Python3 pass lists to function with functools.lru_cache

This fails because a list is unhashable. This would make it hard for Python to know what values are cached. A way to fix this is by converting lists to tuples before passing them to a cached function: since tuples are immutable and hashable, they can be cached.

TL;DR

Use a tuple instead of a list:

>>> @lru_cache(maxsize=2)... def my_function(args):...     pass...>>> my_function([1,2,3])Traceback (most recent call last):  File "<input>", line 1, in <module>    my_function([1,2,3])TypeError: unhashable type: 'list'>>> # TO FIX: use a tuple >>> my_function(tuple([1,2,3]))>>>

It should not throw an error, rather convert into hash-able form within decorator without user even knowing it. You can fix this problem by decorating your functions like this:

#Custom Decorator functiondef listToTuple(function):    def wrapper(*args):        args = [tuple(x) if type(x) == list else x for x in args]        result = function(*args)        result = tuple(result) if type(result) == list else result        return result    return wrapper#your cached function@listToTuple@lru_cache(maxsize=cacheMaxSize)def checkIfAdminAcquired(self, adminId) -> list:    query = "SELECT id FROM public.admins WHERE id IN ({}) and     confirmed_at IS NOT NULL"    response = self.handleQuery(query, "int", adminId)    return response

You might want to use yet another decorator after lru_cache to make sure that output of the function is not a tuple, but a list, since right now it will return tuple.

Sometimes a parameter can take either a simple hashable type, or a complicated unhashable type without a straightforward conversion to be hashable, as the current answers propose. In this situation it may still be desirable to have a cache used for the (possibly more common) case of hashable type without using a cache or erroring out in the unhashable case - simply calling the underlying function.

This ignores the error and works generally for any hashable type:

import functoolsdef ignore_unhashable(func):     uncached = func.__wrapped__    attributes = functools.WRAPPER_ASSIGNMENTS + ('cache_info', 'cache_clear')    @functools.wraps(func, assigned=attributes)     def wrapper(*args, **kwargs):         try:             return func(*args, **kwargs)         except TypeError as error:             if 'unhashable type' in str(error):                 return uncached(*args, **kwargs)             raise     wrapper.__uncached__ = uncached    return wrapper

Usage and testing:

@ignore_unhashable@functools.lru_cache()def example_func(lst):    return sum(lst) + max(lst) + min(lst)example_func([1, 2]) # 6example_func.cache_info()# CacheInfo(hits=0, misses=0, maxsize=128, currsize=0)example_func((1, 2)) # 6example_func.cache_info()# CacheInfo(hits=0, misses=1, maxsize=128, currsize=1)example_func((1, 2)) # 6example_func.cache_info()# CacheInfo(hits=1, misses=1, maxsize=128, currsize=1)

Took me a moment to wrap my head around it, but example_func.__wrapped__ is the lru_cache's version and example_func.__uncached__ is the original version.