The basic premise of data transfer and involves requesting and receiving lists. This is simplistic, but it gets to the root of why we’ve developed the technologies and best practices to pass data using web services. RESTful APIs have grown to serve the needs of numerous individuals, startups, and enterprise companies across the world. They are useful, productive, and the concepts surrounding them are relatively standardized. If you don’t know how to create one, you can quickly find information building a great API that can grow to fit your needs. That’s when things get complicated…

If you start digging into REST, you’ll realize there’s quite a bit more to throwing lists. There are common threads that many people encounter when developing an API, and you begin to encounter many of the same questions so many others have before, such as: How strictly should you adhere to the principles of REST? How should you handle versioning? Should you bother? How do you want to structure your objects? Are users able to easily figure out what API endpoints are available and how they should be used?

There are many ways approach these. It boils down to communicating the structures that a given endpoint will return or accept. The cascade of questions that results from the choices made here will ripple through from the back-end to the client. The secondary issue is that these questions and choices are not at all uncommon. There are answers to these that follow Best Practices. But there is still plenty of ambiguity involved when attempting to build a flexible API that works well. These are the Commonly Tolerated Situations.

If you hadn’t already guessed, there is a solution that frees us from the dogma of REST and allows us to solve all these issues in a declarative, powerful, and fun way. That solution is GraphQL. In this blog, I’ll provide an introduction to the GraphQL specification with code examples…