2 releases
0.1.1 | Jul 21, 2022 |
---|---|
0.1.0 | Jul 18, 2022 |
#680 in Data structures
70KB
1K
SLoC
mini-rx: Tiny reactive programming change propagation a la scala.rx
Example
use mini_rx::*;
fn example() {
// setup
let side_effect = Cell::new(0);
let side_effect2 = RefCell::new(String::new());
// The centralized data dependency graph
let mut g = RxDAG::new();
// Create variables which you can set
let var1 = g.new_var(1);
let var2 = g.new_var("hello");
assert_eq!(var1.get(g.now()), &1);
assert_eq!(var2.get(g.now()), &"hello");
var1.set(&g, 2);
var2.set(&g, "world");
assert_eq!(var1.get(g.now()), &2);
assert_eq!(var2.get(g.now()), &"world");
// Create computed values which depend on these variables...
let crx1 = g.new_crx(move |g| var1.get(g) * 2);
// ...and other Rxs
let crx2 = g.new_crx(move |g| format!("{}-{}", var2.get(g), crx1.get(g) * 2));
// ...and create multiple values which are computed from a single function
let (crx3, crx4) = g.new_crx2(move |g| var2.get(g).split_at(3));
assert_eq!(crx1.get(g.now()), &4);
assert_eq!(crx2.get(g.now()), &"world-8");
assert_eq!(crx3.get(g.now()), &"wor");
assert_eq!(crx4.get(g.now()), &"ld");
var1.set(&g, 3);
var2.set(&g, &"rust");
assert_eq!(crx1.get(g.now()), &6);
assert_eq!(crx2.get(g.now()), &"rust-12");
assert_eq!(crx3.get(g.now()), &"rus");
assert_eq!(crx4.get(g.now()), &"t");
// Run side effects when a value is recomputed
let var3 = g.new_var(Vec::from("abc"));
let side_effect_ref = &side_effect;
let side_effect_ref2 = &side_effect2;
// borrowed values must outlive g but don't have to be static
g.run_crx(move |g| {
side_effect_ref.set(side_effect_ref.get() + var1.get(g));
side_effect_ref2.borrow_mut().push_str(&String::from_utf8_lossy(var3.get(g)));
});
assert_eq!(side_effect.get(), 3);
assert_eq!(&*side_effect2.borrow(), &"abc");
var1.set(&g, 4);
g.recompute();
assert_eq!(side_effect.get(), 7);
assert_eq!(&*side_effect2.borrow(), &"abcabc");
// Note that the dependencies aren't updated until .recompute or .now is called...
var3.set(&g, Vec::from("xyz"));
assert_eq!(side_effect.get(), 7);
assert_eq!(&*side_effect2.borrow(), &"abcabc");
g.recompute();
assert_eq!(side_effect.get(), 11);
assert_eq!(&*side_effect2.borrow(), &"abcabcxyz");
// the side-effect also doesn't trigger when none of its dependencies change
var2.set(&g, "rust-lang");
g.recompute();
assert_eq!(side_effect.get(), 11);
assert_eq!(&*side_effect2.borrow(), &"abcabcxyz");
assert_eq!(crx2.get(g.now()), &"rust-lang-16");
// lastly we can create derived values which will access or mutate part of the base value
// which are useful to pass to children
let dvar = var3.derive_using_clone(|x| &x[0], |x, char| {
x[0] = char;
});
assert_eq!(dvar.get(g.now()), &b'x');
dvar.set(&g, b'b');
assert_eq!(dvar.get(g.now()), &b'b');
assert_eq!(var3.get(g.now()), &b"byz");
dvar.set(&g, b'f');
assert_eq!(dvar.get(g.now()), &b'f');
assert_eq!(var3.get(g.now()), &b"fyz");
assert_eq!(&*side_effect2.borrow(), &"abcabcxyzbyzfyz");
}
Overview
mini-rx
is a bare-bones implementation of "reactive programming" in Rust with 1 dependency. It uses manual polling and integrates well with the borrow checker by storing all values in a central data dependency graph, RxDAG
.
The type of reactive programming is signal-based, which is similar to scala.rx but different than most libraries (which are stream-based) and maybe not technically FRP. Instead of manipulating a stream of values, you manipulate variables which trigger other computed values to recompute, which in turn trigger other values to recompute and side effects to run.
Key concepts/types
RxDAG
: stores all yourRx
s. Lifetime rules guarantee that they don't change while you have active references (see Lifetimes)new_var
: creates aVar
new_crx
: creates aCRx
run_crx
: runs a side-effect, will re-run when any of the accessedVar
s orCRx
s changenew_crx[n]
: createsn
CRx
s which come from a single computationrecompute
: updates allVar
andCRx
values, but requires a mutable reference which ensures there are no active shared references to the old valuesnow
: recomputes and then gets anRxContext
so you can get values. It must recompute and thus requires a mutable reference.stale
: Does not recompute but will not return the most recently set values unlessrecompute
was called.
Var
: value with no dependencies which you explicitly set, and this triggers updatesCRx
: value computed from dependenciesRxContext
: allows you to readVar
andCRx
values. Accessible viaRxDAG::now
or in computations (RxDAG::new_crx
) and side-effects (RxDAG::run_crx
)MutRxContext
: allows you to write toVar
s. An&RxDAG
is aMutRxContext
. You cannot set values in aCRx
computation because they are inputs.
Signal-based
The type of reactive programming is signal-based, which is similar to scala.rx but different than most libraries (which are stream-based). Instead of manipulating a stream of values, you manipulate variables which trigger other computed values to recompute, which in turn trigger other values to recompute and side effects to run.
You can simulate stream-based reactivity by adding a side-effect which pushes values on trigger, like so:
use mini_rx::*;
fn stream_like() {
let stream = RefCell::new(Vec::new());
let stream_ref = &stream;
let input1 = vec![1, 2, 3];
let input2 = vec![0.5, 0.4, 0.8];
let mut g = RxDAG::new();
let var1 = g.new_var(0);
let var2 = g.new_var(0.0);
let crx = g.new_crx(move |g| *var1.get(g) as f64 + *var2.get(g));
g.run_crx(move |g| {
stream_ref.borrow_mut().push(*crx.get(g));
});
assert_eq!(&*stream.borrow(), &vec![0.0]);
for (a, b) in input1.iter().zip(input2.iter()) {
var1.set(&g, *a);
var2.set(&g, *b);
g.recompute();
}
assert_eq!(&*stream.borrow(), &vec![0.0, 1.5, 2.4, 3.8]);
}
For more traditional stream-based reactive programming, I recommend reactive-rs
Lifetimes
You can't obtain a mutable reference to the value stored within a Var
. Instead you call Var::set
or Var::modify
with a completely new value. This is because there may be active references to the old Var
. When you call Var::set
it doesn't immedidately change the old value, so those references won't change.
In order to actually update the reactive values and run side-effects, you must call RxDAG::recompute
, or a function which internally calls recompute
like RxDAG::now
. In order to do this, you need a mutable refernce to the RxDAG
, which you can only get if there are no active references to any of the reactive values.
Additionally, any compute function in the RxDAG
must live longer than the RxDAG
itself. This is because the function may be called any time while the RxDAG
is alive, when it gets recomputed. So if you have values which you reference in CRx
computations or side-effects, you must either declare them before the RxDAG
or use something like a Weak
reference to ensure that they are still alive when used.
Why? Signal-based Reactive programming 101
Here's a situation commonly encountered in programming: you have a value a
which should always equal b + c
. You don't want a
to be a function, but when b
or c
changes, a
must be recalculated.
Or here's another situation: you have an action which must always run when a value changes, which sends the updated value to the server.
You can chain these. Perhaps the value you want to send to the server on update is a
. Perhaps b
and c
are computed from other values, d, e, f
, and so on. Ultimately, for the theoretical folks, you have a DAG (directed-acyclic-graph) of values and dependencies. Modify one of the roots, and it triggers a cascade of computations and side effects.
Dependencies
~1.5MB
~37K SLoC