Store the cache to a file functools.lru_cache in Python >= 3.2

You can't do what you want using lru_cache, since it doesn't provide an API to access the cache, and it might be rewritten in C in future releases. If you really want to save the cache you have to use a different solution that gives you access to the cache.

It's simple enough to write a cache yourself. For example:

from functools import wrapsdef cached(func):    func.cache = {}    @wraps(func)    def wrapper(*args):        try:            return func.cache[args]        except KeyError:            func.cache[args] = result = func(*args)            return result       return wrapper

You can then apply it as a decorator:

>>> @cached... def fibonacci(n):...     if n < 2:...             return n...     return fibonacci(n-1) + fibonacci(n-2)... >>> fibonacci(100)354224848179261915075L

And retrieve the cache:

>>> fibonacci.cache{(32,): 2178309, (23,): 28657, ... }

You can then pickle/unpickle the cache as you please and load it with:

fibonacci.cache = pickle.load(cache_file_object)

I found a feature request in python's issue tracker to add dumps/loads to lru_cache, but it wasn't accepted/implemented. Maybe in the future it will be possible to have built-in support for these operations via lru_cache.

You can use a library of mine, mezmorize

import randomfrom mezmorize import Cachecache = Cache(CACHE_TYPE='filesystem', CACHE_DIR='cache')@cache.memoize()def add(a, b):    return a + b + random.randrange(0, 1000)>>> add(2, 5)727>>> add(2, 5)727

Consider using joblib.Memory for persistent caching to the disk.

Since the disk is enormous, there's no need for an LRU caching scheme.