A Redis cache backend for django
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A Redis cache backend for Django
Docs can be found at http://django-redis-cache.readthedocs.org/en/latest/.
rediss://.expire method in lieu of Django’s touch.CacheKey in favor of string literals.set_many.get_many and set_many to work with empty parameters.set_many to set cache key version.delete_many to fail silently with an empty list.get_or_set.DEFAULT_TIMEOUT.SOCKET_CONNECT_TIMEOUT option.Backward incompatibilities:
The HashRing behavior has changed to maintain a proper keyspace balance.
This will lead to some cache misses, so be aware.
Now requires redis-py_ >= 2.10.3
expire command.persist command.has_key implementation that uses Redis’s exists command.has_key up drastically if the key under question iscache.set('key', 'value', timeout=None)ttl method to the cache. cache.ttl(key) will return the number ofAdds Support for Python 3.3 and Django 1.5 and 1.6. Huge thanks to Carl Meyer
for his work.
Redis cache now allows you to use either a TCP connection or Unix domain
socket to connect to your redis server. Using a TCP connection is useful for
when you have your redis server separate from your app server and/or within
a distributed environment. Unix domain sockets are useful if you have your
redis server and application running on the same machine and want the fastest
possible connection.
You can now specify (optionally) what parser class you want redis-py to use
when parsing messages from the redis server. redis-py will pick the best
parser for you implicitly, but using the PARSER_CLASS setting gives you
control and the option to roll your own parser class if you are so bold.
redis-py_ >= 2.10.3
redis_ >= 2.4
hiredis_
python_ >= 2.7
Run pip install django-redis-cache.
Modify your Django settings to use redis_cache.
… code:: python
# When using TCP connections
CACHES = {
'default': {
'BACKEND': 'redis_cache.RedisCache',
'LOCATION': [
'<host>:<port>',
'<host>:<port>',
'<host>:<port>',
],
'OPTIONS': {
'DB': 1,
'PASSWORD': 'yadayada',
'PARSER_CLASS': 'redis.connection.HiredisParser',
'CONNECTION_POOL_CLASS': 'redis.BlockingConnectionPool',
'CONNECTION_POOL_CLASS_KWARGS': {
'max_connections': 50,
'timeout': 20,
},
'MAX_CONNECTIONS': 1000,
'PICKLE_VERSION': -1,
},
},
}
# When using unix domain sockets
# Note: ``LOCATION`` needs to be the same as the ``unixsocket`` setting
# in your redis.conf
CACHES = {
'default': {
'BACKEND': 'redis_cache.RedisCache',
'LOCATION': '/path/to/socket/file',
'OPTIONS': {
'DB': 1,
'PASSWORD': 'yadayada',
'PARSER_CLASS': 'redis.connection.HiredisParser',
'PICKLE_VERSION': 2,
},
},
}
# For Master-Slave Setup, specify the host:port of the master
# redis-server instance.
CACHES = {
'default': {
'BACKEND': 'redis_cache.RedisCache',
'LOCATION': [
'<host>:<port>',
'<host>:<port>',
'<host>:<port>',
],
'OPTIONS': {
'DB': 1,
'PASSWORD': 'yadayada',
'PARSER_CLASS': 'redis.connection.HiredisParser',
'PICKLE_VERSION': 2,
'MASTER_CACHE': '<master host>:<master port>',
},
},
}
django-redis-cache shares the same API as django’s built-in cache backends,
with a few exceptions.
cache.delete_pattern
Delete keys using glob-style pattern.
example::
>>> from news.models import Story
>>>
>>> most_viewed = Story.objects.most_viewed()
>>> highest_rated = Story.objects.highest_rated()
>>> cache.set('news.stories.most_viewed', most_viewed)
>>> cache.set('news.stories.highest_rated', highest_rated)
>>> data = cache.get_many(['news.stories.highest_rated', 'news.stories.most_viewed'])
>>> len(data)
2
>>> cache.delete_pattern('news.stores.*')
>>> data = cache.get_many(['news.stories.highest_rated', 'news.stories.most_viewed'])
>>> len(data)
0
cache.clear
Same as django’s cache.clear, except that you can optionally specify a
version and all keys with that version will be deleted. If no version is
provided, all keys are flushed from the cache.
cache.reinsert_keys
This helper method retrieves all keys and inserts them back into the cache. This
is useful when changing the pickle protocol number of all the cache entries.
As of django-redis-cache < 1.0, all cache entries were pickled using version 0.
To reduce the memory footprint of the redis-server, simply run this method to
upgrade cache entries to the latest protocol.
A common problem with caching is that you can sometimes get into a situation
where you have a value that takes a long time to compute or retrieve, but have
clients accessing it a lot. For example, if you wanted to retrieve the latest
tweets from the twitter api, you probably want to cache the response for a number
of minutes so you don’t exceed your rate limit. However, when the cache entry
expires you can have mulitple clients that see there is no entry and try to
simultaneously fetch the latest results from the api.
The way to get around this problem you pass in a callable and timeout to
get_or_set, which will check the cache to see if you need to compute the
value. If it does, then the cache sets a placeholder that tells future clients
to serve data from the stale cache until the new value is created.
Example::
tweets = cache.get_or_set('tweets', twitter.get_newest, timeout=300)
./install_redis.sh
make test
… _redis-py: http://github.com/andymccurdy/redis-py/
… _redis: http://github.com/antirez/redis/
… _hiredis: http://github.com/antirez/hiredis/
… _python: http://python.org