Package: aiocache
Asyncio cache supporting multiple backends (memory, redis and memcached).This library aims for simplicity over specialization. All caches contain the same minimum interface which consists on the following functions:add: Only adds key/value if key does not exist.get: Retrieve value identified by key.set: Sets key/value.multi_get: Retrieves multiple key/values.multi_set: Sets multiple key/values.exists: Returns True if key exists False otherwise.increment: Increment the value stored in the given key.delete: Deletes key and returns number of deleted items.clear: Clears the items stored.raw: Executes the specified command using the underlying client.ContentsInstallingUsageHow does it workAmazing examplesDocumentationInstallingpip install aiocachepip install aiocache[redis]pip install aiocache[memcached]pip install aiocache[redis,memcached]pip install aiocache[msgpack]UsageUsing a cache is as simple as>>>importasyncio>>>fromaiocacheimportCache>>>cache=Cache(Cache.MEMORY)# Here you can also use Cache.REDIS and Cache.MEMCACHED, default is Cache.MEMORY>>>withasyncio.Runner()asrunner:>>>runner.run(cache.set('key','value'))True>>>runner.run(cache.get('key'))'value'Or as a decoratorimportasynciofromcollectionsimportnamedtuplefromaiocacheimportcached,Cachefromaiocache.serializersimportPickleSerializer# With this we can store python objects in backends like Redis!Result=namedtuple('Result',"content, status")@cached(ttl=10,cache=Cache.REDIS,key="key",serializer=PickleSerializer(),port=6379,namespace="main")asyncdefcached_call():print("Sleeping for three seconds zzzz.....")awaitasyncio.sleep(3)returnResult("content",200)asyncdefrun():awaitcached_call()awaitcached_call()awaitcached_call()cache=Cache(Cache.REDIS,endpoint="127.0.0.1",port=6379,namespace="main")awaitcache.delete("key")if__name__=="__main__":asyncio.run(run())The recommended approach to instantiate a new cache is using theCacheconstructor. However you can also instantiate directly usingaiocache.RedisCache,aiocache.SimpleMemoryCacheoraiocache.MemcachedCache.You can also setup cache aliases so its easy to reuse configurationsimportasynciofromaiocacheimportcaches# You can use either classes or strings for referencing classescaches.set_config({'default':{'cache':"aiocache.SimpleMemoryCache",'serializer':{'class':"aiocache.serializers.StringSerializer"}},'redis_alt':{'cache':"aiocache.RedisCache",'endpoint':"127.0.0.1",'port':6379,'timeout':1,'serializer':{'class':"aiocache.serializers.PickleSerializer"},'plugins':[{'class':"aiocache.plugins.HitMissRatioPlugin"},{'class':"aiocache.plugins.TimingPlugin"}]}})asyncdefdefault_cache():cache=caches.get('default')# This always returns the SAME instanceawaitcache.set("key","value")assertawaitcache.get("key")=="value"asyncdefalt_cache():cache=caches.create('redis_alt')# This creates a NEW instance on every callawaitcache.set("key","value")assertawaitcache.get("key")=="value"asyncdeftest_alias():awaitdefault_cache()awaitalt_cache()awaitcaches.get("redis_alt").delete("key")if__name__=="__main__":asyncio.run(test_alias())How does it workAiocache provides 3 main entities:backends: Allow you specify which backend you want to use for your cache. Currently supporting: SimpleMemoryCache, RedisCache usingredisand MemCache usingaiomcache.serializers: Serialize and deserialize the data between your code and the backends. This allows you to save any Python object into your cache. Currently supporting: StringSerializer, PickleSerializer, JsonSerializer, and MsgPackSerializer. But you can also build custom ones.plugins: Implement a hooks system that allows to execute extra behavior before and after of each command.If you are missing an implementation of backend, serializer or plugin you think it could be interesting for the package, do not hesitate to open a new issue.Those 3 entities combine during some of the cache operations to apply the desired command (backend), data transformation (serializer) and pre/post hooks (plugins). To have a better vision of what happens, here you can check howsetfunction works inaiocache:Amazing examplesInexamples folderyou can check different use cases:Sanic, Aiohttp and TornadoPython object in RedisCustom serializer for compressing dataTimingPlugin and HitMissRatioPlugin demosUsing marshmallow as a serializerUsing cached decorator.Using multi_cached decorator.DocumentationUsageCachesSerializersPluginsConfigurationDecoratorsTestingExamples