首先安装模块：
pip install cachetools
Cachetools提供了五个主要功能：
- Cached
- LRUCache
- TTLCache
- LFUCache
- RRCache
Cached
cached用作装饰器。当我们调用缓存时，它会将函数缓存起来以备后用。默认情况下，这将执行一个简单的缓存。
语法结构：
@cached(cache = {})
def some_fun():
pass示例代码： 【使用时间模块来查看模块的效率】
from cachetools import cached
import time
# without cached
def fib(n):
return n if n < 2 else fib(n - 1) + fib(n - 2)
s = time.time()
print(fib(36))
print("Time Taken:", time.time() - s)
# Now using cached
s = time.time()
# Use this decorator to enable caching
@cached(cache={})
def fib(n):
return n if n < 2 else fib(n - 1) + fib(n - 2)
print(fib(36))
print("Time Taken(cached): ", time.time() - s)
运行结果：
LRUCache
LRUCache在缓存装饰器内部使用。LRU 缓存是指“最近最少使用”的缓存。它接受一个参数“maxsize”，该参数说明应如何缓存最近的函数。
语法结构：
@cached(cache= LRUCache(maxsize= 3))
def some_fun():
pass示例代码：
from cachetools import cached, LRUCache
import time
# cache using LRUCache
@cached(cache=LRUCache(maxsize=3))
def my_fun(n):
# This delay resembles some task
s = time.time()
time.sleep(n)
print("\nTime Taken: ", time.time() - s)
return f"I am executed: {n}"
# Takes 3 seconds
print(my_fun(3))
# Takes no time
print(my_fun(3))
# Takes 2 seconds
print(my_fun(2))
# Takes 1 second
print(my_fun(1))
# Takes 4 seconds
print(my_fun(4))
# Takes no time
print(my_fun(1))
# Takes 3 seconds because maxsize = 3
# and the 3 recent used functions had 1,
# 2 and 4.
print(my_fun(3))
运行结果：
注意： LRUCache也可以从标准 Python 包 functools 中调用
from functools import lru_cache
@lru_cache
def myfunc():
passTTLCache
TTLCache或“Time To Live”缓存是 cachetools 模块中包含的第三个功能。它有两个参数——“maxsize”和“TTL”。“maxsize”的使用与 LRUCache 相同，但这里的“TTL”值表示缓存应存储多长时间。该值以秒为单位。
语法结构：
@cached(cache= TTLCache(maxsize= 33, ttl = 600))
def some_fun():
pass示例代码：
from cachetools import cached, TTLCache
import time
# Here recent 32 functions
# will we stored for 1 minutes
@cached(cache=TTLCache(maxsize=32, ttl=25))
def my_fun(n):
# This delay resembles some task
s = time.time()
time.sleep(n)
print("\nTime Taken: ", time.time() - s)
return f"I am executed: {n}"
print(my_fun(3))
print(my_fun(3))
print("*" * 100)
time.sleep(24)
print(my_fun(3))
print("*" * 100)
time.sleep(26)
print(my_fun(3))
运行结果：
LFUCache
LFUCache或“Least Frequently Used”缓存是另一种类型的缓存技术，用于检索项目被调用的频率。它会在必要时丢弃最不常调用的项目以腾出空间。它采用一个参数——“maxsize”，与 LRUCache 中的相同。
语法结构：
@cached(cache= LFUCache(maxsize= 33))
def some_fun():
pass示例代码：
from cachetools import cached, LFUCache
import time
# Here if a particular item is not called
# within 5 successive call of the function,
# it will be discarded
@cached(cache=LFUCache(maxsize=5))
def my_fun(n):
# This delay resembles some task
s = time.time()
time.sleep(n)
print("\nTime Taken: ", time.time() - s)
return f"I am executed: {n}"
print(my_fun(3))
print(my_fun(3))
print(my_fun(2))
print(my_fun(4))
print(my_fun(1))
print(my_fun(1))
print(my_fun(3))
print(my_fun(3))
print(my_fun(4))
运行结果：
RRCache
RRCache或“Random Replacement”缓存是另一种缓存技术，它随机选择缓存中的项目并在必要时丢弃它们以释放空间。它采用一个参数——“maxsize”，与 LRUCache 中的相同。它还有一个参数选择，默认设置为“random.choice”。
语法结构：
@cached(cache= RRCache(maxsize= 33))
def some_fun():
pass示例代码：
from cachetools import cached, RRCache
import time
# Here if a particular item is not called
# within 5 successive call of the function,
# it will be discarded
@cached(cache=RRCache(maxsize=5))
def my_fun(n):
# This delay resembles some task
s = time.time()
time.sleep(n)
print("\nTime Taken: ", time.time() - s)
return f"I am executed: {n}"
print(my_fun(3))
print(my_fun(3))
print(my_fun(2))
print(my_fun(4))
print(my_fun(1))
print(my_fun(1))
print(my_fun(3))
print(my_fun(2))
print(my_fun(3))
运行结果：
