---
nav_title: Rust
nav_order: 10
---
# Rust
`lemma-engine` is the engine itself. Crate name `lemma-engine`, imported as `lemma`.
## Install
```bash
cargo add lemma-engine --rename lemma
```
## Usage
```rust
use lemma::{DateTimeValue, Engine, IndexMap, SourceType};
use std::path::PathBuf;
use std::sync::Arc;
let mut engine = Engine::new();
engine.load([(
SourceType::Path(Arc::new(PathBuf::from("example.lemma"))),
r#"
spec compensation
data base_salary: 60000
data bonus_rate: 10%
rule bonus: base_salary * bonus_rate
rule total: base_salary + bonus
"#
.to_string(),
)])?;
let now = DateTimeValue::now();
let response = engine.evaluate(
None,
"compensation",
Some(&now),
IndexMap::new(),
None,
false,
)?;
for (rule_name, rule_result) in &response.results {
if !rule_result.vetoed {
println!("{rule_name}: {}", rule_result.result().unwrap_or(""));
}
}
```
## Providing values at runtime
```rust
use lemma::{DateTimeValue, Engine, IndexMap, SourceType};
use std::path::PathBuf;
use std::sync::Arc;
let mut engine = Engine::new();
engine.load([(
SourceType::Path(Arc::new(PathBuf::from("example.lemma"))),
r#"
spec shipping
uses lemma units
data weight: 5 kilogram
data destination: "domestic"
rule rate: 10
unless weight > 10 kilogram then 15
unless destination is "international" then 25
rule valid: weight <= 30 kilogram
unless weight > 30 kilogram then veto "Package too heavy for shipping"
"#
.to_string(),
)])?;
let mut values = IndexMap::new();
values.insert("weight".to_string(), "12 kilogram".into());
values.insert("destination".to_string(), "international".into());
let now = DateTimeValue::now();
let response = engine.evaluate(
None,
"shipping",
Some(&now),
values,
None,
false,
)?;
```
## Evaluation data
`evaluate` takes an `IndexMap<String, EvaluateDataValue>`. An `EvaluateDataValue` is a `Literal` (Lemma literal text such as `"12 kilogram"`, `"84"`, `"2025-03-01"`), a `Boolean`, a `Map` (a single-unit map like `{"eur": "84"}` for a measure or ratio) or a `List`. `&str` and `String` convert into `Literal` with `.into()`. Numbers travel as text so that they stay exact; see [Numeric precision](../learn/precision.md).
A list is one key holding a `List`: `Literal` items for a value list, `Map` items keyed by the row spec's data names for an instance list. The list replaces every row written in the spec. In the response, a list-valued rule carries `list` and a row-valued rule carries `row`, whose `index` points into `Response.rows`, where each referenced row appears once with its `data` and `rules`. See [Lists](../learn/lists.md).
## Show vs evaluate discovery
`Engine::show` returns the static planning catalog: `Show.types` (local data declarations), `Show.data` (inputs rules need: non-empty `needed_by_rules`, with `path` for import identity), plus this spec's own rules as `ShowRule` (`type`, `path`, `branches`, `depends_on_rules` as `input_key`). Branch Rule leaves may name reachable imports that are not `Show.rules` keys; follow those via `show` on the imported spec. `lemma::api::show_document(&engine, &show)` turns it into the JSON document every surface returns: a Draft 2020-12 JSON Schema for the evaluation data (`properties`, `required`, `$defs` row schemas) with Lemma metadata under `x-lemma-*` (`x-lemma-type`, `x-lemma-path`, `x-lemma-needed-by-rules`, `x-lemma-value`, `x-lemma-suggestion`, `x-lemma-types`, `x-lemma-rules`, ...). Parent Show.rules keys that need a `$defs` row field through a list are under document-level `x-lemma-row-field-needed-by-rules`; `$defs` row properties keep empty `x-lemma-needed-by-rules` so `LemmaRow_*` schemas are identical across Show documents. Default `evaluate` evaluates this spec's rules; pass Show.rules keys only (imported names are a request error).
For requirements on a partial evaluation, call `evaluate` and inspect each rule's `missing_data` (`string[]` input keys in evaluation / decision-tree order; first key is the next fact the live tree needs). Local type catalog, filled literals, and `-> suggest` hints are on `Engine::show` (`Show.types` / `Show.data` values are `ShowData`) only. Bound inputs (caller evaluation bindings or spec-filled values) are omitted from `missing_data`; suggestions do not bind until supplied in `evaluate`'s data. Non-veto rule results flatten `RuleResultValue` onto each result (`result()` / typed fields). Pass `explain: true` as the last `evaluate` argument to attach per-rule explanation trees ([api.v1.json](../../../engine/schemas/api.v1.json)).
```rust
let response = engine.evaluate(
None,
"shipping",
Some(&now),
IndexMap::new(),
Some(&["rate".to_string()]),
false,
)?;
for key in &response.results["rate"].missing_data {
println!("need: {key}");
}
```
## Embedded units stdlib
`Engine::new()` loads `repo lemma` / `spec units` at compile time (import with `uses lemma units`). It always appears in `Engine::specs`. Formatted source: `engine.source(Some("lemma"), None, None)?`.
JSON documents for `show` / `evaluate` / bindings use `lemma::api` (`api::show_document`, `api::Response`, ...).
## API docs
Full Rust API documentation is published on [docs.rs](https://docs.rs/lemma-engine).