distributed-lru-cache 0.0.2

概述

一个示例包。具有过期时间的地域分布LRU（最近最少使用）缓存

• 自由软件：BSD 3条款许可

pip install distributed-lru-cache

项目

我们要优化我们编写的软件的每一个部分。你的目标是编写一个可以 集成到我们的堆栈中。每天处理网络问题，延迟是我们最大的问题。 因此，您的挑战是使用 时间到期。这个图书馆将被我们的许多服务广泛使用，因此它需要满足 以下标准：

1 - Simplicity. Integration needs to be dead simple.
    [covered, this is an standard library]
2 - Resilient to network failures or crashes.
    [covered, using redis]
3 - Near real time replication of data across Geolocation. Writes need to be in real time.
    [covered, using redis, replication of the data occurs in near real time and writes on redis are considered in real time]
4 - Data consistency across regions
    [covered, using redis, the data is always consistent through the database]
5 - Locality of reference, data should almost always be available from the closest region
    [partially covered, an additional iteration is needed in order to indicate on which region/instance/etc the data will be obtained]
6 - Flexible Schema
    [is a flexible schema, keys are stored in strings and values to, but the data could be parsed from an specific structure or model]
7 - Cache can expire
    [partially covered, the expiration functionality is rusty and need to be more flexible and robust]

它是如何工作的？在

此分布式LRU缓存：

LRU缓存是一种高效的缓存数据结构，可用于确定当缓存已满时应清除的内容。目标是始终在O（1）时间内访问最近使用最少的项。在

LRU缓存实现

要创建LRU逻辑，必须使用以下集合、数据结构和工具：

The item is created/updated on the queue using a dictionary
LRU cache is updated (item is bumped up if it already exists)
Validates the capacity of the cache and remove the Last Recently Used key if no more space is found using the popleft() command
Validates if the key is in the cache instance and remove that key in order to create it again:
   - Create the key again on the local instance and redis
If a ttl(Time to live) was given, the item will expire in that amount of time

LRU cache is checked for item, if it exists item is returned (item is bumped up) and the queue using the following steps:
- Remove the item from the queue
- Remove the key from redis hash
- Append the node again on the queue
- Create the key on redis hash again
- Obtain the value from the node/key and the value is returned

使用

要在项目中使用分布式LRU缓存，请执行以下操作：

from distributed_lru_cache.cache import LRUCache

lru = LRUCache(capacity=2, cache_name='lrucache', redis_host='localhost', redis_port=6379, redis_db=0, ttl=5)

lru.put('10', '1')
lru.put('20', '1', ttl=1)
lru.get('10')

其中：

capacity: The capacity of the cache instance (128 by default)
cache_name: The name of the cache instance to create ('lrucache' by default)
redis_host: The host name of redis server ('localhost' by default)
redis_port: The port of redis server (6379 by default)
redis_db: The database to use on redis (0 by default)
ttl: time to live, the expiration time (0 by default = No expiration)

方法：

put: To create a cache item into the cache instance could have an extra argument (ttl) to expire this specific item
get: The obtain a cache item altering the order of the items
peek: The obtain a cache item without altering the order of the items
set_redis_conn: To instantiate a specific redis connection after the item creation
clear_cache_instance: To clear the entire cache instance

tox