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[ Source: aiocache  ]

Package: python3-aiocache (0.12.3-2)

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Asyncio-mellemlager med flere motorer

Asyncio cache understøtter flere motorer (hukommelse, redis og memcached). Dette bibliotek er rettet mod enkelhed frem for specialisering. Alle mellemlagre indeholder den samme minimale grænseflade, der består på de følgende funktioner:

 - ``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.

  .. role:: python(code)
   :language: python

  .. contents::

  .. section-numbering:

Brug ====

Brug af et mellemlager er så simpelt som at

  .. code-block:: python

     >>> import asyncio
     >>> from aiocache import Cache
     >>> cache = Cache(Cache.MEMORY) # Here you can also use Cache.REDIS and Cache.MEMCACHED, default is Cache.MEMORY
     >>> with asyncio.Runner() as runner:
     >>>     runner.run(cache.set('key', 'value'))
     True
     >>>     runner.run(cache.get('key'))
     'value'

Eller som en dekoratør

  .. code-block:: python

     import asyncio

     from collections import namedtuple

     from aiocache import cached, Cache
     from aiocache.serializers import PickleSerializer
     # 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")
     async def cached_call():
         print("Sleeping for three seconds zzzz.....")
         await asyncio.sleep(3)
         return Result("content", 200)

     async def run():
         await cached_call()
         cache = Cache(Cache.REDIS, endpoint="127.0.0.1", port=6379, namespace="main")
         await cache.delete("key")

     if __name__ == "__main__":
         asyncio.run(run())

 The recommended approach to instantiate a new cache is using the `Cache` constructor.
 However you can also instantiate directly using `aiocache.RedisCache`,
 `aiocache.SimpleMemoryCache` or `aiocache.MemcachedCache`.

Du kan også opsætte mellemlageraliasser så det er nemt at genbruge konfigurationer

  .. code-block:: python

   import asyncio

   from aiocache import caches

   # You can use either classes or strings for referencing classes
   caches.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"}
           ]
       }
   })

   async def default_cache():
       cache = caches.get('default')   # This always returns the SAME instance
       await cache.set("key", "value")
       assert await cache.get("key") == "value"

   async def alt_cache():
       cache = caches.create('redis_alt')   # This creates a NEW instance on every call
       await cache.set("key", "value")
       assert await cache.get("key") == "value"

   async def test_alias():
       await default_cache()
       await alt_cache()

       await caches.get("redis_alt").delete("key")

   if __name__ == "__main__":
       asyncio.run(test_alias())

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