Gain insights into GraphQL's architecture and methodology. Learn about setting up servers, performing complex queries, and updating data with mutations using Apollo Server and Node.js. Discover practical deployment.

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GraphQL is a query language for web APIs and a runtime for fulfilling queries with existing data. GraphQL gives clients the power to ask for precisely what they need, making it easy to evolve APIs with powerful developer tools.

This course is an introduction to GraphQL using the Node.js JavaScript runtime environment and Apollo Server. You’ll start with an introduction to GraphQL’s architecture and functions before exploring the structure of GraphQL data and learning to perform meaningful, complex queries. You’ll then learn how to update server data using mutations. Next, you’ll explore the GraphQL type system and schemas to set up a GraphQL server using Apollo Server. Once the server is set up, you’ll implement a full GraphQL application using Apollo and Node.js.

By the end of this course, you’ll have a rich understanding of GraphQL’s architecture and methodology and be prepared to deploy GraphQL applications to the web using Apollo and Node.js.

Getting Started with GraphQL using Node.js

The GraphQL specification doesn’t provide ready-made solutions for a handful of essential APIs, such as dealing with the network, authorization, and pagination. That doesn’t mean that there aren’t answers for these problems when using GraphQL API. 

In this final GraphQL lesson, we’ll look at some of the standard best practices for GraphQL.


# HTTP
GraphQL typically serves over HTTP via the endpoint `/graphql`, which expresses the complete set of capabilities of the service. In contrast, REST APIs expose a suite of URLs, such as `/pizza/1` and `/pizza/`, each revealing a single resource. While the client could use GraphQL alongside a suite of resource URLs, this is considered bad practice since it’s harder to use with a GraphQL IDE like Apollo Studio or GraphiQL.


# Versioning
GraphQL documentaton recommends not implementing versioning at all, and instead suggests evolving the GraphQL schema continuously.

Why do APIs need a version? First, the API version occurs because there’s limited control over the data returned from an API endpoint. In addition, any update can be considered a breaking change, and breaking changes require a new version—the tradeoff between multiple incremental versions versus the maintainability of the API.

In contrast, GraphQL only returns the explicitly requested data, so API can add new capabilities via new object types and new fields on those types without creating a breaking change. As a result, GraphQL is now widely used to avoid breaking changes and as a versionless API.


# Nullability
Type systems that recognize `null` provide both the standard type and the nullable version of that type. In a GraphQL type system, each field is nullable by default. This is because many things can go awry in a networked service backed by databases and other services. For example, a database could go down, or an asynchronous action could fail and cause an exception.

By providing a nullable fallback for every field, any error may result in that field returning `null` rather than  a statement that the request failed to be processed. So instead, GraphQL provides non-null types that guarantee that the area will never return `null` if requested. If an error occurs, the previous parent field will be `null` instead.

When designing a GraphQL schema, it’s essential to consider all the issues, including whether `null` is a suitable value for filling in incomplete data. Most of the time it is, but that’s not always the case. If that’s the case, we have the option to use non-null types.



# Server-side batching and caching
By design, GraphQL allows us to write clean code on the server. This is because every field of every type has a single purpose function for resolving that value. However, a GraphQL service could be very chatty, meaning it could repeatedly load data from our databases without additional consideration. A batching technique usually solves this. Several requests for data from a backend are collected and then dispatched in a single process to an underlying database or microservice by using a third-party library, such as Facebook’s DataLoader.



Understand established best practices to successfully adopt GraphQL.


GraphQL Best Practices

Understand established best practices to successfully adopt GraphQL.

Introduction

Getting to Know GraphQL

Queries

Mutations

Schemas and Types

Schema Validation

Schema Execution

Schema Introspection

GraphQL Best Practices

GraphQL Exam

GraphQL Best Practices