# [juniper-from-schema](https://crates.io/crates/juniper-from-schema)
**Important notice**: This project is still in a very experimental state. It does work but the API might change drastically.
---
This library exposes a procedural macro that reads a GraphQL schema file, and generates the
corresponding Juniper macro calls. This means you can have a real schema file and be guaranteed
that it matches your Rust implementation. It also removes most of the boilerplate from using
Juniper.
## Example
Schema:
```graphql
schema {
query: Query
mutation: Mutation
}
type Query {
// this makes the return value `FieldResult<String>`
// rather than the default `FieldResult<&String>`
"#[ownership(owned)]"
helloWorld(name: String!): String!
}
type Mutation {
noop: Boolean!
}
```
Rust implementation of schema:
```rust
#[macro_use]
extern crate juniper;
use juniper::*;
use juniper_from_schema::graphql_schema_from_file;
// This is the important line
graphql_schema_from_file!("tests/schemas/doc_schema.graphql");
pub struct Context;
impl juniper::Context for Context {}
pub struct Query;
impl QueryFields for Query {
fn field_hello_world(
&self,
executor: &Executor<'_, Context>,
name: String,
) -> FieldResult<String> {
Ok(format!("Hello, {}!", name))
}
}
pub struct Mutation;
impl MutationFields for Mutation {
fn field_noop(&self, executor: &Executor<'_, Context>) -> FieldResult<&bool> {
Ok(&true)
}
}
fn main() {
let ctx = Context;
let query = "query { helloWorld(name: \"Ferris\") }";
let (result, errors) = juniper::execute(
query,
None,
&Schema::new(Query, Mutation),
&Variables::new(),
&ctx,
)
.unwrap();
assert_eq!(errors.len(), 0);
assert_eq!(
result
.as_object_value()
.unwrap()
.get_field_value("helloWorld")
.unwrap()
.as_scalar_value::<String>()
.unwrap(),
"Hello, Ferris!",
);
}
```
This expands into:
```rust
#[macro_use]
extern crate juniper;
use juniper::*;
pub struct Context;
impl juniper::Context for Context {}
pub struct Query;
graphql_object!(Query: Context |&self| {
field hello_world(&executor, name: String) -> FieldResult<String> {
<Self as QueryFields>::field_hello_world(&self, &executor, name)
}
});
trait QueryFields {
fn field_hello_world(
&self,
executor: &Executor<'_, Context>,
name: String,
) -> FieldResult<String>;
}
impl QueryFields for Query {
fn field_hello_world(
&self,
executor: &Executor<'_, Context>,
name: String,
) -> FieldResult<String> {
Ok(format!("Hello, {}!", name))
}
}
pub struct Mutation;
graphql_object!(Mutation: Context |&self| {
field noop(&executor) -> FieldResult<&bool> {
<Self as MutationFields>::field_noop(&self, &executor)
}
});
trait MutationFields {
fn field_noop(&self, executor: &Executor<'_, Context>) -> FieldResult<&bool>;
}
impl MutationFields for Mutation {
fn field_noop(&self, executor: &Executor<'_, Context>) -> FieldResult<&bool> {
Ok(&true)
}
}
type Schema = juniper::RootNode<'static, Query, Mutation>;
fn main() {
let ctx = Context;
let query = "query { helloWorld(name: \"Ferris\") }";
let (result, errors) = juniper::execute(
query,
None,
&Schema::new(Query, Mutation),
&Variables::new(),
&ctx,
)
.unwrap();
assert_eq!(errors.len(), 0);
assert_eq!(
result
.as_object_value()
.unwrap()
.get_field_value("helloWorld")
.unwrap()
.as_scalar_value::<String>()
.unwrap(),
"Hello, Ferris!",
);
}
```
## Customizing ownership
By default all fields return borrowed values. Specifically the type is
`juniper::FieldResult<&'a T>` where `'a` is the lifetime of `self`. This works well for
returning data owned by `self` and avoids needless `.clone()` calls you would need if fields
returned owned values.
However if you need to return owned values (such as values queried from a database) you have to
annotate the field in the schema with `#[ownership(owned)]`.
All field arguments will be owned.
## GraphQL features
The goal of this library is to support as much of GraphQL as Juniper does.
Here is the complete list of features:
Supported:
- Object types including converting lists on non-nulls to Rust types
- Custom scalar types including the `ID` type
- Interfaces
- Unions
- Input objects
- Enumeration types
Not supported yet:
- Default values for arguments
- Subscriptions (currently not supported by Juniper so we're unsure when or if this will happen)
### The `ID` type
The `ID` GraphQL type will be generated as a newtype wrapper around a `String` using
[`juniper::graphql_scalar!`](https://docs.rs/juniper/0.11.1/juniper/macro.graphql_scalar.html). The Rust type will be called `Id`.
Example:
```rust
pub struct Id(pub String);
impl Id {
// A generated convenience initializer
pub fn new<T: Into<String>>(id: T) -> Self {
Id(id.into())
}
}
```
### Custom scalar types
Similarly to `ID`, custom scalar types get converted into newtype wrappers around `String`s. For example:
```graphql
scalar Cursor
```
Would result in
```rust
pub struct Cursor(pub String);
```
`Date` and `DateTime` are the two exceptions to this. `Date` gets converted into
[`chrono::naive::NaiveDate`](https://docs.rs/chrono/0.4.6/chrono/naive/struct.NaiveDate.html)
and `DateTime` into
[`chrono::DateTime<chrono::offset::Utc>`](https://docs.rs/chrono/0.4.6/chrono/struct.DateTime.html).
### Interfaces
Juniper has several ways of representing GraphQL interfaces in Rust. They are listed
[here](https://graphql-rust.github.io/types/interfaces.html#enums) along with their advantages
and disadvantages.
For the generated code we use the `enum` pattern because we found it to be the most flexible.
Example:
```rust
#
graphql_schema! {
schema {
query: Query
}
type Query {
"#[ownership(owned)]"
search(query: String!): [SearchResult!]!
}
interface SearchResult {
id: ID!
text: String!
}
type Article implements SearchResult {
id: ID!
text: String!
}
type Tweet implements SearchResult {
id: ID!
text: String!
}
}
pub struct Query;
impl QueryFields for Query {
fn field_search(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, SearchResult, Walked>,
query: String,
) -> FieldResult<Vec<SearchResult>> {
let article: Article = Article { id: Id::new("1"), text: "Business".to_string() };
let tweet: Tweet = Tweet { id: Id::new("2"), text: "1 weird tip".to_string() };
let posts = vec![
SearchResult::from(article),
SearchResult::from(tweet),
];
Ok(posts)
}
}
```
The enum that gets generated has variants for each type that implements the interface and also
implements `From<T>` for each type.
### Union types
Union types are basically just interfaces so they work in very much the same way.
Example:
```rust
#
graphql_schema! {
schema {
query: Query
}
type Query {
"#[ownership(owned)]"
search(query: String!): [SearchResult!]!
}
union SearchResult = Article | Tweet
type Article {
id: ID!
text: String!
}
type Tweet {
id: ID!
text: String!
}
}
pub struct Query;
impl QueryFields for Query {
fn field_search(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, SearchResult, Walked>,
query: String,
) -> FieldResult<Vec<SearchResult>> {
let article: Article = Article { id: Id::new("1"), text: "Business".to_string() };
let tweet: Tweet = Tweet { id: Id::new("2"), text: "1 weird tip".to_string() };
let posts = vec![
SearchResult::from(article),
SearchResult::from(tweet),
];
Ok(posts)
}
}
```
Note that union types current don't work with `QueryTrail`s, meaning that it will not generate
methods for each field in the union. Expect that to be fixed in a future version.
### Input objects
Input objects will be converted into Rust structs with public fields.
Example:
```rust
graphql_schema! {
schema {
query: Query
mutation: Mutation
}
type Mutation {
"#[ownership(owned)]"
createPost(input: CreatePost!): Post
}
input CreatePost {
title: String!
}
type Post {
id: ID!
title: String!
}
type Query { noop: Boolean! }
}
pub struct Mutation;
impl MutationFields for Mutation {
fn field_create_post(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, Post, Walked>,
input: CreatePost,
) -> FieldResult<Option<Post>> {
let title: String = input.title;
unimplemented!()
}
}
```
From that example `CreatePost` will be defined as
```rust
pub struct CreatePost {
pub title: String,
}
```
### Enumeration types
GraphQL enumeration types will be converted into normal Rust enums. The name of each variant
will be camel cased.
Example:
```rust
#
graphql_schema! {
schema {
query: Query
}
enum Status {
PUBLISHED
UNPUBLISHED
}
type Query {
"#[ownership(owned)]"
allPosts(status: STATUS!): [Post!]!
}
type Post {
id: ID!
}
}
pub struct Query;
impl QueryFields for Query {
fn field_all_posts(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, Post, Walked>,
status: Status,
) -> FieldResult<Vec<Post>> {
match status {
Status::Published => unimplemented!("find published posts"),
Status::Unpublished => unimplemented!("find unpublished posts"),
}
}
}
```
## GraphQL to Rust types
This is how the standard GraphQL types will be mapped to Rust:
- `Int` -> `i32`
- `Float` -> `f64`
- `String` -> `String`
- `Boolean` -> `bool`
- `ID` -> `pub struct Id(pub String)`
## Query trails
If you're not careful about preloading associations for deeply nested queries you risk getting
lots of [N+1 query bugs][]. Juniper provides a [look ahead api][] which lets you inspect things
coming up further down a query. However the API is string based, so you risk making typos and
checking for fields that don't exist.
`QueryTrail` is a thin wrapper around Juniper look aheads with generated methods for each field
on all your types. This means the compiler will reject your code if you're checking for invalid
fields.
Fields that return objects types (non scalar values) will also get a `QueryTrail` argument
besides the executor.
[N+1 query bugs]: https://secure.phabricator.com/book/phabcontrib/article/n_plus_one/
[look ahead api]: https://docs.rs/juniper/0.11.1/juniper/struct.LookAheadSelection.html
### Example
```rust
#
graphql_schema! {
schema {
query: Query
}
type Query {
"#[ownership(owned)]"
allPosts: [Post!]!
}
type Post {
id: Int!
author: User!
}
type User {
id: Int!
}
}
pub struct Query;
impl QueryFields for Query {
fn field_all_posts(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, Post, Walked>,
) -> FieldResult<Vec<Post>> {
// Check if the query includes the author
if let Some(_) = trail.author().walk() {
// Somehow preload the users to avoid N+1 query bugs
// Exactly how to do this depends on your setup
}
// Normally this would come from the database
let post = Post {
id: 1,
author: User { id: 1 },
};
Ok(vec![post])
}
}
pub struct Post {
id: i32,
author: User,
}
impl PostFields for Post {
fn field_id(&self, executor: &Executor<'_, Context>) -> FieldResult<&i32> {
Ok(&self.id)
}
fn field_author(
&self,
executor: &Executor<'_, Context>,
trail: &QueryTrail<'_, User, Walked>,
) -> FieldResult<&User> {
Ok(&self.author)
}
}
pub struct User {
id: i32,
}
impl UserFields for User {
fn field_id(
&self,
executor: &Executor<'_, Context>,
) -> FieldResult<&i32> {
Ok(&self.id)
}
}
```
### Types
A query trial has two generic parameters: `QueryTrail<'_, T, K>`. `T` is the type the current
field returns and `K` is either `Walked` or `NotWalked`.
#### `T`
The `T` allows us to implement different methods for different types. For example in the
example above we implement `id` and `author` for `QueryTrail<'_, Post, K>` but only `id` for
`QueryTrail<'_, User, K>`.
#### `K`
The `Walked` and `NotWalked` types are used to check if a given trail has been checked to
actually be part of a query. Calling any method on a `QueryTrail<'_, T, K>` will return
`QueryTrail<'_, T, NotWalked>`, and to check if the trail is actually part of the query you have
to call `.walk()` which returns `Option<QueryTrail<'_, T, Walked>>`. If that is a `Some(_)`
you'll know the trail is part of the query and you can do whatever preloading is necessary.
Example:
```rust
if let Some(walked_trail) = trail.some_field().some_other_field().third_field().walk() {
// preload stuff
}
```
You can always run `cargo doc` and inspect all the methods on `QueryTrail` and in which
contexts you can call them.
---
License: MIT