Tag Archives: API Docs

Is GraphQL really “self-documenting”?

If you Google for ‘API trends’ or ‘the future of APIs’ , one technology that crops up a lot is GraphQL. Developers rave about it being a more powerful and flexible alternative to REST. Not only that but if you’re a technical writer like me, claims that it is self-documenting are particularly interesting. So what is GraphQL and is it really as self-documenting as people say?

What is GraphQL?

GraphQL is an open source data query and manipulation language that was developed internally by Facebook for their mobile applications before being released publicly in 2015. Since then it has grown in popularity with some people claiming it might replace REST APIs in the future.

Like REST APIs, both operate over HTTP with requests being sent to retrieve or manipulate data. The key difference is with REST you might need to send requests to multiple endpoints to retrieve a particular set of data, with GraphQL there is only one endpoint so with a single request you can retrieve an object and all of its related objects.

For example, with this GraphQL schema and server wrapping the SWAPI (Star Wars API), you can retrieve multiple pieces of data using just one endpoint. In this case, finding out the species and home planet of Luke Skywalker by adding more fields to the endpoint:

Star-Wars-GraphQL

“The self-descriptive nature of GraphQL”

There seems to be plenty of love for GraphQL on Twitter with developers praising its speed, flexibility and introspective nature. The other key attribute that crops up a lot is “self-documenting” or “self-descriptive”:

One developer even went as far to say that GraphQL doesn’t require documentation at all. However, after playing around with GraphQL and experimenting with some public GraphQL examples out there, I’m not so sure I agree.

Naming matters

The key thing about GraphQL from a documentation perspective is the importance of naming. Lee Byron, one of developers behind GraphQL, spoke about this in his talk “Lessons from Four Years of GraphQL” at the GraphQL Summit in November 2016: “Naming things is super important in GraphQL APIs,” he said. “An important question to ask when designing APIs is ‘Would a new engineer understand this?'[… ] And that means no code names or server-side lingo.”

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Lee Byron, one of the developers behind GraphQL, spoke about the importance of naming.

He continued: “Imagine that most of the engineers who are going to be using your API might not find it so easy to go and find out how that field maps to some underlying system. It’s really important not just to have names that are good but to have names that are self-documenting. Naming things that adhere closely to what those things actually do is really important to make this experience actually work.”

“An important question to ask when designing APIs is ‘Would a new engineer understand this?’ […] Naming things that adhere closely to what those things actually do is really important to make this experience actually work.” – Lee Byron

Despite Byron’s warnings, fields with poor or no descriptions were a common issue in the different GraphQL APIs I looked at. In the example below, taken from the GraphiQL documentation explorer, I had no idea what the ‘section’ query field did or what data it sent back because it had no description:

Screen Shot 2018-07-25 at 18.44.37

Apart from the documentation explorer, another way to see what query and mutation fields are available is the auto-populating feature in GraphiQL. Hovering over the field or type reveals a description but this can be as useless as the description in the documentation explorer if all it says is ‘Self descriptive’, as this Twitter user found out:

Does GraphQL need documentation?

I agree that GraphQL is self-descriptive and if you’re familiar with the query language and the schema, its introspective nature means it is easy to refer to the description of a field or type to find out what it does. One of the other advantages of GraphQL is the API documentation is easy to keep accurate and up-to-date as the descriptions are pulled directly from the code. In version 0.7 or above of GraphQL, this is as simple as adding a comments directly above the type or field in the code:

Star-Wars

However, GraphQL is only “self-documenting” if the developer or a technical writer has given the fields adequately intuitive or self-descriptive names or has added decent descriptions for them in the schema code. If the names are obscure or the descriptions aren’t great then your GraphQL API is as useful as a chocolate teapot and there are already a few chocolate teapots out there from what I’ve seen. So I guess the good news for technical writers is that we still have a role to play in helping to document GraphQL, it isn’t a magical solution that renders us unnecessary just yet!

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The Story behind Slate: An Interview with Robert Lord

Back in 2013, developer Robert Lord, then an 18-year-old intern at Tripit travel software company, was challenged to create an API documentation tool by his boss. It took him several weeks but the result was a beautiful, responsive API documentation generator called Slate. Five years later, it has grown into a popular open-source tool that is used by a number of global organisations and companies including NASA, IBM and Coinbase.

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Robert Lord created Slate while interning at Tripit. Copyright© Concur Technologies,

Lord said the Slate project grew out of a set of requirements the Tripit engineering team had at the time. He said: “I was interning at TripIt and my boss pointed me towards some two-column documentation pages and said ‘We’d like a page like this for our new API.’ They also had the requirement that their technical writer could make changes, and I think they didn’t want to write raw HTML. I made a generator that ended up being pretty generic to any documentation, and convinced them to let me open source it.”

How to Use Slate

Slate is simple to use, you fork the Slate Github repository and create a clone. Next you customise the code to meet your requirements; adding a custom logo, fonts and any additional CSS styling in the source folders, before adding your API endpoints and their descriptions in Markdown.

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Slate helps users to create beautiful, intelligent and responsive API documentation.

When you’re done, you start Slate and launch your API documentation site using Vagrant or create an image using Docker. The result is an attractive, responsive three-panelled API documentation site with code samples in multiple languages down one side and a smooth scrolling table of contents down the other. For more information on how to use Slate, follow the instructions in the Slate README.

Slate in the Wild

Today more than 90 people have contributed to Slate on Github, it has been forked more than 13,000 times and has been given more than 23,000 stars. Some of the organisations and companies listed as users include NASA, IBM, Sony, Monzo, Skyscanner and Coinbase. There is a list of more than 90 companies that have used it on the Slate in the Wild sub-page of the repository.

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Lord admits he still finds it “pretty surreal” that such large companies have adopted what he labels the “buggy project” he created as a teenager. “I really did not expect anybody else to see it or care about it,” he said. “Slate never really had a big rush of new users all at once, the growth in stars has been more or less linear over the years. No hockey sticks here. So there was never a single moment where suddenly a bunch of people were using it, it was a very slow process of discovering one company at a time.”

Life after Slate

Interestingly, a year after working at Tripit, Lord interned at Stripe, one of the leading API-first companies whose own API documentation inspired him when creating Slate. Stripe realised the value of their product hinged on people being able to read and digest their APIs. They invested a lot of time and effort in developing their own in-house API documentation tool and set the bar for the rest of the industry with the two-panelled design that has inspired so many other API tools.

Lord had plans to develop further API tools but decided to focus on other things. “Initially had some plans for similar tools,” he said. “But I think I realized I’m still early in my career, and would rather branch out and work on a variety of projects instead of focusing in on just one area.” Despite moving onto other projects and being fairly modest about the success of Slate, it’s an impressive piece of work for the young developer to put on his resumé. Indeed, one of the main reasons he asked Tripit to allow him to open source the project was so he could show future employers his work. “I mostly convinced them to open source it just so I could point future employers to this chunk of code I wrote,” he said. One company clearly took notice, Lord starts work on Fuschia at Google in a few of weeks time.