# entrait
A proc macro to ease development using _Inversion of Control_ patterns in Rust.
`entrait` is used to generate a trait from the definition of a regular function.
The main use case for this is that other functions may depend upon the trait
instead of the concrete implementation, enabling better test isolation.
The macro looks like this:
```rust
#[entrait(MyFunction)]
fn my_function<D>(deps: &D) {
}
```
which generates the trait `MyFunction`:
```rust
trait MyFunction {
fn my_function(&self);
}
```
`my_function`'s first and only parameter is `deps` which is generic over some unknown type `D`.
This would correspond to the `self` parameter in the trait.
But what is this type supposed to be? We can generate an implementation in the same go, using `for Type`:
```rust
struct App;
#[entrait::entrait(MyFunction for App)]
fn my_function<D>(deps: &D) {
}
// Generated:
// trait MyFunction {
// fn my_function(&self);
// }
//
// impl MyFunction for App {
// fn my_function(&self) {
// my_function(self)
// }
// }
fn main() {
let app = App;
app.my_function();
}
```
The advantage of this pattern comes into play when a function declares its dependencies, as _trait bounds_:
```rust
#[entrait(Foo for App)]
fn foo(deps: &(impl Bar))
{
deps.bar();
}
#[entrait(Bar for App)]
fn bar<D>(deps: &D) {
}
```
The functions may take any number of parameters, but the first one is always considered specially as the "dependency parameter".
Functions may also be non-generic, depending directly on the App:
```rust
#[entrait(ExtractSomething for App)]
fn extract_something(app: &App) -> SomeType {
app.some_thing
}
```
These kinds of functions may be considered "leaves" of a dependency tree.
### "Philosophy"
The idea behind `entrait` is to explore a specific architectural pattern:
* Interfaces with _one_ runtime implementation
* named traits as the interface of single functions
`entrait` does not implement Dependency Injection (DI). DI is a strictly object-oriented concept that will often look awkward in Rust.
The author thinks of DI as the "reification of code modules": In a DI-enabled programming environment, code modules are grouped together
as _objects_ and other modules may depend upon the _interface_ of such an object by receiving some instance that implements it.
When this pattern is applied successively, one ends up with an in-memory dependency graph of high-level modules.
`entrait` tries to turn this around by saying that the primary abstraction that is depended upon is a set of _functions_, not a set of code modules.
An architectural consequence is that one ends up with _one ubiquitous type_ that represents a running application that implements all
these function abstraction traits. But the point is that this is all loosely coupled: Most function definitions themselves do not refer
to this god-like type, they only depend upon traits.
### `async` support
Since Rust at the time of writing does not natively support async methods in traits, you may opt in to having `#[async_trait]` generated
for your trait:
```rust
#[entrait(Foo, async_trait=true)]
async fn foo<D>(deps: &D) {
}
```
This is designed to be forwards compatible with real async fn in traits. When that day comes, you should be able to just remove the `async_trait=true`
to get a proper zero-cost future.
### Mock support
The macro supports autogenerating [mockall] mock structs:
[mockall]: https://docs.rs/mockall/latest/mockall/
```rust
#[entrait(Foo, mockall=true)]
fn foo<D>(_: &D) -> u32 {
unimplemented!()
}
fn my_func(deps: &(impl Foo)) -> u32 {
deps.foo()
}
fn main() {
let mut deps = MockFoo::new();
deps.expect_foo().returning(|| 42);
assert_eq!(42, my_func(&deps));
}
```
Using `mockall` is easy enough when there is only one trait bound, because the generated trait need only be attributed with `mockall::automock`.
#### multiple trait bounds with `unimock`
With multiple trait bounds, this becomes a little harder: We need some concrete struct that implement all the given traits.
This is easily solved by the crate [unimock], and using `unimock = true`:
[unimock]: https://docs.rs/unimock/latest/unimock/
```rust
use unimock::Unimock;
#[entrait(Foo, unimock=true)]
fn foo<D>(_: &D) -> u32 {
unimplemented!()
}
#[entrait(Bar, unimock=true)]
fn bar<D>(_: &D) -> u32 {
unimplemented!()
}
fn my_func(deps: &(impl Foo + Bar)) -> u32 {
deps.foo() + deps.bar()
}
fn main() {
let deps = Unimock::new()
.mock(|foo: &mut MockFoo| {
foo.expect_foo().returning(|| 40);
})
.mock(|bar: &mut MockBar| {
bar.expect_bar().returning(|| 2);
});
assert_eq!(42, my_func(&deps));
}
```
`unimock = true` implies `mockall = true`.
#### conditional mock implementations
Most often, you will only need to generate mock implementations in test code, and skip this for production code. For this, there are the `test` variants:
* `mockall = test`
* `unimock = test`
which puts the corresponding attributes in `#[cfg_attr(test, ...)]`:
```rust
#[entrait(Foo, unimock=test)]
fn foo<D>(_: &D) -> u32 {
unimplemented!()
}
fn takes_foo(foo: impl Foo) {}
fn main() {
// we can still instantiate Unimock, but it's not useful,
// because now it doesn't implement `Foo`:
let mock = unimock::Unimock::new();
//takes_foo(mock);
//--------- ^^^^ the trait `Foo` is not implemented for `Unimock`
}
#[test]
fn test() {
// this compiles!
let mock = unimock::Unimock::new();
takes_foo(mock);
}
```
This is opt-in because there could be scenarios where this behaviour is not desired, e.g. when you write a library and want mocks exported for those.
License: MIT