# Logic programming in Rust
[](https://github.com/s-arash/ascent/actions/workflows/rust.yml) [](https://crates.io/crates/ascent)
Ascent is a logic programming language (similar to Datalog) embedded in Rust via macros.
For more information, check out [the CC paper](https://s-arash.github.io/ascent/cc22main-p95-seamless-deductive-inference-via-macros.pdf) on Ascent.
## Examples
### Computing all the connected nodes in a graph
```Rust
ascent!{
relation edge(i32, i32);
relation path(i32, i32);
path(x, y) <-- edge(x, y);
path(x, z) <-- edge(x, y), path(y, z);
}
```
## Using Ascent
1. [Install Rust](https://www.rust-lang.org/tools/install).
2. Make a new Rust project:
```bash
cargo new my-ascent-project
cd my-ascent-project
```
3. Add `ascent` as a dependency in `Cargo.toml`:
```toml
[dependencies]
ascent = "0.3"
# or:
# ascent = {git = "https://github.com/s-arash/ascent"}
```
4. Write some Ascent code in `main.rs`. Here is a complete example:
```rust
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);
}
```
5. Run the program:
```bash
cargo run
```
## Features
### Lattices
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 (v<sub>1</sub>, v<sub>2</sub>, ..., v<sub>(n-1)</sub>, v<sub>n</sub>) is discovered, and a fact (v<sub>1</sub>, v<sub>2</sub>, ..., v<sub>(n-1)</sub>, v'<sub>n</sub>) is already present in the database, v<sub>n</sub> and v'<sub>n</sub> 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.
```Rust
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)`.
### Conditions and Generative clauses
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.
```Rust
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;
}
```
### Negation and Aggregation
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`:
```Rust
use ascent::aggregators::*;
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:
```Rust
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`](./ascent/src/aggregators.rs).
### `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:
```Rust
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.
### Macro definitions
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](MACROS.MD).
### Misc
- `#![measure_rule_times]` causes execution times of individual rules to be measured. Example:
```Rust
ascent! {
#![measure_rule_times]
// ...
}
```
- 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.