Python LRU Cache Decorator Per Instance

crzysdrs picture crzysdrs · Feb 18, 2013 · Viewed 11.2k times · Source

Using the LRU Cache decorator found here: http://code.activestate.com/recipes/578078-py26-and-py30-backport-of-python-33s-lru-cache/

from lru_cache import lru_cache
class Test:
    @lru_cache(maxsize=16)
    def cached_method(self, x):
         return x + 5

I can create a decorated class method with this but it ends up creating a global cache that applies to all instances of class Test. However, my intent was to create a per instance cache. So if I were to instantiate 3 Tests, I would have 3 LRU caches rather than 1 LRU cache that for all 3 instances.

The only indication I have that this is happening is when calling the cache_info() on the different class instances decorated methods, they all return the same cache statistics (which is extremely unlikely to occur given they are being interacted with very different arguments):

CacheInfo(hits=8379, misses=759, maxsize=128, currsize=128)
CacheInfo(hits=8379, misses=759, maxsize=128, currsize=128)
CacheInfo(hits=8379, misses=759, maxsize=128, currsize=128)

Is there a decorator or trick that would allow me to easily cause this decorator to create a cache for each class instance?

Answer

abarnert picture abarnert · Feb 18, 2013

Assuming you don't want to modify the code (e.g., because you want to be able to just port to 3.3 and use the stdlib functools.lru_cache, or use functools32 out of PyPI instead of copying and pasting a recipe into your code), there's one obvious solution: Create a new decorated instance method with each instance.

class Test:
    def cached_method(self, x):
         return x + 5
    def __init__(self):
         self.cached_method = lru_cache(maxsize=16)(self.cached_method)