[Python-ideas] Using functools.lru_cache only on some arguments of a function

[Serhiy Storchaka]

On 04.12.15 23:44, Bill Winslow wrote:
> This is a question I posed to reddit, with no real resolution:
> https://www.reddit.com/r/learnpython/comments/3v75g4/using_functoolslru_cache_only_on_some_arguments/
>
> The summary for people here is the following:
>
> Here's a pattern I'm using for my code:
>
> def deterministic_recursive_calculation(input, partial_state=None):
>      condition = do_some_calculations(input)
>      if condition:
>          return deterministic_recursive_calculation(reduced_input,
> some_state)
>
> Basically, in calculating the results of the subproblem, the subproblem
> can be calculated quicker by including/sharing some partial results from
> the superproblem. (Calling the subproblem without the partial state
> still gives the same result, but takes substantially longer.)
>
> I want to memoize this function for obvious reasons, but I need the
> lru_cache to ignore the partial_state argument, for its value does not
> affect the output, only the computation expense.
>
> Is there any reasonable way to do this?

Memoize a closure.

def deterministic_calculation(input):
     some_state = ...
     @lru_cache()
     def recursive_calculation(input):
         nonlocal some_state
         ...
         return recursive_calculation(reduced_input)
     return recursive_calculation(input)