在Python中，是否有相当于Java对象进行回忆？

发布于 2025-02-10 13:30:13 字数 557 浏览 2 评论 0原文

因此，我试图在Python fibonacci（n）功能中进行回忆。

def fib(n, memo = [None] * (fibn+1)):
    if memo[n] != None: return memo[n]
    if n <= 2: return 1
    memo[n] = fib(n-1) + fib(n-2)
    return memo[n]

我正在尝试找到一种方法来存储我已经计算的值的解决方案。我对此的临时解决方案是制作列表memo = [none] *（fibn+1），如果计算了一个新值：memo [n] = fib（n）。我遇到的问题是，列表大部分是空的，总体上非常低效。我想从此

memo = [none，1，None，2，None，None，等...]

转到

memo = {
3: 2 
4: 3
7: 13
}

类似于Java中的对象的类似物品。

原文

So I am trying to do memoization in a python fibonacci(n) function.

def fib(n, memo = [None] * (fibn+1)):
    if memo[n] != None: return memo[n]
    if n <= 2: return 1
    memo[n] = fib(n-1) + fib(n-2)
    return memo[n]

I am trying to find a way to store the solutions of values, which I already computed. My temporary solution to that is to make a list memo = [None] * (fibn+1) and if a new value is computed: memo[n] = fib(n). The problem I have with this is that the list is mostly empty and is overall very inefficient. I want to go from this

memo = [None, 1, None, 2, None, None, etc...]

to something like this

memo = {
3: 2 
4: 3
7: 13
}

which is just like an object in Java.

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猥琐帝 2025-02-17 13:30:13

Python提供的装饰器可以在functools模块中自动缓存结果：

from functools import lru_cache

@lru_cache
def fib(n):
    if n == 0:
        return 0
    elif n == 1:
        return 1
    return fib(n - 1) + fib(n - 2)

Python provides decorators that can cache the results for you automatically in the functools module:

from functools import lru_cache

@lru_cache
def fib(n):
    if n == 0:
        return 0
    elif n == 1:
        return 1
    return fib(n - 1) + fib(n - 2)

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