juniper/docs/book/content/quickstart.md

Quickstart

This page will give you a short introduction to the concepts in Juniper.

Juniper follows a code-first approach to defining GraphQL schemas. If you would like to use a schema-first approach instead, consider juniper-from-schema for generating code from a schema file.

Installation

[dependencies]
juniper = "0.15"

Schema example

Exposing simple enums and structs as GraphQL is just a matter of adding a custom derive attribute to them. Juniper includes support for basic Rust types that naturally map to GraphQL features, such as Option<T>, Vec<T>, Box<T>, String, f64, and i32, references, and slices.

For more advanced mappings, Juniper provides multiple macros to map your Rust types to a GraphQL schema. The most important one is the graphql_object procedural macro that is used for declaring an object with resolvers, which you will use for the Query and Mutation roots.

# #![allow(unused_variables)]
# extern crate juniper;
# use std::fmt::Display;
use juniper::{
    graphql_object, EmptySubscription, FieldResult, GraphQLEnum, 
    GraphQLInputObject, GraphQLObject, ScalarValue,
};
#
# struct DatabasePool;
# impl DatabasePool {
#     fn get_connection(&self) -> FieldResult<DatabasePool> { Ok(DatabasePool) }
#     fn find_human(&self, _id: &str) -> FieldResult<Human> { Err("")? }
#     fn insert_human(&self, _human: &NewHuman) -> FieldResult<Human> { Err("")? }
# }

#[derive(GraphQLEnum)]
enum Episode {
    NewHope,
    Empire,
    Jedi,
}

#[derive(GraphQLObject)]
#[graphql(description = "A humanoid creature in the Star Wars universe")]
struct Human {
    id: String,
    name: String,
    appears_in: Vec<Episode>,
    home_planet: String,
}

// There is also a custom derive for mapping GraphQL input objects.

#[derive(GraphQLInputObject)]
#[graphql(description = "A humanoid creature in the Star Wars universe")]
struct NewHuman {
    name: String,
    appears_in: Vec<Episode>,
    home_planet: String,
}

// Now, we create our root Query and Mutation types with resolvers by using the
// object macro.
// Objects can have contexts that allow accessing shared state like a database
// pool.

struct Context {
    // Use your real database pool here.
    pool: DatabasePool,
}

// To make our context usable by Juniper, we have to implement a marker trait.
impl juniper::Context for Context {}

struct Query;

#[graphql_object(
    // Here we specify the context type for the object.
    // We need to do this in every type that
    // needs access to the context.
    context = Context,
)]
impl Query {
    fn apiVersion() -> &'static str {
        "1.0"
    }

    // Arguments to resolvers can either be simple types or input objects.
    // To gain access to the context, we specify a argument
    // that is a reference to the Context type.
    // Juniper automatically injects the correct context here.
    fn human(context: &Context, id: String) -> FieldResult<Human> {
        // Get a db connection.
        let connection = context.pool.get_connection()?;
        // Execute a db query.
        // Note the use of `?` to propagate errors.
        let human = connection.find_human(&id)?;
        // Return the result.
        Ok(human)
    }
}

// Now, we do the same for our Mutation type.

struct Mutation;

#[graphql_object(
    context = Context,
    // If we need to use `ScalarValue` parametrization explicitly somewhere
    // in the object definition (like here in `FieldResult`), we could
    // declare an explicit type parameter for that, and specify it.
    scalar = S: ScalarValue + Display,
)]
impl Mutation {
    fn createHuman<S: ScalarValue + Display>(context: &Context, new_human: NewHuman) -> FieldResult<Human, S> {
        let db = context.pool.get_connection().map_err(|e| e.map_scalar_value())?;
        let human: Human = db.insert_human(&new_human).map_err(|e| e.map_scalar_value())?;
        Ok(human)
    }
}

// A root schema consists of a query, a mutation, and a subscription.
// Request queries can be executed against a RootNode.
type Schema = juniper::RootNode<'static, Query, Mutation, EmptySubscription<Context>>;
#
# fn main() {
#   let _ = Schema::new(Query, Mutation{}, EmptySubscription::new());
# }

We now have a very simple but functional schema for a GraphQL server!

To actually serve the schema, see the guides for our various server integrations.

Juniper is a library that can be used in many contexts--it does not require a server and it does not have a dependency on a particular transport or serialization format. You can invoke the executor directly to get a result for a query:

Executor

You can invoke juniper::execute directly to run a GraphQL query:

# // Only needed due to 2018 edition because the macro is not accessible.
# #[macro_use] extern crate juniper;
use juniper::{
    graphql_object, EmptyMutation, EmptySubscription, FieldResult, 
    GraphQLEnum, Variables, graphql_value,
};

#[derive(GraphQLEnum, Clone, Copy)]
enum Episode {
    NewHope,
    Empire,
    Jedi,
}

// Arbitrary context data.
struct Ctx(Episode);

impl juniper::Context for Ctx {}

struct Query;

#[graphql_object(context = Ctx)]
impl Query {
    fn favoriteEpisode(context: &Ctx) -> FieldResult<Episode> {
        Ok(context.0)
    }
}

// A root schema consists of a query, a mutation, and a subscription.
// Request queries can be executed against a RootNode.
type Schema = juniper::RootNode<'static, Query, EmptyMutation<Ctx>, EmptySubscription<Ctx>>;

fn main() {
    // Create a context object.
    let ctx = Ctx(Episode::NewHope);

    // Run the executor.
    let (res, _errors) = juniper::execute_sync(
        "query { favoriteEpisode }",
        None,
        &Schema::new(Query, EmptyMutation::new(), EmptySubscription::new()),
        &Variables::new(),
        &ctx,
    ).unwrap();

    // Ensure the value matches.
    assert_eq!(
        res,
        graphql_value!({
            "favoriteEpisode": "NEW_HOPE",
        })
    );
}