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Hands-On Full-Stack Web Development with GraphQL and React

Hands-On Full-Stack Web Development with GraphQL and React

By : Grebe
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Hands-On Full-Stack Web Development with GraphQL and React

Hands-On Full-Stack Web Development with GraphQL and React

3 (2)
By: Grebe

Overview of this book

React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements.
Table of Contents (15 chapters)
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Caching with Apollo Server and the Client

Hopefully, when deploying your first application, you'll soon get a growing user base. You're required to improve the performance and efficiency of your application. One way this can be done is through standard improvements, such as code refactoring. Another crucial thing to do is caching. Not just files such as our CSS and JavaScript files should be cached, but also the requests that we send.

Apollo provides Automatic Persisted Queries (APQ), which is a technique that significantly reduces bandwidth usage and carries out caching through unique IDs per request. The workflow of this technique is as follows:

  1. The client sends a hash instead of the full query string.
  2. Apollo Server tries to find this hash inside its cache.
  3. If the server finds the corresponding query string to the hash, it'll execute it and respond with its result...

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