For the Priority Queue Medium Article

half_consumption_bruteforce.py

def add_fans(machine_consumptions, total_initial_consumption, n_fans):

    # Find the machine that has the largest amount of consumption and the 
    # current total amount of consumption for the company
    max_index, max_value, current_total_consumption = 0, machine_consumptions[0], 0
    for machine_index in range(len(machine_consumptions)):
        # Compute factory consumption
        current_total_consumption = current_total_consumption + machine_consumptions[machine_index]
        # Find worse machine with largest consumption so far
        if max_value < machine_consumptions[machine_index]:
            max_index, max_value = machine_index, machine_consumptions[machine_index]

    # Resolve the recursion, because we have reached the target: "just below half of initial consumption"
    if current_total_consumption <= total_initial_consumption / 2:
        return n_fans

    # Update the consumption of the worse machine given the effect of the fan we just placed
    machine_consumptions[max_index] = max_value / 2

    # Recurse, and place a fan on the new worse machine
    return add_fans(machine_consumptions, total_initial_consumption, n_fans + 1)


def solution(A):
    # write your code in Python 3.6

    # This is a greedy algorithm, that will try to put fans first on those machines
    # that have the largest contribution to the overall factory consumption
    return add_fans(A, sum(A), 0)