Merge pull request #724 from PThorpe92/extdocs

Add documentation for extensions/core
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# Limbo extension API
The `limbo_ext` crate simplifies the creation and registration of libraries meant to extend the functionality of `Limbo`, that can be loaded
like traditional `sqlite3` extensions, but are able to be written in much more ergonomic Rust.
---
## Currently supported features
- [ x ] **Scalar Functions**: Create scalar functions using the `ScalarDerive` derive macro and `Scalar` trait.
- [ x ] **Aggregate Functions**: Define aggregate functions with `AggregateDerive` macro and `AggFunc` trait.
- [] **Virtual tables**: TODO
---
## Installation
Add the crate to your `Cargo.toml`:
```toml
[dependencies]
limbo_ext = { path = "path/to/limbo/extensions/core" } # temporary until crate is published
```
**NOTE** Crate must be of type `cdylib`
```
[lib]
crate-type = ["cdylib"]
```
`cargo build` will output a shared library that can be loaded with `.load target/debug/libyour_crate_name`
Extensions can be registered with the `register_extension!` macro:
```rust
register_extension!{
scalars: { Double },
aggregates: { Percentile },
}
```
### Scalar Example:
```rust
use limbo_ext::{register_extension, Value, ScalarDerive, Scalar};
/// Annotate each with the ScalarDerive macro, and implement the Scalar trait on your struct
#[derive(ScalarDerive)]
struct Double;
impl Scalar for Double {
fn name(&self) -> &'static str { "double" }
fn call(&self, args: &[Value]) -> Value {
if let Some(arg) = args.first() {
match arg.value_type() {
ValueType::Float => {
let val = arg.to_float().unwrap();
Value::from_float(val * 2.0)
}
ValueType::Integer => {
let val = arg.to_integer().unwrap();
Value::from_integer(val * 2)
}
}
} else {
Value::null()
}
}
/// OPTIONAL: 'alias' if you would like to provide an additional name
fn alias(&self) -> &'static str { "twice" }
}
### Aggregates Example:
```rust
use limbo_ext::{register_extension, AggregateDerive, AggFunc, Value};
/// annotate your struct with the AggregateDerive macro, and it must implement the below AggFunc trait
#[derive(AggregateDerive)]
struct Percentile;
impl AggFunc for Percentile {
/// The state to track during the steps
type State = (Vec<f64>, Option<f64>, Option<String>); // Tracks the values, Percentile, and errors
/// Define the name you wish to call your function by.
/// e.g. SELECT percentile(value, 40);
fn name(&self) -> &'static str {
"percentile"
}
/// Define the number of arguments your function takes
fn args(&self) -> i32 {
2
}
/// Define a function called on each row/value in a relevant group/column
fn step(state: &mut Self::State, args: &[Value]) {
let (values, p_value, error) = state;
if let (Some(y), Some(p)) = (
args.first().and_then(Value::to_float),
args.get(1).and_then(Value::to_float),
) {
if !(0.0..=100.0).contains(&p) {
*error = Some("Percentile P must be between 0 and 100.".to_string());
return;
}
if let Some(existing_p) = *p_value {
if (existing_p - p).abs() >= 0.001 {
*error = Some("P values must remain consistent.".to_string());
return;
}
} else {
*p_value = Some(p);
}
values.push(y);
}
}
/// A function to finalize the state into a value to be returned as a result
/// or an error (if you chose to track an error state as well)
fn finalize(state: Self::State) -> Value {
let (mut values, p_value, error) = state;
if let Some(error) = error {
return Value::error(error);
}
if values.is_empty() {
return Value::null();
}
values.sort_by(|a, b| a.partial_cmp(b).unwrap());
let n = values.len() as f64;
let p = p_value.unwrap();
let index = (p * (n - 1.0) / 100.0).floor() as usize;
Value::from_float(values[index])
}
}
```