安装

pip3 install cachetools

常见缓存分类

• class cachetools.Cache(maxsize, getsizeof=None)
• class cachetools.LRUCache(maxsize, getsizeof=None). Least Recently Used
• class cachetools.TTLCache(maxsize, ttl, timer=time.monotonic, getsizeof=None). Time To Live
• class cachetools.LFUCache(maxsize, getsizeof=None). Least Frequently Used
• class cachetools.RRCache(maxsize, choice=random.choice, getsizeof=None). Random Replacement

maxsize属性定义了在缓存开始淘汰旧条目之前的最大条目数
ttl属性定义了在缓存开始淘汰旧条目之前的最大时间,单位是秒

普通方式使用

from cachetools import Cache

#maxsize is the size of data the Cache can hold
cache_data = Cache(maxsize=50000)

data_item1 = "http://example1.com"
data_item2 = "http://example2.com"
data_item3 = "http://example3.com"
data_item4 = "http://example4.com"
data_item5 = "http://example5.com"

cache_data[hash(data_item1)] = data_item1
cache_data[hash(data_item2)] = data_item2
cache_data[hash(data_item3)] = data_item3
cache_data[hash(data_item4)] = data_item4
cache_data[hash(data_item5)] = data_item5

#Accessing data from cache
item = cache_data.get(hash(data_item4), None)

print("Getting from cache = ", item)

装饰器方式使用

使用装饰器方式的时候, key是返回值
返回值必须可以hash

• cached

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)

• LRUCache

def envkey(*args, env={}, **kwargs):
    key = hashkey(*args, **kwargs)
    key += tuple(sorted(env.items()))
    return key

@cached(LRUCache(maxsize=128), key=envkey)
def foo(x, y, z, env={}):
    pass

foo(1, 2, 3, env=dict(a='a', b='b'))