Decorator for using dicts/lists with any Python cache function (like lru_cache)

hashable_cache.py

# Inspired by https://gist.github.com/harel/9ced5ed51b97a084dec71b9595565a71

from collections import namedtuple
import functools
import json
import six

Serialized = namedtuple('Serialized', 'json')


def hashable_cache(cache):
    def hashable_cache_internal(func):
        def deserialize(value):
            if isinstance(value, Serialized):
                return json.loads(value.json)
            else:
                return value

        def func_with_serialized_params(*args, **kwargs):
            _args = tuple([deserialize(arg) for arg in args])
            _kwargs = {k: deserialize(v) for k, v in six.viewitems(kwargs)}
            return func(*_args, **_kwargs)

        cached_func = cache(func_with_serialized_params)

        @functools.wraps(func)
        def hashable_cached_func(*args, **kwargs):
            _args = tuple([
                Serialized(json.dumps(arg, sort_keys=True))
                if type(arg) in (list, dict) else arg
                for arg in args
            ])
            _kwargs = {
                k: Serialized(json.dumps(v, sort_keys=True))
                if type(v) in (list, dict) else v
                for k, v in kwargs.items()
            }
            return cached_func(*_args, **_kwargs)
        hashable_cached_func.cache_info = cached_func.cache_info
        hashable_cached_func.cache_clear = cached_func.cache_clear
        return hashable_cached_func

    return hashable_cache_internal


# Example usage below

from cachetools.func import lru_cache

@hashable_cache(lru_cache())
def fib(n):
    assert n >= 0
    if n == 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n - 1) + fib(n - 2)