Recently, we were faced with the task of writing an API-first web application in order to support future mobile platform development. Here’s a summary of the project from the point of view of one of the developers.
For the first couple of iterations, we had problems demonstrating the project progress to the customer at the end of iteration meetings. The customer on this project was extremely understanding and reasonably tech-savvy but despite that, he remained uninterested in the progress of the API and became quite concerned by the lack of UI progress. Although we were busy writing and testing the API code sitting just beneath the surface, letting the customer watch our test suite run would have achieved nothing. It was frustrating to find that, when there was nothing for the customer to click around on, we couldn’t get the level of engagement and collaboration we would typically achieve. In the end, we had to rely on the wireframes from the design process which the customer had signed off on to inform our technical decisions and, to allay the customer’s fears, we ended up throwing together some user interfaces which lacked any functionality purely to give the illusion of progress.
On the plus side, once we had written enough of our API to know that it was fit for purpose, development on the front-end began and progressed very rapidly; most of the back-end validation was already in place, end-points were well defined, and the comprehensive integration tests we’d written served as a decent how-to-use manual for our API.
Developing the application API-first took more work and more lines of code than it would have required if implemented as a typical post-back website.
Each interface had to be judged by its general usefulness rather than by its suitability for one particular bit of functionality alluded to by our wireframes or specification. Any view that called upon a complex or esoteric query had to instead be implemented using querystring filters or a peculiar non-generic endpoint.
In a typical postback project with private, application-specific endpoints, we’d be able to pick and choose the HTTP verbs relevant to the template we’re implementing however our generic API required considerably more thought. For each resource and collection, we had to carefully think about the permissions structure for each HTTP method, and the various circumstances in which the endpoint might be used.
We wrote around 4000 lines of integration test code just to pin down the huge combination of HTTP methods and user permissions however I sincerely doubt that all of those combinations are required by the web application. Had we not put in the extra effort however, we’d have risked making our API too restrictive to future potential consumers.
In terms of future maintainability, I’d say that each new generic endpoint will require a comparable amount of otherwise-unnecessary consideration and testing of permissions and HTTP methods.
Having such an explicitly documented split between the front and back end was actually very beneficial. The front end and back-end were developed and tested based on the API we’d designed and documented. For over a month, I worked solely on the back-end and my colleague worked solely on the front and we found this division of labour was an incredibly efficient way to work. By adhering to the HTTP 1.1 specification, using the full range of available HTTP verbs and response codes, and to our endpoint specification, we required far less interpersonal coordination than would typically be the case.
The two major issues we found with generic CRUD endpoints were (1) when we needed to perform a complex data query, and (2) update multiple resources in a single transaction.
To a certain extent we managed to solve the first problem using querystrings, with keys representing fields on the resource. For all other cases, and also to solve the second problem, we used an underused yet still perfectly valid REST resource archetype: the controller, used to model a procedural concept.
We used controller endpoints on a number of occasions to accommodate things like /invitations/3/accept (“accept” represents the controller) which would update the invitation instance and other related user instances, as well as sending email notifications.
Where we needed to support searching, we added procedures to collections, of the form /applicants/search, to which we returned members of the collection (in this example “applicants”) which passed a case-insensitive containment test based on the given key.
API-first required extra implementation effort and a carefully-considered design. We found it was far easier and more efficient to implement as a generic, decoupled back-end component than in the typical creation process (model -> unit test -> url -> view -> template -> integration test), with the front-end being created completely independently.
In the end, we wrote more lines of code and far more lines of integration tests. The need to stringently adhere to the HTTP specification for our public API really drove home the benefits to using methods and status codes.
In case you’re curious, we used Marionette to build the front-end, and Django REST Framework to build the back end.