Django’s cache framework

小结：

1、缓存存储位置：数据库、文件系统、内存

2、通过缓存前缀实现跨服务器缓存

 

Django’s cache framework | Django documentation | Django https://docs.djangoproject.com/en/2.2/topics/cache/

 The cache system requires a small amount of setup. Namely, you have to tell it where your cached data should live – whether in a database, on the filesystem or directly in memory. This is an important decision that affects your cache’s performance; yes, some cache types are faster than others.

 

In this example, Memcached is running on localhost (127.0.0.1) port 11211, using the python-memcachedbinding:

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
        'LOCATION': '127.0.0.1:11211',
    }
}

In this example, Memcached is available through a local Unix socket file /tmp/memcached.sock using the python-memcached binding:

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
        'LOCATION': 'unix:/tmp/memcached.sock',
    }
}

When using the pylibmc binding, do not include the unix:/ prefix:

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.memcached.PyLibMCCache',
        'LOCATION': '/tmp/memcached.sock',
    }
}

One excellent feature of Memcached is its ability to share a cache over multiple servers. This means you can run Memcached daemons on multiple machines, and the program will treat the group of machines as a singlecache, without the need to duplicate cache values on each machine. To take advantage of this feature, include all server addresses in LOCATION, either as a semicolon or comma delimited string, or as a list.

In this example, the cache is shared over Memcached instances running on IP address 172.19.26.240 and 172.19.26.242, both on port 11211:

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
        'LOCATION': [
            '172.19.26.240:11211',
            '172.19.26.242:11211',
        ]
    }
}

In the following example, the cache is shared over Memcached instances running on the IP addresses 172.19.26.240 (port 11211), 172.19.26.242 (port 11212), and 172.19.26.244 (port 11213):

CACHES = {
    'default': {
        'BACKEND': 'django.core.cache.backends.memcached.MemcachedCache',
        'LOCATION': [
            '172.19.26.240:11211',
            '172.19.26.242:11212',
            '172.19.26.244:11213',
        ]
    }
}

A final point about Memcached is that memory-based caching has a disadvantage: because the cached data is stored in memory, the data will be lost if your server crashes. Clearly, memory isn’t intended for permanent data storage, so don’t rely on memory-based caching as your only data storage. Without a doubt, none of the Django caching backends should be used for permanent storage – they’re all intended to be solutions for caching, not storage – but we point this out here because memory-based caching is particularly temporary.

 

 

Cache key prefixing

If you are sharing a cache instance between servers, or between your production and development environments, it’s possible for data cached by one server to be used by another server. If the format of cached data is different between servers, this can lead to some very hard to diagnose problems.

To prevent this, Django provides the ability to prefix all cache keys used by a server. When a particular cache key is saved or retrieved, Django will automatically prefix the cache key with the value of the KEY_PREFIXcache setting.

By ensuring each Django instance has a different KEY_PREFIX, you can ensure that there will be no collisions in cache values.

 

 

from django.core.cache import cache

https://niwinz.github.io/django-redis/latest/