python: bookkeeping dependencies in cached attributes that might change

Question

I have a class A with three attributes a,b,c, where a is calculated from b and c (but this is expensive). Moreover, attributes b and c are likely to change over times. I want to make sure that:

1. a is cached once it is calculated and then reproduced from cache
2. if b or c change then the next time a is needed it must be recomputed to reflect the change

the following code seems to work:

class A():

    def __init__(self, b, c):
        self._a = None
        self._b = b
        self._c = c

    @property
    def a(self):
        if is None:
            self.update_a()
        return self._a

    def update_a(self):
        """
        compute a from b and c
        """
        print('this is expensive')
        self._a = self.b + 2*self.c

    @property
    def b(self):
        return self._b

    @b.setter
    def b(self, value):
        self._b = value
        self._a = None #make sure a is recalculated before its next use

    @property
    def c(self):
        return self._c

    @c.setter
    def c(self, value):
        self._c = value
        self._a = None #make sure a is recalculated before its next use

however this approach does not seem very good for many reasons:

1. the setters of b and c needs to know about a
2. it becomes a mess to write and maintain if the dependency-tree grows larger
3. it might not be apparent in the code of update_a what its dependencies are
4. it leads to a lot of code duplication

Is there an abstract way to achieve this that does not require me to do all the bookkeeping myself? Ideally, I would like to have some sort of decorator which tells the property what its dependencies are so that all the bookkeeping happens under the hood.

I would like to write:

@cached_property_depends_on('b', 'c')
def a(self):
    return self.b+2*self.c

or something like that.

EDIT: I would prefer solutions that do not require that the values assigned to a,b,c be immutable. I am mostly interested in np.arrays and lists but I would like the code to be reusable in many different situations without having to worry about mutability issues.

Answer 1

You could use functools.lru_cache:

from functools import lru_cache
from operator import attrgetter

def cached_property_depends_on(*args):
    attrs = attrgetter(*args)
    def decorator(func):
        _cache = lru_cache(maxsize=None)(lambda self, _: func(self))
        def _with_tracked(self):
            return _cache(self, attrs(self))
        return property(_with_tracked, doc=func.__doc__)
    return decorator

The idea is to retrieve the values of tracked attributes each time the property is accessed, pass them to the memoizing callable, but ignore them during the actual call.

Given a minimal implementation of the class:

class A:

    def __init__(self, b, c):
        self._b = b
        self._c = c

    @property
    def b(self):
        return self._b

    @b.setter
    def b(self, value):
        self._b = value

    @property
    def c(self):
        return self._c

    @c.setter
    def c(self, value):
        self._c = value

    @cached_property_depends_on('b', 'c')
    def a(self):
        print('Recomputing a')
        return self.b + 2 * self.c

a = A(1, 1)
print(a.a)
print(a.a)
a.b = 3
print(a.a)
print(a.a)
a.c = 4
print(a.a)
print(a.a)

outputs

Recomputing a
3
3
Recomputing a
5
5
Recomputing a
11
11