Version information

Version 1.0.2, requires Python 2.4 or higher.

Features

• fast in memory caching of any object
• transparent dictionnary-like usage
• possibility to limit the cache size in number of objects
• possibility to expire automatically objects after a given time of no update
• thread-safe

Basic usage

Creating a cache:

>>> from GenericCache.GenericCache import GenericCache
>>> c = GenericCache()

Storing values:

>>> c["key"] = "value"
   or
>>> c.insert("key", "value")

Retrieving values:

>>> c["key"]
   or
>>> c.fetch("key")

None is returned if no value is found in the cache. Fetch can take an optional value to fail with KeyError if no value is found.

Warnings

• in current implementation keys are converted into strings
• object expiry for timeout is lazy, which means that objects stay in the cache until someone try to access them, len() will still see them; there is a collect() method to collect all timeouted objects, but it may be slow.

Decorator usage

The decorator, for Python 2.4+, can be used to decorate any function or method. Here is an example:

>>> from GenericCache.GenericCache import GenericCache
>>> from GenericCache.decorators import cached
>>> cache = GenericCache()
>>> @cached(cache)
... def add(x, y):
...     print x, "+", y
...     return x + y
...
>>> add(2,3)
2 + 3
5
>>> add(2,3)
5
>>> add(2,4)
2 + 4
6
>>> add(2,4)
6
>>> add(2,3)
5
>>>

The decorator takes an optional parameter, a marshaller that filter the paramters of the function and converts it into a caching key (some parameters may be discarded, for example).