the quantity of lists (left brackets, for example).

Python Recursive Summation of Nested Lists Big O Analysis

1 个答案: