Since its public release in 2015, GraphQL has been on the rise both in popularity and widespread use. The addition of the data graph changed the development process forever, bringing together data and services in a comprehensive and secure way. An ever-growing number of companies have recognized its vast capabilities, with such entities as Shopify, Microsoft or Yelp adding GraphQL to their development stacks.

GraphQL is alive and well, but how did it grow from a hermetic language used by very few to a widely recognized, almost indispensable tool? It wouldn't be here without quite a few success stories surrounding it.

A perfect example would be a recent migration of Airbnb's API. It has been discussed at length by [Brie Bunge, one of their software engineers, at GraphQL summit](https://www.youtube.com/watch?v=pywcFELoU8E\&feature=youtu.be), where she described the process in some detail. I wanted to take a look at some of the distinct advantages of using GraphQL in these operations in the hope that you, dear reader, might find a solution to one of your problems.

![Migrating from REST to GraphQL](https://graphqleditorcms.fra1.cdn.digitaloceanspaces.com/graphqleditorcms/blogpost/graphql-restapi.webp)

##### Source: [undraw.co](https://undraw.co/)

## Better data access

The adoption of GraphQL for their API resulted in quicker access to data and a much more enjoyable interface. Thanks to the step-by-step approach to migration, with hardly any downtime during the whole process. Instead of trying to convert preexisting code at once or even rebuilding from the ground up, Airbnb opted for gradual changes. Consequently, this allowed for a smooth transition without the need to put any services on pause.

## Over-fetching problem

Another improvement gained through switching over to [GraphQL](https://graphqleditor.com/) was the significant reduction in over-fetching. The data has been shaped in a way that doesn’t allow for requesting any more than is needed in a particular instance. This severely reduces unnecessary costs that may have been incurred beforehand, something that must be considered when designing data architecture.

After the whole conversion process was complete, the result was a dependable, streamlined and far-reaching tool. It is able to quickly and reliably access requested data by combining the strengths of its components while getting rid of needlessly complicated code. Furthermore, should the need arise, Airbnb’s implementation of GraphQL is ready to be scaled within reason. According to [Adam Neary](https://medium.com/@AdamRNeary), another software engineer at the aforementioned company, other benefits [include](https://medium.com/airbnb-engineering/reconciling-graphql-and-thrift-at-airbnb-a97e8d290712):

* a strongly typed API schema,
* flexibility in field selection,
* cross-platform client-side development

... and many more.

Despite the indisputable gains from using [GraphQL](https://graphqleditor.com/), this project is far from complete. There are numerous improvements that can be developed sooner or later.

By reshaping the schema into a more data-centric one, they hope to cut down on duplicate requests, further increasing the efficiency and speeding up the caching, which has been a major bottleneck up till then.

This is but one of many examples of GraphQL being a prime choice for data handling at a major company. Nearly a thousand businesses from various branches using this language for all their dealings with queries, showing just how flexible and efficient it is.

The advantages of migrating to GraphQL

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Unlocking the Power of React 19

Welcome to a short post about a recent quality of life update to GraphQL Zeus. If you're not familiar with GraphQL Zeus go ahead and read my [earlier post which breaks down its basics](/what-is-graphql-zeus). If you are lets go ahead and talk about the update!

### Graphql Fragments

GraphQL has long supported reusable fields natively with the use of fragments. If you're not familiar with them basically if you had the same fields in multiple queries you could define a fragment - a set of fields, and then reuse it instead of repeating all the fields every time. Lets say you had a user with some fields like name, email, address. Then you could use a fragment like this:

```ts
query getUser {
  user(id: 4) {
    ...userFields
  }
}

fragment userFields on User {
  name,
  email,
  address,
  avatar
}
```

For reusability you could put all your fragments in a fragments.js file and then use them across a project. Zeus already had a solution like Selectors (which work a bit similarly to that) but with the latest update it can now go a step further! :)

### Zeus fields - GraphQL spread operator

For our example lets say we need to get the posts data for our blog page where we display them in a grid, usually the query that would look something like this:

```ts
const posts = await Chain('http://example.com/api/graphql')('query')({
  posts: [
    {
      title: true,
      coverImage: true,
      publishedAt: true,
      slug: true,
      content: { markdown: true },
    },
  ],
});
```

With Zeus 6.0.0 you can simply use a spread operator `...fields` with the TypeScript type from the schema (eg. `Post`) to simply get all the fields available for that type:

```ts
const posts = await Chain('http://example.com/api/graphql')('query')({
  posts: [
    {
      ...fields('Post'),
    },
  ],
});
```

### Never go full REST

With this, we now have a convenient quality-of-life improvement for cases where you just want to quickly retrieve all the fields for a type. That said it's important to remember what GraphQL is all about - getting exactly what you requested without overfetching. So don't just use `...fields` everywhere or you'll defeat the entire purpose of using GraphQL in the first place and turn it into REST, always pulling way more data than necessary.


Zeus update - GraphQL spread operator

GraphQL Zeus is codegen which, with the use of just one command, generates Typescript types for your GraphQL schema. From there even a junior frontend dev can easily handle writing type-safe requests to the backend, and do so without asking backend devs or even looking at the schema. To showcase how easy it is lets go over the installation and some basic use cases.

### Installation and example query

1. Obviously first we need to install it in our project using `npm i graphql-zeus`.
2. Once it finishes installing we need to point it to our schema url using the command `zeus http://example.com/your-schema-url/`. Zeus will then generate types for everything in that schema and put that in a file in its folder so that you can easily import it across your project.

### Queries

Now we can begin writing type safe requests. Lets say our example will be a simple query which fetches reviews which we then put into a table, list, carousel or whatever else on our website:

```ts
const reviews = await Chain('http://example.com/your-schema-url/')('query')({
  listReviews: [
    {
      author_name: true,
      rating: true,
      content: true,
    },
  ],
});
```

That will give us all the reviews as an array, we can then easily map over it to create some simple component like this:

```ts
{
  reviews.map((review, idx) => {
    return (
      <div key={idx} className="flex flex-col">
        <h3>{review.author_name}</h3>
        <div>{'★'.repeat(review.rating)}</div>
        <p>{review.content}</p>
      </div>
    );
  });
}
```

Queries follow a simple structure: we use square brackets for their contents and then:

- in the first curly brackets we put the query payload ie. what we're sending to the backend (for example the id of the item we want to get, the locale or the access token for a login query)
- in the second curly brackets we specify which fields we want to receive

Following our example lets say we're interested in getting our reviews in only one language - then we would have to specify that in the query payload(autocomplete is your friend here and will tell you exactly what you can input there):

```ts
const reviews = await Chain('http://example.com/your-schema-url/')('query')({
  listReview: [
    { locale: 'pl' },
    {
      author_name: true,
      rating: true,
      content: true,
    },
  ],
});
```

### Mutations

With mutations instead of retrieving data, we're sending it to the backend to make changes. The structure is the same as with queries, two sets of curly brackets:

- in the first brackets one we include the inputs ie. what we want to change (like add a new review or modify an existing one by id)
- in the second brackets we specify what we want to get back after the mutation runs, which is usually a confirmation that the mutation was successful

Sticking with our previous example we can create a mutation to submit reviews:

```ts
const newReview = await Chain('http://example.com/your-schema-url/')(
  'mutation',
)({
  createReview: [
    { input: { author_name: 'John', rating: 5, content: 'Great product!' } },
    {
      id: true,
    },
  ],
});
```

This will only create a 5 star review by John with that content. Most likely you'd want to link that to some small form component which lets users write reviews and sends that mutation with the data on submit or something similar.

### Use with CMS (Hygraph)

If we're reusing queries or mutations across our project it makes little sense to keep writing them out like that. It makes more sense to put them in a specific file and then import them as needed. For this example lets say we're pulling data from a CMS like Hygraph, we can create a file called `requests.ts`. Then at the top of it we can create a custom Chain which will handle the url and authorization (we'll be using it for all our queries and mutations since Hygraph wont let us through otherwise):

```ts
export const chain = Chain(process.env.CMS_URL!, {
  headers: {
    Authorization: `Bearer ${process.env.CMS_TOKEN}`,
  },
});
```

Now we can create a query to get all our blogposts from the CMS and even limit those to only the ones in English and only those in the Published stage o that we avoid getting drafts and such:

```ts
export const getPosts = async () => {
  return await chain('query')({
    posts: [
      {
        stage: Stage.PUBLISHED,
        locales: [Locale.en],
      },
      {
        title: true,
        author: true,
        coverImage: true,
        publishedAt: true,
        slug: true,
        content: { markdown: true },
      },
    ],
  });
};
```

From here using it in our component is a simple as doing a const and then putting the data in a map, list, carousel or whatever we want.

```ts
const blogposts = await getPosts();
{
  blogposts.map((blogpost, idx) => {
    return <BlogCard key={idx} />;
  });
}
```

GraphQL's core concept is getting only what you request without overfetching so if we want to get just one blogpost we'll need a specific query for that. Lets say we want to make dynamic pages for our blogposts using slugs, for that we'll need to pass that to the CMS in the payload and then we'll receive only the post we asked for. We also need to throw an error in case an incorrect slug was provided or something else went wrong, so lets use a simple try catch:

```ts
const getPostBySlug = async ({ slug }: { slug: string }) => {
  try {
    const result = await Chain('query')({
      post: [
        {
          stage: Stage.PUBLISHED,
          locales: [Locale.en],
          where: { slug: slug },
        },
        {
          title: true,
          author: true,
          coverImage: true,
          publishedAt: true,
          slug: true,
          content: { markdown: true },
        },
      ],
    });
    return result;
  } catch (error) {
    console.error('Could not get post, error:', error);
    throw error;
  }
};
```

### Zeus Selectors

Writing out all the fields we want returned every single time would be cumbersome, and that's where Selectors come in. Since Zeus generates types for the entire schema it makes writing Selectors much easier with the use of autocomplete and type-safety. As we were querying for blogposts it makes the most sense to go with a Post Selector as an example:

```ts
export const postSelector = Selector('Post')({
  title: true,
  author: true,
  coverImage: true,
  publishedAt: true,
  slug: true,
  content: { markdown: true },
});
```

Thanks to that instead of writing out all the fields we can just use a selector like this:

```ts
export const getPosts = async () => {
  return await chain('query')({
    posts: [
      {
        stage: Stage.PUBLISHED,
        locales: [Locale.en],
      },
      postSelector,
    ],
  });
};
```

And that's all for the basic use cases, hopefully this guide was simple enough to follow and now you're ready to use Zeus for your projects and find out yourself how handy it is for working with the backend. I can say it definitely worked wonders for me as a very junior frontend dev. If you have any questions or want to know more, feel free to reach out and stay tuned for the next post, where I’ll dive into a recent update to Zeus and how it can make things even easier!


The advantages of migrating to GraphQL

Source: undraw.co

Better data access

Over-fetching problem

Check out our other blogposts

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