Lightweight and extensible caching framework for Python applications. It uses Redis as its storage backend.
RedCache is a lightweight and extensible caching framework for Python applications. It uses Redis as its storage backend.
Suppose we have a function that loads data from a remote source:
def load_something_from_somewhere(): # Load the data... return data
Now let’s use it in a Flask view:
@app.route('/something/') def get_something(): data = load_something_from_somewhere() # Do something with the data... return jsonify(data=data)
The problem here is that the view will wait until the data is fetched. If the view is called often it’ll generate significant traffic between our server and the remote source. This isn’t pretty.
What if we cached the loaded data for some time and refresh it only when the cache expires? That would be pretty.
There are many caching solutions, e.g. Beaker. RedCache is similar to (and inspired by) Beaker but provides only one storage backend - Redis.
So, how do you cache load_something_from_somewhere using Redis and RedCache?
First setup Redis connection before starting the app:
from redcache import use_connection use_connection()
Then make the function cached:
from redcache import default_cache @default_cache.cache(ttl=5) def load_something_from_somewhere(): # Load the data... return data
Next time load_something_from_somewhere is called RedCache will try to load its last return value from Redis. If it’s not found then the function will be executed and its return value stored in Redis for 5 seconds.
redcache.default_cache is an instance of redcache.cache_manager.DefaultCacheManager which gives convenient access to caching mechanism which uses cPickle behind the scenes. By default the keys will be stored infinitely. Use ttl keyword argument in the decorator to define different TTL.
Extending and advanced use
RedCache can be easily extended to utilize Redis’ datatypes and features.
By overriding redcache.cache_manager.CacheManager.after_load and redcache.cache_manager.CacheManager.before_save you can perform additional operations on data. This way you can e.g. store JSON strings instead of pickled objects.
By overriding redcache.cache_manager.CacheManager.load and redcache.cache_manager.CacheManager.save you can change the way data is loaded and saved. This way you can e.g. store lists of individual objects and retrieve them according to pagination options.
Consult examples to see how to integrate RedCache with SQLAlchemy and to see how to use JSON instead of cPickle.
Source code is available from project repository on GitHub.
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