在Python中缓存类属性

问题描述

我正在用python写一个类，并且我有一个属性，该属性将花费相对较长的时间来计算，所以我只想做一次.此外，该类的每个实例都不需要使用它，因此我不想在__init__中默认使用.

我是Python的新手，但不熟悉编程.我可以想出一种很容易做到这一点的方法，但是我一遍又一遍地发现，"Pythonic"做事的方法通常比我在其他语言中的经验要简单得多. >

在Python中是否有正确"的方法来实现此目的?

解决方案

Python≥3.2

您应该同时使用 @property 和 @functools.lru_cache 装饰器:

import functools
class MyClass:
    @property
    @functools.lru_cache()
    def foo(self):
        print("long calculation here")
        return 21 * 2

此答案提供了更详细的示例，还提到了先前Python版本的反向移植.

Python< 3.2

Python Wiki具有缓存的属性装饰器(已获得MIT许可)像这样:

import random
# the class containing the property must be a new-style class
class MyClass(object):
   # create property whose value is cached for ten minutes
   @cached_property(ttl=600)
   def randint(self):
       # will only be evaluated every 10 min. at maximum.
       return random.randint(0, 100)

或者其他提到的任何实现都可以满足您的需求.
或上述反向端口.

I'm writing a class in python and I have an attribute that will take a relatively long time to compute, so I only want to do it once. Also, it will not be needed by every instance of the class, so I don't want to do it by default in __init__.

I'm new to Python, but not to programming. I can come up with a way to do this pretty easily, but I've found over and over again that the 'Pythonic' way of doing something is often much simpler than what I come up with using my experience in other languages.

Is there a 'right' way to do this in Python?

解决方案

Python ≥ 3.2

You should use both @property and @functools.lru_cache decorators:

import functools
class MyClass:
    @property
    @functools.lru_cache()
    def foo(self):
        print("long calculation here")
        return 21 * 2

This answer has more detailed examples and also mentions a backport for previous Python versions.

Python < 3.2

The Python wiki has a cached property decorator (MIT licensed) that can be used like this:

import random
# the class containing the property must be a new-style class
class MyClass(object):
   # create property whose value is cached for ten minutes
   @cached_property(ttl=600)
   def randint(self):
       # will only be evaluated every 10 min. at maximum.
       return random.randint(0, 100)

Or any implementation mentioned in the others answers that fits your needs.
Or the above mentioned backport.

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