First clear solution for Ghosts Age by kdim - python coding challenges

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First solution in Clear category for Ghosts Age by kdim

def checkio(opacity):
    fibonacci, age = [0, 1], 0
    for i in range(18):
        fibonacci.append(fibonacci[i] + fibonacci[i + 1])
    while opacity != 10000:
        age += 1
        opacity += age if age in fibonacci else -1
    return age

#These "asserts" using only for self-checking and not necessary for auto-testing
if __name__ == '__main__':
    assert checkio(10000) == 0, "Newborn"
    assert checkio(9999) == 1, "1 year"
    assert checkio(9997) == 2, "2 years"
    assert checkio(9994) == 3, "3 years"
    assert checkio(9995) == 4, "4 years"
    assert checkio(9990) == 5, "5 years"

Jan. 1, 2023

Comments:

Selindian on Oct. 19, 2025, 7:44 a.m.
A clean and effective solution with dynamic Fibonacci generation and a clever reverse simulation. Slight room for optimization, but overall a well-crafted piece of code. In the code, the line <pre class='brush: python'>age in fibonacci</pre> checks whether the current age is in the list of Fibonacci numbers. Since <pre class='brush: python'>fibonacci</pre> is a list, Python has to look through the list one item at a time until it finds a match (or reaches the end). This is called a linear-time lookup, and its speed depends on the length of the list. If you convert <pre class='brush: python'>fibonacci</pre> to a set — for example, <pre class='brush: python'>fibonacci = set(fibonacci)</pre> — then Python can check membership using a hash table, which is much faster. This is called a constant-time lookup, meaning it takes the same amount of time regardless of how many items are in the set. So: <ul> <li><pre class='brush: python'>age in list</pre> → slower, especially for longer lists</li> <li><pre class='brush: python'>age in set</pre> → faster, always</li> </ul> In this case, the performance gain is small because the list is short, but using a set is still a cleaner and more efficient choice.

kdim on Oct. 21, 2025, 2:51 p.m.
chatgpt?

Selindian on Oct. 21, 2025, 7:50 p.m.
No, I didn’t use ChatGPT for this. But since English isn’t my native language, I do like to use Copilot or DeepL to improve my texts - though sometimes they go a bit overboard. When I’m stuck on a mission - which occasionally happens, especially when math is involved - I sometimes unlock the solutions using Quest Points and then ask Copilot to explain some of the unlocked solutions to help me understand how I could have solved the mission. It doesn’t always work, but most of the time I end up smarter afterward. Also, when commenting on a solution, I like to have my comment checked by Copilot to make sure my understanding is accurate and that my assumptions about what’s particularly good or what could be improved are correct. But the origin of every comment is a human—me. 🙂

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