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pythonmemoization

How to apply functools.lru_cache to function with mutable parameters?

I have a function with one of the parameters as numpy.ndarray. It's mutable so it can not be cached by lru_cache.

Is there any existing solution for this?

Solution

  • Possibly the simplest way of doing so is to memoize a version taking only immutable objects.

    Say your function takes an np.array, and let's assume it's a 1d array. Fortunately, it is easily translated to a tuple:

    import numpy as np

a = np.array([1, 2, 3, 4])
>> tuple(a)
(1, 2, 3, 4)

    and vice versa:

    >> np.array(tuple(a))
array([1, 2, 3, 4])

    So you get something like

    # Function called by the rest of your program
array_foo(a) # `a` is an `np.array`
    ...
    return tuple_foo(tuple(a))

    then memoize instead this function:

    # Internal implementation
@functools.lru_cache
tuple_foo(t) # `t` is a tuple
    ...
    a = np.array(t)