Python LRU Cache Decorator Per Instance

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:

Solution 1:

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)

Solution 2:

How about this: a function decorator that wraps the method with lru_cache the first time it's called on each instance?

def instance_method_lru_cache(*cache_args, **cache_kwargs):
    def cache_decorator(func):
        @wraps(func)
        def cache_factory(self, *args, **kwargs):
            print('creating cache')
            instance_cache = lru_cache(*cache_args, **cache_kwargs)(func)
            instance_cache = instance_cache.__get__(self, self.__class__)
            setattr(self, func.__name__, instance_cache)
            return instance_cache(*args, **kwargs)
        return cache_factory
    return cache_decorator

Use it like this:

class Foo:
    @instance_method_lru_cache()
    def times_2(self, bar):
        return bar * 2

foo1 = Foo()
foo2 = Foo()

print(foo1.times_2(2))
# creating cache
# 4
foo1.times_2(2)
# 4

print(foo2.times_2(2))
# creating cache
# 4
foo2.times_2(2)
# 4

Here's a gist on GitHub with some inline documentation.

Solution 3:

These days, methodtools will work

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

You need to install methodtools

pip install methodtools

If you are still using py2, then functools32 also is required

pip install functools32