Python中的 Cachetools 模块

Cachetools是一个Python模块，它提供了各种记忆集合和装饰器。它还包括来自 functools 的 @lru_cache 装饰器的变体。要使用它，首先，我们需要使用 pip 安装它。

pip install cachetools

Cachetools为我们提供了五个主要函数。

• 缓存的
• LRUCache
• TTL缓存
• LFUCache
• RRCache

让我们通过示例详细了解以下每个功能。

缓存

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。

句法：

@cached(cache = {})
def some_fun():
    pass

示例：让我们用一个例子来看看它。我们将使用时间模块来查看我们模块的效率。

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(old_fib(35))
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(35))
print("Time Taken(cached): ", time.time() - s)

输出：

9227465
Time Taken:  4.553245782852173
9227465
Time Taken(cached):  0.0003821849822998047

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。

句法：

@cached(cache= LRUCache(maxsize= 3))
def some_fun():
    pass

例子：

from cachetools import cached, LRUCache
import time
  
  
# cache using LRUCache
@cached(cache = LRUCache(maxsize = 3))
def myfun(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(myfun(3))
  
# Takes no time
print(myfun(3))
  
# Takes 2 seconds
print(myfun(2))
  
# Takes 1 second
print(myfun(1))
  
# Takes 4 seconds
print(myfun(4))
  
# Takes no time
print(myfun(1))
  
# Takes 3 seconds because maxsize = 3 
# and the 3 recent used functions had 1,
# 2 and 4.
print(myfun(3))

输出：

Time Taken:  3.0030977725982666
I am executed: 3
I am executed: 3

Time Taken:  2.002072334289551
I am executed: 2

Time Taken:  1.001115083694458
I am executed: 1

Time Taken:  4.001702070236206
I am executed: 4
I am executed: 1

Time Taken:  3.0030171871185303
I am executed: 3

注意： LRUCache也可以从标准Python包 functools 中调用。它可以看到导入为

from functools import lru_cache
@lru_cache
def myfunc():
    pass

TTL缓存

TTLCache或“生存时间”缓存是 cachetools 模块中包含的第三个函数。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。

句法：

@cached(cache= TTLCache(maxsize= 33, ttl = 600))
def some_fun():
    pass

例子：

from cachetools import cached, TTLCache
import time
  
# Here recent 32 functions 
# will we stored for 1 minutes
@cached(cache = TTLCache(maxsize = 32, ttl = 60))        
def myfun(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(myfun(3))
print(myfun(3))
time.sleep(61)
print(myfun(3))

输出：

Time Taken:  3.0031025409698486
I am executed: 3
I am executed: 3

Time Taken:  3.0029332637786865
I am executed: 3

LFUCache

LFUCache或“最少使用”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。

句法：

@cached(cache= LFUCache(maxsize= 33))
def some_fun():
    pass

例子：

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 myfun(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(myfun(3))
print(myfun(3))
print(myfun(2))
print(myfun(4))
print(myfun(1))
print(myfun(1))
print(myfun(3))
print(myfun(3))
print(myfun(4))

输出：

Time Taken:  3.002413272857666
I am executed: 3
I am executed: 3

Time Taken:  2.002107620239258
I am executed: 2

Time Taken:  4.003819465637207
I am executed: 4

Time Taken:  1.0010886192321777
I am executed: 1
I am executed: 1
I am executed: 3
I am executed: 3
I am executed: 4

RRCache

RRCache或“随机替换”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”。

句法：

@cached(cache= RRCache(maxsize= 33))
def some_fun():
    pass

例子：

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 myfun(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(myfun(3))
print(myfun(3))
print(myfun(2))
print(myfun(4))
print(myfun(1))
print(myfun(1))
print(myfun(3))
print(myfun(2))
print(myfun(3))

输出：

Time Taken:  3.003124713897705
I am executed: 3
I am executed: 3

Time Taken:  2.0021231174468994
I am executed: 2

Time Taken:  4.004120588302612
I am executed: 4

Time Taken:  1.0011250972747803
I am executed: 1
I am executed: 1
I am executed: 3
I am executed: 2
I am executed: 3