Crates.io | ascent |
lib.rs | ascent |
version | 0.7.0 |
source | src |
created_at | 2022-02-24 22:34:31.192143 |
updated_at | 2024-10-06 19:45:23.839127 |
description | Logic programming in Rust |
homepage | https://s-arash.github.io/ascent/ |
repository | https://github.com/s-arash/ascent |
max_upload_size | |
id | 538846 |
size | 121,337 |
Ascent is a logic programming language (similar to Datalog) embedded in Rust via macros.
For more information, check out the CC paper on Ascent.
In addition, this OOPSLA paper describes the "Bring Your Own Data Structures to Datalog" aspect of Ascent.
ascent! {
relation edge(i32, i32);
relation path(i32, i32);
path(x, y) <-- edge(x, y);
path(x, z) <-- edge(x, y), path(y, z);
}
cargo new my-ascent-project
cd my-ascent-project
ascent
as a dependency in Cargo.toml
:
[dependencies]
ascent = "*"
main.rs
. Here is a complete example:
use ascent::ascent;
ascent! {
relation edge(i32, i32);
relation path(i32, i32);
path(x, y) <-- edge(x, y);
path(x, z) <-- edge(x, y), path(y, z);
}
fn main() {
let mut prog = AscentProgram::default();
prog.edge = vec![(1, 2), (2, 3)];
prog.run();
println!("path: {:?}", prog.path);
}
cargo run
See the ascent/examples directory for a more complete set of examples.
Ascent supports computing fixed points of user-defined lattices. The lattice
keyword defines a lattice in Ascent. The type of the final column of a lattice
must implement the Lattice
trait. A lattice
is like a relation, except that when a new lattice
fact (v1, v2, ..., v(n-1), vn) is discovered, and a fact (v1, v2, ..., v(n-1), v'n) is already present in the database, vn and v'n are join
ed together to produce a single fact.
This feature enables writing programs not expressible in Datalog. For example we can use this feature to compute the lengths of shortest paths between nodes in a graph.
ascent! {
lattice shortest_path(i32, i32, Dual<u32>);
relation edge(i32, i32, u32);
shortest_path(x, y, Dual(*w)) <-- edge(x, y, w);
shortest_path(x, z, Dual(w + l)) <--
edge(x, y, w),
shortest_path(y, z, ?Dual(l));
}
In this example, Dual<T>
is the dual of the lattice T
. We use Dual<T>
because we are interested in shortest paths, given two path lengths l1
and l2
for any given pair of nodes, we only store min(l1, l2)
.
Ascent is capable of producing parallel code. The macros ascent_par!
and ascent_run_par!
produce parallelized code.
Naturally, column types must be Send + Sync
to work in parallel Ascent.
Parallel Ascent utilizes rayon
, so the parallelism level can be controlled either via rayon
's ThreadPoolBuilder
or using the RAYON_NUM_THREADS
environment variable (see here for more info).
BYODS (short for Bring Your Own Data Structures to Datalog) is a feature of Ascent that enables relations to be backed by custom data structures. This feature allows improving the algorithmic complexity of Ascent programs by optimizing the data structures used to back relations. For example, a program that requires transitive closure computation of a large graph could improve its performance by choosing a union-find based data structure trrel_uf
(defined in ascent-byods-rels
) for the transitive closure relation:
in Cargo.toml
:
[dependencies]
ascent-byods-rels = "*"
ascent = "*"
use ascent_byods_rels::trrel_uf;
ascent! {
relation edge(Node, Node);
#[ds(trrel_uf)] // Makes the relation transitive
relation path(Node, Node);
path(x, y) <-- edge(x, y);
}
The #[ds(trrel_uf)]
attribute directs the Ascent compiler to use the data structure provider defined in the module trrel_uf
for the path
relation.
You can find a complete example of BYODS dramatically speeding up Ascent computations here.
See BYODS.MD for more information on BYODS.
ascent_run!
In addition to ascent!
, we provide the ascent_run!
macro. Unlike ascent!
, this macro evaluates the ascent program when invoked. The main advantage of ascent_run!
is that local variables are in scope inside the Ascent program. For example, we can define a function for discovering the (optionally reflexive) transitive closure of a relation like so:
fn tc(r: Vec<(i32, i32)>, reflexive: bool) -> Vec<(i32, i32)> {
ascent_run! {
relation r(i32, i32) = r;
relation tc(i32, i32);
tc(x, y) <-- r(x, y);
tc(x, z) <-- r(x, y), tc(y, z);
tc(x, x), tc(y, y) <-- if reflexive, r(x, y);
}.tc
}
In the above example, we initialize the relation r
directly to shorten the program.
We also provide ascent_run_par!
, the parallel version of ascent_run!
.
The syntax is designed to be familiar to Rust users. In this example, edge
is populated with non-reflexive edges from node
. Note that any type that implements Clone + Eq + Hash
can be used as a relation column.
ascent! {
relation node(i32, Rc<Vec<i32>>);
relation edge(i32, i32);
edge(x, y) <--
node(x, neighbors),
for &y in neighbors.iter(),
if x != y;
}
Ascent supports stratified negation and aggregation. Aggregators are defined in ascent::aggregators
. You can find sum
, min
, max
, count
, and mean
there.
In the following example, the average grade of students is stored in avg_grade
:
use ascent::aggregators::mean;
type Student = u32;
type Course = u32;
type Grade = u16;
ascent! {
relation student(Student);
relation course_grade(Student, Course, Grade);
relation avg_grade(Student, Grade);
avg_grade(s, avg as Grade) <--
student(s),
agg avg = mean(g) in course_grade(s, _, g);
}
You can define your own aggregators if the provided aggregators are not sufficient. For example, an aggregator for getting the 2nd highest value of a column can have the following signature:
fn second_highest<'a, N: 'a>(inp: impl Iterator<Item = (&'a N,)>) -> impl Iterator<Item = N>
where N: Ord + Clone
Aggregators can even be parameterized! For an example of a parameterized aggregator, lookup the definition of percentile
in ascent::aggregators
.
It may be useful to define macros that expand to either body items or head items. Ascent allows you to do this.
You can find more about macros in Ascent macros here.
#![measure_rule_times]
causes execution times of individual rules to be measured. Example:
ascent! {
#![measure_rule_times]
// ...
}
let mut prog = AscentProgram::default();
prog.run();
println!("{}", prog.scc_times_summary());
Note that scc_times_summary()
is generated for all Ascent programs. With #![measure_rule_times]
it reports execution times of individual rules too.
With #![generate_run_timeout]
, a run_timeout
function is generated that stops after
the given amount of time.
The feature wasm-bindgen
allows Ascent programs to run in WASM environments.
struct
declarations can be added to the top of ascent!
definitions. This allows changing the
name and visibility of the generated type and introduction of type/lifetime parameters and constraints.
ascent! {
struct GenericTC<N: Clone + Eq + Hash>;
relation edge(N, N);
// ...
}
Hint: If you get a "private type ... in public interface (error E0446)" warning, you can fix it by making the generated Ascent type private, as done in the above example.