时间戳

首页 > 解决方案 > 在python中缓存

python - 在python中缓存

问题描述

最近，我尝试了一些关于缓存的代码。我有 2 个代码，第一个使用字典。其次是使用缓存库。我不明白为什么运行时间如此不同。我认为使用缓存库的第二个与第一个相同。

一：导入时间导入日期时间

class new():
    def __init__(self):
        self.cache = {}

    def get_candy_price(self, candy_id):
        # let's use a sleep to simulate the time your function spends trying to connect to
        # the web service, 5 seconds will be enough.
        time.sleep(5)
        if candy_id % 2 not in self.cache:
            if candy_id % 2 == 0:
                self.cache[candy_id % 2] = 1.5
            else:
                self.cache[candy_id % 2] = 1

        # let's pretend that the price returned by the web service is $1 for candies with a
        # odd candy_id and $1,5 for candies with a even candy_id

        return (datetime.datetime.now().strftime("%c"), self.cache[candy_id % 2])


# now, let's simulate 20 customers in your show.
# They are asking for candy with id 2 and candy with id 3...
for i in range(0,20):
    n = new()
    print(n.get_candy_price(2))
    print(n.get_candy_price(3))

由于每个人都想要输出：

输出：

('Thu Oct 25 16:14:27 2018', 1.5)
('Thu Oct 25 16:14:32 2018', 1)
('Thu Oct 25 16:14:37 2018', 1.5)
('Thu Oct 25 16:14:42 2018', 1)
('Thu Oct 25 16:14:47 2018', 1.5)
('Thu Oct 25 16:14:52 2018', 1)
('Thu Oct 25 16:14:57 2018', 1.5)
('Thu Oct 25 16:15:02 2018', 1)
('Thu Oct 25 16:15:07 2018', 1.5)
('Thu Oct 25 16:15:12 2018', 1)
('Thu Oct 25 16:15:17 2018', 1.5)
('Thu Oct 25 16:15:22 2018', 1)
('Thu Oct 25 16:15:27 2018', 1.5)
('Thu Oct 25 16:15:32 2018', 1)
('Thu Oct 25 16:15:37 2018', 1.5)
('Thu Oct 25 16:15:42 2018', 1)
('Thu Oct 25 16:15:47 2018', 1.5)
('Thu Oct 25 16:15:52 2018', 1)
('Thu Oct 25 16:15:57 2018', 1.5)
('Thu Oct 25 16:16:02 2018', 1)
('Thu Oct 25 16:16:07 2018', 1.5)
('Thu Oct 25 16:16:12 2018', 1)
('Thu Oct 25 16:16:17 2018', 1.5)
('Thu Oct 25 16:16:22 2018', 1)
('Thu Oct 25 16:16:27 2018', 1.5)
('Thu Oct 25 16:16:32 2018', 1)
('Thu Oct 25 16:16:37 2018', 1.5)
('Thu Oct 25 16:16:42 2018', 1)
('Thu Oct 25 16:16:47 2018', 1.5)
('Thu Oct 25 16:16:52 2018', 1)
('Thu Oct 25 16:16:57 2018', 1.5)
('Thu Oct 25 16:17:02 2018', 1)
('Thu Oct 25 16:17:07 2018', 1.5)
('Thu Oct 25 16:17:12 2018', 1)
('Thu Oct 25 16:17:17 2018', 1.5)
('Thu Oct 25 16:17:22 2018', 1)
('Thu Oct 25 16:17:27 2018', 1.5)
('Thu Oct 25 16:17:32 2018', 1)
('Thu Oct 25 16:17:37 2018', 1.5)
('Thu Oct 25 16:17:42 2018', 1)

real    3m20.145s
user    0m0.031s
sys     0m0.016s

第二：

import time
import datetime

from cachetools import cached, TTLCache  # 1 - let's import the "cached" decorator and the "TTLCache" object from cachetools
cache = TTLCache(maxsize=100, ttl=300)  # 2 - let's create the cache object.

@cached(cache)
def get_candy_price(candy_id):
    # let's use a sleep to simulate the time your function spends trying to connect to
    # the web service, 5 seconds will be enough.
    time.sleep(5)

    # let's pretend that the price returned by the web service is $1 for candies with a
    # odd candy_id and $1,5 for candies with a even candy_id

    price = 1.5 if candy_id % 2 == 0 else 1

    return (datetime.datetime.now().strftime("%c"), price)


# now, let's simulate 20 customers in your show.
# They are asking for candy with id 2 and candy with id 3...
for i in range(0,20):
    print(get_candy_price(2))
    print(get_candy_price(3))

输出：

('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)
('Thu Oct 25 16:32:28 2018', 1.5)
('Thu Oct 25 16:32:33 2018', 1)

real    0m10.121s
user    0m0.031s
sys     0m0.016s

谁能以更理解的方式向我展示第二个缓存的代码示例？例如，是否可以将其更改为更容易查看库如何运行以进行缓存的内容，例如首先？相差约3分钟。

我的目标：

是为了理解python中的缓存，所以我尝试实现两种不同的方式；一个有图书馆，另一个没有。那么cache with library其实和自己制作字典一样吗？那么缓存是否意味着我们制作了一个充当查找表的字典？

标签： python

解决方案

你总是可以和代码老兄一起玩，

您的第一个示例很难理解缓存机制，您正在制作

您的缓存元素将一次又一次地形成，因为n = new()正在重新初始化自己。丢失所有缓存。这就是为什么它需要太长时间。让它像，

 n = new()
 for i in range(0,20):
    print(n.get_candy_price(2))
    print(n.get_candy_price(3))

另一件事，

    # let's use a sleep to simulate the time your function spends trying to connect to
    # the web service, 5 seconds will be enough.
    time.sleep(5)

你想缓存，对吧？那么为什么每次都会调用这个网络电话。仅当答案不在缓存中时才应始终调用它，我正在重新定义您的get_candy_price函数，

def get_candy_price(self, candy_id):
    # for observing the results
    print (self.cache, candy_id)
    if candy_id % 2 not in self.cache:

        # as this wasn't already in cache
        # let's use a sleep to simulate the time your function spends trying to connect to
        # the web service, 1 seconds will be enough.
        time.sleep(5)
        if candy_id % 2 == 0:
            self.cache[candy_id % 2] = 1.5
        else:
            self.cache[candy_id % 2] = 1
    else:
        # as we already have cached it
        return self.cache[candy_id % 2]
    return (datetime.datetime.now().strftime("%c"), self.cache[candy_id % 2])

在第二个示例中，使用 ttl 参数

 cache = TTLCache(maxsize=100, ttl=5)

请注意，它现在没有那么快是吗？这是因为您的 ttl(Time to live) 参数将结果缓存了一段时间。谷歌了解更多！

推荐阅读