什么是备忘录，如何在Python中使用备忘录? [英] What is memoization and how can I use it in Python?

问题描述

我刚开始使用Python，不知道记忆化是什么以及如何使用它.另外，我可以举一个简化的例子吗?

解决方案

记忆有效地指基于方法输入记住方法调用的结果(记忆"→备忘录"→要记忆)，然后返回记忆的结果而不是再次计算结果.您可以将其视为方法结果的缓存.有关更多详细信息，请参阅第387页的Cormen等人的 算法简介 (3e)中的定义.

一个简单的示例，该示例使用Python中的记忆来计算阶乘:

factorial_memo = {}
def factorial(k):
    if k < 2: return 1
    if k not in factorial_memo:
        factorial_memo[k] = k * factorial(k-1)
    return factorial_memo[k]

您可能会变得更加复杂，并将备注过程封装到一个类中:

class Memoize:
    def __init__(self, f):
        self.f = f
        self.memo = {}
    def __call__(self, *args):
        if not args in self.memo:
            self.memo[args] = self.f(*args)
        #Warning: You may wish to do a deepcopy here if returning objects
        return self.memo[args]

然后:

def factorial(k):
    if k < 2: return 1
    return k * factorial(k - 1)

factorial = Memoize(factorial)

Python 2.4中添加了一个称为"装饰器"的功能，该功能现在，您只需编写以下代码即可完成同一件事:

@Memoize
def factorial(k):
    if k < 2: return 1
    return k * factorial(k - 1)

Python装饰器库具有类似的装饰器，称为memoization is and how to use it. Also, may I have a simplified example?

解决方案

Memoization effectively refers to remembering ("memoization" → "memorandum" → to be remembered) results of method calls based on the method inputs and then returning the remembered result rather than computing the result again. You can think of it as a cache for method results. For further details, see page 387 for the definition in Introduction To Algorithms (3e), Cormen et al.

A simple example for computing factorials using memoization in Python would be something like this:

factorial_memo = {}
def factorial(k):
    if k < 2: return 1
    if k not in factorial_memo:
        factorial_memo[k] = k * factorial(k-1)
    return factorial_memo[k]

You can get more complicated and encapsulate the memoization process into a class:

class Memoize:
    def __init__(self, f):
        self.f = f
        self.memo = {}
    def __call__(self, *args):
        if not args in self.memo:
            self.memo[args] = self.f(*args)
        #Warning: You may wish to do a deepcopy here if returning objects
        return self.memo[args]

Then:

def factorial(k):
    if k < 2: return 1
    return k * factorial(k - 1)

factorial = Memoize(factorial)

A feature known as "decorators" was added in Python 2.4 which allow you to now simply write the following to accomplish the same thing:

@Memoize
def factorial(k):
    if k < 2: return 1
    return k * factorial(k - 1)

The Python Decorator Library has a similar decorator called memoized that is slightly more robust than the Memoize class shown here.

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