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GraphQL Best Practices
GraphQL Best Practices

GraphQL Best Practices: Gain hands-on experience with schema design, security, and error handling

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Profile Icon Artur Czemiel
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€29.99
Paperback Oct 2024 422 pages 1st Edition
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Arrow left icon
Profile Icon Artur Czemiel
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€29.99
Paperback Oct 2024 422 pages 1st Edition
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€15.99 €23.99
Paperback
€29.99
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Free Trial
Renews at €18.99p/m
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€15.99 €23.99
Paperback
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GraphQL Best Practices

Unveiling the Holy Grail of Communication – GraphQL

GraphQL seemed to appear both recently and also a long time ago. We live in such times that it’s hard to define. We can definitely consider the year 2015 as the beginning of GraphQL, as that was when Facebook decided it was the right time to make GraphQL open source and available to everyone. Although GraphQL was primarily created to limit data transfer, as a side effect, it also reduced the need for extensive communication within the development team.

I became deeply interested in GraphQL technology around 2018. Since 2016, I had been trying to solve the communication problem between frontend and backend teams by building a TypeScript-based system that generated a REST application skeleton for backend developers and “enforced” them to implement a system with the appropriate types for each endpoint and return exactly what was specified by the system designer (who worked in a visual graph editor). In...

Technical requirements

To follow this chapter and run the mock backend example, you will need the following:

A GitHub repository has been created for this book, and you can find the code for this chapter here: https://github.com/PacktPublishing/GraphQL-Best-Practices/tree/main/chapter-01.

Understanding the advantage of built-in introspection

Why does GraphQL bring about such significant changes? This is primarily because of introspection. In practice, this means that frontend developers, mobile developers, or any API consumers can send a query to the backend asking about the available resolvers, their parameters, and what will be returned from the backend. Thanks to this mechanism, developers can efficiently communicate with the API without diving into the system documentation.

Introspection is a mechanism that allows developers to see the entire structure of a system. Through introspection, we can not only discover what queries we can execute against the backend but also distinguish between queries for data retrieval and mutations for making changes to the system. Additionally, we receive detailed information about the returned types.

Why wasn’t this concept invented earlier, considering it is so simple and obvious? Well, it has been invented before, for...

Working with GraphQL as a source of truth

I often reminisce about the days without GraphQL with an ironic smile on my face. I remember how, as a frontend developer, I had to call backend developers and ask why a certain field suddenly disappeared or what the name of an endpoint was because I couldn’t remember it anymore. Of course, even in REST, there are specification systems that allow for a detailed description of our backend; however, they don’t enforce it on the backend developer – they only enable it.

I was already interested in the concept of a single source of truth even before GraphQL, but as soon as I understood the power of GraphQL, I immediately decided to teach it to everyone in our company and turn it into a competitive advantage.

Understanding the source of truth

Let’s imagine a scenario where we’re starting a project from scratch without any existing systems in place. Typically, the process involves creating wireframes and...

Creating self-documenting schemas

As you can see from our library schema, even though it doesn’t have documentation, just by looking at it, we know exactly what the system based on this schema is used for. This is clear to every member of the team.

Now, let’s go further, looking at self-documenting schemas – these are GraphQL schemas that contain comprehensive and descriptive naming and connections between nodes, allowing developers to easily understand and interact with the available data and operations. Here, we will look at the different elements that make up these schemas.

Custom scalars

Scalars represent simple primitives in GraphQL. There are five built-in scalars in GraphQL: String, Int, Float, ID, and Boolean. Out of these five scalars, only ID needs to be translated, as it is used to indicate a unique key and can be either a string, a number, or a custom object.

With custom scalars, the situation is different as they behave according to how...

Understanding the GraphQL query language

As I mentioned earlier, introspection is vital, and now I present to you the most important part that benefits from introspection: the GraphQL query language. While REST APIs allow for exposing the JSON schema, which provides information about the API structure, I have rarely encountered good use cases for it throughout my professional career. On the other hand, the GraphQL query language is widely used in a proper manner because the language makes it hard to make mistakes.

When I first started using GraphQL, I had this feeling of “Why didn’t people agree on such a standard earlier?” We didn’t need artificial intelligence or quantum computers for it – all we needed was to communicate and reach a consensus – but now GraphQL is commonly used and it is a standard we needed. While it may not be visibly apparent at this moment, I can confidently say that GraphQL is pushing programming technologies forward...

Mocking GraphQL responses

Mocks refers to data that is used when we don’t have the system implementation yet. Their purpose is to closely resemble the data that will be returned from a functioning backend.

But how do mocks work? It’s quite simple. Each type, except for custom scalars, ultimately resolves to basic scalars such as String, ID, Float, Int, and Boolean. By knowing the final type and the resolver path, sometimes, even with detailed documentation, we can return very accurate mock values.

Let’s take a look at our simplified Book type:

type Book {
  id: ID!
  title: String!
  author: String!
}
type Query{
  books: [Book!]!
}

If the fields are built-in scalars, we are able to provide mocks just after looking at the type. In the following JSON code, we provide a response for Query.books:

[
  {
    "id": "123abc",
    "title&quot...

Summary

In this chapter, we have reviewed the basics of GraphQL and highlighted its greatest strengths. We have learned how to query the GraphQL backend for its structure and how it is defined in the SDL. These are all solid foundations of GraphQL that will allow us to smoothly progress through this book. If you don’t understand something in the upcoming chapters, you can always come back here.

Before we dive into the heavyweight schema definition in GraphQL, I’d like us to take a look at how GraphQL relates to large language models and how these two technologies can work together seamlessly. In the next chapter, you will learn how to make GraphQL schemas AI-friendly.

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Key benefits

  • Gain detailed guidance for crafting effective GraphQL schemas
  • Explore insights into securing and optimizing GraphQL applications
  • Learn through step-by-step examples, using TypeScript for practical learning
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

In the ever-evolving landscape of web development, GraphQL has emerged as a powerful query language that addresses the limitations of traditional REST APIs. This guide delves deep into GraphQL, starting with its foundational principles and swiftly advancing to complex topics that will equip you with the skills you need to understand this technology. As you progress, you’ll cover advanced concepts such as schema design, security enhancements, and error handling. You'll also explore essential topics such as federation and the transition from REST to GraphQL, gaining a comprehensive understanding of these critical areas. The book helps you learn through practical examples in TypeScript, guiding you through building scalable and secure GraphQL backends. Additionally, you’ll get up to speed with the intricacies of frontend integration. By the end of this book, you’ll have the skills you need to implement real-world GraphQL solutions, creating efficient and robust applications that meet modern web development demands.

Who is this book for?

This book is for developers interested in advancing their knowledge of GraphQL, from beginners curious about the basics to experienced developers looking to refine their schema design and security strategies. It's particularly ideal for backend developers, full-stack professionals, and frontend developers who wish to understand GraphQL from the ground up and apply advanced techniques in real-world scenarios. Additionally, this book is a must-read for anyone looking to make their applications more efficient and robust using GraphQL.

What you will learn

  • Understand the core principles of GraphQL
  • Integrate GraphQL with frontend technologies such as Node.js and Next.js
  • Optimize GraphQL queries for better performance
  • Deploy and maintain GraphQL applications with confidence
  • Explore schema design, security, and error handling
  • Scale GraphQL with modular schemas
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Table of Contents

22 Chapters
Part 1 - Why GraphQL? Chevron down icon Chevron up icon
Chapter 1: Unveiling the Holy Grail of Communication – GraphQL Chevron down icon Chevron up icon
Chapter 2: Applying an AI-Friendly Approach to GraphQL Chevron down icon Chevron up icon
Part 2 - Schema-First Design Patterns Chevron down icon Chevron up icon
Chapter 3: Crafting Effective GraphQL Schemas Chevron down icon Chevron up icon
Chapter 4: Building Pipes Chevron down icon Chevron up icon
Part 3 - Exploring Possible Ways to Use GraphQL Chevron down icon Chevron up icon
Chapter 5: Transitioning from REST to GraphQL Chevron down icon Chevron up icon
Chapter 6: Defining GraphQL Transformers Chevron down icon Chevron up icon
Chapter 7: Understanding GraphQL Federation Chevron down icon Chevron up icon
Part 4 - Advanced GraphQL Chevron down icon Chevron up icon
Chapter 8: Executing Schema-First Systems Chevron down icon Chevron up icon
Chapter 9: Working on the Frontend with GraphQL Chevron down icon Chevron up icon
Chapter 10: Keeping Data Secure Chevron down icon Chevron up icon
Chapter 11: Describing Errors in GraphQL Chevron down icon Chevron up icon
Chapter 12: Documenting your Schema Chevron down icon Chevron up icon
Chapter 13: Tackling Schemas with Visualization Chevron down icon Chevron up icon
Part 5 - From an Idea to a Working Project Chevron down icon Chevron up icon
Chapter 14: From an Idea to a Working Project – Backend Development with GraphQL and TypeScript Chevron down icon Chevron up icon
Chapter 15: From an Idea to a Working Project – Frontend Integration with GraphQL and TypeScript Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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