How to wrap a REST API with GraphQL - A 3-step tutorial

In this article, you learned how to turn a REST API into a GraphQL API in three simple steps

This article was written by Nikolas Burk and was originally posted on the Prisma blog. You can find the original article here.
REST APIs have been the standard for building web APIs for the past decade. In 2015, Facebook introduced a new and open-source query language for APIs that comes with notable advantages compared to REST: GraphQL!

Since then, many developers want to start using GraphQL but are stuck with their legacy REST APIs. In this article, we’re going to introduce a lightweight process for turning REST into GraphQL APIs. No special tooling required!
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REST is schemaless

One of the biggest drawbacks of REST APIs is that they don’t have a schema describing what the data structures that are returned by the API endpoints look like.

Assume you’re hitting this REST endpoint with a GET request: /users

Now, you’re flying completely blind. If the person who designed the API is sane, it is probably safe to assume that it will return an array of some kind of user objects — but what data each of the user objects actually carries can in no way be derived just from looking at this endpoint.
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A sample REST API

In this article, we’ll take the example of a simple blogging application. Assume there are two models, users and posts. There is a one-to-many relationship between them in that one user can be associated with multiple posts.
For that example, we’d have the following endpoints:
1. /users 2. /users/<id> 3. /users/<id>/posts 4. /posts 5. /blog/posts/<id> 6. /blog/posts/<id>/user

With this design, we’re able to query:
  1. a list of users
  2. a specific user given their id
  3. all posts of a specific user given their id
  4. a list of posts
  5. a specific post given its id
  6. the author of a post given its id
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Wrapping a REST API with GraphQL in 3 simple steps

In this section, we’ll outline how you can wrap REST APIs with GraphQL in 3 simple steps.

Overview: How do GraphQL servers work
GraphQL is no rocket science! In fact, it follows a few very simple rules which make it so flexible and universally adaptable.

In general, building a GraphQL API always requires two essential steps: At first you need to define a GraphQL schema, then you have to implement resolver functions for that schema.

GraphQL resolver functions can return data from anywhere: SQL or NoSQL databases, REST APIs, 3rd-party APIs, legacy systems or even other GraphQL APIs.

A huge part of GraphQL’s flexibility comes from the fact that GraphQL itself is not
bound to a particular data source. Resolver functions can return data from virtually anywhere: SQL or NoSQL databases, REST APIs, 3rd-party APIs, legacy systems or even other GraphQL APIs.

This is what makes it a suitable tool for wrapping REST APIs. In essence, there are three steps you need to perform when wrapping a REST API with GraphQL:
  1. Analyze the data model of the REST API
  2. Derive the GraphQL schema for the API based on the data model
  3. Implement resolver functions for the schema

Let’s go through each of these steps, using the REST API from before as an example.
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Step 1: Analyze the data model of the REST API

The first thing you need to understand is the shape of the data that’s returned by the different REST endpoints.

In our example scenario, we can state the following:
The User model has id and name fields (of type string) as well as a posts field which represents a to-many-relationship to the Post model.

The Post model has id, title, content (of type string) and published (of type boolean) fields as well as an author field which represents a to-one-relationship to the User model.

Once we’re aware of the shape of the data returned by the API, we can translate our findings into the GraphQL Schema Definition Language (SDL):
type User { id: ID! name: String! posts: [Post!]! } type Post { id: ID! title: String! content: String! published: Boolean! author: User! }

The SDL syntax is concise and straightforward. It allows to define types with fields. Each field on a type also has a type. This can be a scalar type like Int and String or an object type like Post and User. The exclamation point following the type of a field means that this field can never be null.

The types that we defined in that schema will be the foundation for the GraphQL API that we’re going to develop in the next step.
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Step 2: Define GraphQL schema

Each GraphQL schema has three special root types: Query, Mutation and Subscription. These define the entry-points for the API and roughly compare to REST endpoints (in the sense that each REST endpoint can be said to represent one query against its REST API whereas with GraphQL, every field on the Query type represents one query).

There are two ways to approach this step:
  1. Translate each REST endpoint into a corresponding query
  2. Tailor an API that’s more suitable for the clients
In this article, we’ll go with the first approach since it illustrates well the mechanisms you need to apply. Deducing from it how the second approach works should be an instructive exercise for the attentive reader.

Let’s start with the /users endpoint. To add the capability to query a list of users to our GraphQL API, we first need to add the Query root type to the schema definition and then add a field that returns the list of users:
type Query { users: [User!]! } type User { id: ID! name: String! posts: [Post!]! } type Post { id: ID! title: String! content: String! published: Boolean! author: User! }

To invoke the users query that we now added to the schema, you can put the following query into the body of an HTTP POST request that’s sent to the endpoint of the GraphQL API:
query { users { id name } }

Don’t worry, we’ll show you in a bit how you can actually send that query.
The neat thing here is that the fields you’re nesting under the users query determine what fields will be included in the JSON payload of the server’s response. This means you could remove the name field if you don’t need the user’s names on the client-side.

Even cooler: If you like, you can also query the related Post items of each user with as many fields as you like, for example:
query { users { id name posts { id title } } }

Let’s now add the second endpoint to our API:/users/<id>. The parameter that’s part of the URL of the REST endpoint now simply becomes an argument for the field we’re introducing on the Query type (for brevity, we’re now omitting the User and Posttypes from the schema, but they’re still part of the schema):
type Query { users: [User!]! user(id: ID!): User }

Here’s what a potential query looks like (again, we can add as many or as few fields of the User type as we like and thus dictate what data the server is going to return):
query { user(id: "user-1") { name posts { title content } } }

As for the /users/<id>/posts endpoint, we actually don’t even need it because the ability to query posts of a specific user is already taken care of by the user(id: ID!): User field we just added. Groovy!

Let’s now complete the API by adding the ability to query Post items. We’ll add the queries for all three REST endpoints at once:
type Query { users: [User!]! user(id: ID!): User posts: [Post!]! post(id: ID!): Post }

This is it — we have now created the schema definition for a GraphQL API that is
equivalent to the previous REST API. Next, we need to implement the resolver functions for the schema!
With REST, that’s done by using the PUT, POST and DELETE HTTP methods against the same endpoints.

When using GraphQL, this is done via the Mutation root type. Just as an example, this is how we could add the ability to create, update and delete new User items to the API:
type Mutation { createUser(name: String!): User! updateUser(id: ID!, name: String!): User deleteUser(id: ID!): User } type Query { users: [User!]! user(id: ID!): User posts: [Post!]! post(id: ID!): Post }
Note that the createUser, updateUser and deleteUser mutations would correspond to POST, PUT and DELETE HTTP requests made against the /users/<id>endpoint.

Implementing the resolvers for mutations is equivalent to implementing resolvers for queries, so there’s no need to learn anything new for mutations as they follow the exact same mechanics as queries — the only difference is that mutation resolvers will have side-effects.
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Step 3: Implementing resolvers for the schema

GraphQL has a strict separation between structure and behaviour.

The structure of an API is defined by the GraphQL schema definition. This schema definition is an abstract description of the capabilities of the API and allows clients to know exactly what operations they can send to it.

The behaviour of a GraphQL API is the implementation of the schema definition in the form of resolver functions. Each field in the GraphQL schema is backed by exactly one resolver that knows how to fetch the data for that specific field.

The implementation of the resolvers is fairly straightforward. All we do is making calls to the corresponding REST endpoints and immediately return the responses we receive:
const baseURL = `https://rest-demo-hyxkwbnhaz.now.sh` const resolvers = { Query: { users: () => { return fetch(`${baseURL}/users`).then(res => res.json()) }, user: (parent, args) => { const { id } = args return fetch(`${baseURL}/users/${id}`).then(res => res.json()) }, posts: () => { return fetch(`${baseURL}/posts`).then(res => res.json()) }, post: (parent, args) => { const { id } = args return fetch(`${baseURL}/blog/posts/${id}`).then(res => res.json()) }, }, }

For the user and post resolvers, we’re also extracting the id argument that’s provided in the query and include it in the URL.

All you need now to get this up-and-running is to instantiate a GraphQLServer from the graphql-yoga NPM package, pass the resolvers and the schema definition to it and invoke the start method on the server instance:
const { GraphQLServer } = require('graphql-yoga') const fetch = require('node-fetch') const baseURL = `https://rest-demo-hyxkwbnhaz.now.sh` const resolvers = { // ... the resolver implementation from above ... } const server = new GraphQLServer({ typeDefs: './src/schema.graphql', resolvers, }) server.start(() => console.log(`Server is running on http://localhost:4000`))

If you want to follow along, you can copy the code from the above index.js and schema.graphql snippets into corresponding files inside a src directory in a Node project, add graphql-yoga as a dependency and then run node src/index.js.

If you do so and then open your browser at http://localhost:4000, you’ll see the following GraphQL Playground:


A GraphQL Playground is a GraphQL IDE that let’s you explore the capabilities of a GraphQL API in an interactive manner. Similar to Postman, but with many additional GraphQL-specific features. In there, you can now send the queries we saw above.

The query will be resolved by the GraphQL engine of the GraphQLServer. All it needs to do is invoking the resolvers for the fields in the query and thus calling out to the appropriate REST endpoints. This is the user(id: ID) query for example:


Awesome! You can now add fields of the User type to the query as you like.

However, when also asking for the related Post items of a user, you’ll be disappointed that you’re getting an error:
So, something doesn’t quite work yet! Let’s take a look at the resolver implementation for the user(id: ID) field again:
user: (parent, args) => { const { id } = args return fetch(`${baseURL}/users/${id}`).then(res => res.json()) },

The resolver only returns the data it receives from the /users/<id> endpoint and because we’re using the flat version of the REST API, there are no associated Postelements! So, one way out of that problem would be to use the nested version — but that’s not what we want here!

A better solution is to implement a dedicated resolver for the User type (and in fact, for the Post type as well since we’ll have the same problem the other way around):
const resolvers = { Query: { // ... the resolver implementation from above ... }, Post: { author: parent => { const { id } = parent return fetch(`${baseURL}/blog/posts/${id}/user`).then(res => res.json()) }, }, User: { posts: parent => { const { id } = parent return fetch(`${baseURL}/users/${id}/posts`).then(res => res.json()) }, }, }

The implementation of the resolver is bug free and you can nest your queries as you wish. Pleasing!
Great, this is it! You successfully learned how to wrap a REST API with GraphQL.

If you want to play around with this example, you can check out this repository which contains the full version of the GraphQL API we just implemented.
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Conclusion

In this article, you learned how to turn a REST API into a GraphQL API in three simple steps:
  1. Analyze the data model of the REST API
  2. Define your GraphQL schema
  3. Implement the resolvers for the schema
Wrapping REST APIs with GraphQL is probably one of the most exciting applications of GraphQL — and still in its infancy. The process explained in this article was entirely manual, the real interesting part is the idea of automating the different steps. Stay tuned for more content on that topic!
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This article was written by Nikolas Burk and was originally posted on the Prisma blog. You can find the original article here.


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