rand-functors
provides an abstraction over different ways of evaluating random processes expressed as functions of both deterministic and stochastic data. This is achieved using a combination of a type-based version of the Strategy pattern and functional programming's Functor pattern.
A motivating problem for this crate is the code duplication present across these two functions modelling the same random process:
use rand::prelude::*;
fn next_state(mut state: u8) -> u8 {
state = state.wrapping_add(random());
if random() {
state %= 3;
}
state
}
fn next_states(state: u8) -> Vec<u8> {
let mut out: Vec<_> = (0..=255).map(|r| state.wrapping_add(r)).collect();
out.append(&mut out.iter().copied().map(|i| i % 3).collect());
out
}
While these functions may appear different, the same random process is embedded in both of them. A random u8
is added to state
and then, if a random bool
is true
, the state will be set to itself modulo 3.
This redundant implementation of the random process could pose issues during a refactor. If one decides to change the %= 3
to a %= 5
in next_state
, he or she will need to make the corresponding update in next_states
.
Using rand-functors
, these two functions can be combined as:
use rand::prelude::*;
use rand_functors::{Functor, RandomStrategy};
fn next_state<S: RandomStrategy>(state: u8) -> S::Functor<u8> {
let mut out = S::fmap_rand(Functor::pure(state), &mut thread_rng(), |s, r| {
s.wrapping_add(r)
});
out = S::fmap_rand(out, &mut thread_rng(), |s, r| if r { s % 3 } else { s });
out
}
This new implementation makes next_state
generic over a RandomStrategy
S
. Its return type is also changed to the Functor
associated with S
. Inside, state
is converted from u8
to S::Functor<u8>
. The remainder of the function is essentially the same as the original next_state
, but each operation a random sample is now wrapped in a call to S::fmap_rand
. Calling next_state::<Sampler>(s)
would be equivalent to calling next_state(s)
before. Similarly, one could call next_state::<Enumerator>(s)
instead of using next_states(s)
, which would require maintaining a separate implementation of the same core process.
At present, rand-functors
only supports random variables that are either of type bool
or of a numeric type occupying no more than 16 bits by default. However, it is possible to implement all the requisite traits for a custom data type.