How can you design APIs to be more user-friendly?

Actively seek feedback from potential or current users of similar APIs. This can be achieved through surveys, interviews, or studying user behavior on existing platforms. If you have access to data on how users interact with similar tools or APIs, analyze this data for insights into common usage patterns, preferences, and pain points. Develop detailed user personas that represent the different types of users who will interact with your API. Personas should include information about the users' technical skills, their goals when using the API, and the environments in which they will use it. Create user journey maps to visualize the process that users go through to achieve their goals using your API.

Understanding the users is the cornerstone of designing user-friendly APIs. Start by identifying the target developers, their technical backgrounds, and the specific use cases they aim to solve with the API. Gather feedback early and often, aligning the API design with real-world workflows and needs. This allows to anticipate challenges and offer intuitive, seamless solutions that enhance productivity. Empathy-driven design not only simplifies the API adoption but fosters a loyal developer community around the product.

To design user-friendly APIs: 1. Use clear and consistent naming. 2. Provide thorough documentation with examples. 3. Implement versioning for backward compatibility. 4. Follow RESTful design principles and use standard HTTP status codes. 5. Use common data formats (e.g., JSON). 6. Securely handle authentication and authorization. 7. Implement rate limiting and clear error handling. 8. Offer a testing environment. 9. Engage with the developer community for feedback and support.

Additionally, consider gathering feedback from potential users during the initial stages of API development. Engaging with developers who will interact with your API provides invaluable insights into their preferences, pain points, and expectations. By incorporating user feedback iteratively, you ensure that the API aligns closely with the needs and workflows of its intended audience. Think of it as crafting a tool that seamlessly fits into the toolkit of your users, simplifying their tasks and enhancing their overall experience. Just as a well-designed product resonates with its users, a thoughtfully crafted API fosters a positive and efficient developer experience, ultimately contributing to the success and adoption of your platform.

Make the API easier to call! Instead of having an argument list of 15 diverse types of data put the data in a package - think structure! Then pass on reference, or pointer to that structure. Try to break down what the data MEANS to the hardware - NOT THE END USER who is not doing any of the programming. Figure out which piece of software/firmware is responsible to do what it does and then write that down. Proper decomposition of the problem is a must. In electronics and software/firmware engineering most teams do not know how to properly decompose the issue. Proper decomposition will yield better organization of the code! Better organization yields better API's.

One thing i have found very essential in API design is the url structures. Develop the urls in such a way that your clients can always guess what the url will be for any needed resources. They will always thank you for following their thinking. Furthermore, JSON is common, and for many use cases, the most preferred, followed by any other formats like XML depending on who your customers are.

I just would like to mention a standard which was not mentioned here yet. If your target audience would be some kind of technically advanced user, consider GRPC as well because it has tons of benefits for the developers: it allows to generate clients automatically for many languages while being bandwidth efficient. And please, avoid XML as much as you can, we are in 2023

100%, but I have an opinion, adhering to all the standards of JSON API is good approach but also seek inspiration from public documentation of prominent players in the space. an example is let's say I am building a GET ALL records endpoint. the convention says return a HTTP 206 when returning filtered results. But for a public API consumer that is an overkill. I see github's, stripes' and Twilio's api all return a OG 200 OK. So we have to keep in mind the importance of seeking inspiration.

Make sure your APIs are as self-explanatory as possible, with clear nomenclature and definitions, and always avoid unexpected behavior.

Even if trying to achieve certain standards like RESTFULL might sound like an uthopy, having an standards-based design and implementation is one of the best things we can do from every possible point of view, it will make life enjoyable for both clients and fellow developers

I've found that the most useful and up to date API documentation is a good OpenAPI (Swagger) definition viewed through swagger-ui or postman. Keeping documentation as code comments means it is top of mind during implementation and can be seen in pull requests by approvers.

Not just making clear and comprehensive documentation, but also making it clearly available is important too. Documentation is only good if users and prospective users can find it - and not being able to find documentation (for both internal and external users) increases the likelihood that duplicate APIs will be created, or those with a very similar cut of features.

I’d agree with comments made on here already to prioritize clear documentation with comprehensive examples. Use intuitive naming conventions, provide error details, and ensure consistent responses. Also, regularly update and communicate changes to users, making the API a seamless experience.

When documenting you API do well to save examples of the response and this would help the users of the API know what to expect

As I've mentioned before, GRPC has plenty of additional benefits. One of that is tooling to keep your implementation in sync with the actual implementation. You can even implement JSON API on top of GRPC by just using a GRPC gateway which will generate all of the needed openapi/swagger docs out of the box.

Aim for simplicity, breaking down complex APIs into simpler ones will be helpful most of the times. You should also follow a naming framework consistent with the how the API would be consumed. You should also make sure that the documentation is clear and concise with details about the parameters expected and the result returned

I agree. API should be consistent and simple to use. Adding more complexity means confusing the users. Consistency is the key to make user friendly API because it gives user confidence to use it.

While designing your API you should always consider your data model, and especially the size of the response. So keep in mind websockets and grpc streams or pagination if you have the intention to serve a lot of data, or close to realtime updates. And also consider a separate download endpoint which works in the async fashion (request, then pull for completion) if you would still need to provide the full data dumps.

Make easy use cases easy and hard ones possible. It may not be possible to create an easy workflow for complex needs, but it may be possible to create sugar APIs that hide the complexity by handling the common scenarios. Like what the Facade design pattern does. Also, complex use cases should not cause the APIs to have unnecessary complexity for common scenarios.

This is probably the most important part, keep it simple, consistent and as close to standard as possible. In the long term this will be useful.

I will talk about the SaaS solution that our team develops. Swagger helps with its legend and schema, it allows us to see clear paths and also allows the autogeneration of clients for different languages. We cover all CUD operations from CRUD with API tests. It helps to find issues in earlier stages of the development cycle and reduces our QA load. With API tests you can validate authorization, integration calls, DB update operations etc. It is not the silver bullet and unit tests are still desirable, but the benefit of API tests is not only the ability to test multiple units but also to test API call processing and API consistency, reducing chances for missed braking changes. Just pick the tool of your choice and start covering with tests

-Clear and Consistent Naming: Use clear, descriptive names for endpoints, methods, parameters, and responses. Keep naming conventions consistent across the API to avoid confusion -Versioning and Stability: Implement versioning to allow for updates without breaking existing functionalities. Ensure backward compatibility wherever possible to prevent disruptions for existing users. -Predictable Responses: Ensure consistent and predictable responses to API requests, with clear error messages. Use standard HTTP status codes to indicate the result of a request (e.g., 200 for success, 404 for not found, etc.). -Proper Error Handling: Provide informative error messages with relevant details to help developers troubleshoot issues.

Swagger/Openapi provides enough data for automated tests. But it's not the panacea. I would recommend using a BDD tests for your API: that will provide the actual documentation while allowing extensive tests of business logic

Test every endpoint like if the person who will be consuming is a serial killer that knows your house address, enforce clear contracts and verify every response code once and again, it's all about being a trustworthy source of data

Leverage automated API testing here tools like postman are so well optimized to generate tests on the basis of sample usage of API. In my opinion APIs are the best candidates for continuous delivery and deployment because of higher developer control. Also use packt for contract testing to ensure the APIs work well in tandem when integrated.

Use versioning sparingly. Instead of breaking API consumptions, version it and make this clearly stated in the documentation. Common approach include adding the version number in the url with the same construct: api/v1/payment/{id}, api/v2/payment/{id}

If you need to break an API, don't do it instantly. Instead, make the API deprecated for a while and show a warning to users. Give time to users of API to change their software.

API continuous improvement and evolution also involves a carefully planned backward compatibility and versioning, your first consumers invested time and effort, they should remain an important client through all the lifecycle of your API

Prioritize robust error handling by providing clear, meaningful error messages that guide users in resolving issues. Manage usage efficiently by setting transparent rate limits and quotas, alongside guidance for handling these limits. Enhance performance and reliability through a Federated GraphQL approach, which consolidates multiple service data through a single gateway, ideal for microservices architectures. This setup simplifies client queries, utilizes strong typing and introspection for clarity, and ensures efficient data loading, optimizing the overall user experience.

It is crucial to select the appropriate types of APIs, such as REST, GraphQL, gRPC, etc. I mention "types" because it is possible to expose identical functionalities through multiple APIs. For instance, GitHub utilizes REST for a portion of its API while employing GraphQL for another part. This approach offers users greater flexibility in their work.

Know the context and needs. Designing for Performance, Ease of Use, or Extensibility have their own constraints, for example. So a best practice for one scenario may not be an option for another.

Single Responsibility for each API. Versioning of API. Sandbox environment for testing the api. Sample payloads and clear Secured access to documentation. Detailing mandatory properties in the payload. Proper status code on response. Usage of proper noun for naming the API Description on Error Codes and Error Messages.

This article heavily focuses on web-based APIs. There is nothing wrong with this, but we just should keep in mind that the term API (application programming interface) is used equally often in other domains, for example class libraries that accompany a programming language, or an operating system. A lot of the best practices mentioned in this article apply in other domains, too, while others may not.