How can you document APIs that are still in development?

Understand the API: Know its purpose, users, and usage. Use a Documentation Tool: Tools like Swagger or Postman can help. Document the Basics: For each endpoint, document the URL, HTTP method(s), parameters, response format, and error messages. Provide Examples: Include examples of requests and responses. Keep it Updated: Update the documentation as changes are made. Versioning: Consider versioning for significant changes.

The integration of Swagger, a documentation framework, is now a standard feature in most backend frameworks. It provides a structured way to describe RESTful APIs, enabling developers to understand a service’s capabilities without reading the source code. This also facilitates the automatic generation of client libraries or server stubs, enhancing productivity and collaboration.

Using a documentation framework is crucial for documenting APIs in development. These tools automate the process, extracting relevant information from code or configuration files. Examples like Swagger, Slate, and Apiary streamline documentation tasks, ensuring accuracy and consistency. By generating documentation automatically, developers save time and effort, allowing them to focus on refining the API. Additionally, these frameworks enable the creation of interactive documentation, enhancing user experience by providing a platform to test endpoints and view responses in real-time.

It is essential to use a documentation framework when documenting APIs in development. These frameworks automate the documentation process by extracting relevant information from code or configuration files. Some examples of such frameworks are Swagger, Slate, and Apiary. They simplify the documentation process, ensuring accuracy and consistency. By automatically generating documentation, developers can save time and effort, allowing them to focus on improving the API. Additionally, these frameworks enable the creation of interactive documentation, improving user experience by providing a platform to test endpoints and view responses in real-time.

If you are using Python, you can use FastAPI. A good framework with documentation generation. With this, you can see all your endpoints and use a visual gui to interact with them.

Adopt the way to have subtasks to create documentation, furthermore, use the code review space to review if the current docs are enough or if it's necessary to have more information. If it's necessary to have more docs or information, mark the PR as "need work".

Agile Principles for API Documentation: >Embrace iterative updates: Don't wait for the API to be finalized before documenting it. Start with minimal documentation and update it as features evolve. >Focus on value: Prioritize documenting aspects critical for developers, like endpoints, parameters, and responses. Leave more detailed explanations for later stages. >Use lightweight methods: Employ tools like Markdown, Google Docs, or API versioning platforms for ease of collaboration and quick updates. >Get feedback continuously: Involve developers and users in the documentation process, gathering feedback to ensure its relevance and clarity.

In an agile approach, we document APIs in development by using tools like Swagger or Postman. These tools allow us to update the documentation in real-time as changes are made. For example, when a new endpoint is added, we can immediately update the documentation to reflect this. This ensures that the documentation is always up-to-date, even when the API is still in development.

Applying an agile approach to API documentation enables iterative refinement, fostering collaboration and adaptability. By breaking tasks into smaller cycles and soliciting frequent feedback, documentation can swiftly evolve in sync with user needs and API advancements, ensuring relevance and effectiveness in a dynamic development landscape.

Version control systems like Git allow you to manage changes to your API documentation effectively. Create a repository for your documentation and use branching to work on updates without affecting the main documentation. This helps in organizing changes, reviewing them, and easily rolling back if needed, ensuring that your documentation stays consistent and accurate during development.

Version control and branching streamline API documentation management by synchronizing it with code development stages, ensuring consistency across different versions and reducing errors.

This can be done directly to the review if the documentation is embedded in the code, otherwise trigger a "callback" in any form, an issue created on gitlab, an entry in confluence, etc.

Frequent updates to your API documentation are essential to keep it aligned with the evolving state of your API during development. As you make changes to your API endpoints, parameters, or responses, reflect those changes promptly in your documentation. Regularly reviewing and updating your documentation ensures that developers have access to the latest information, reducing confusion and enhancing the developer experience.

I worked primarily on C so we used doxygen mostly. On some of my projects, the lead would include days spent on documentation as part of the effort estimate and we would discuss it at as an explicit action item in weekly meetings. I've had projects where I spent 4 months with my primary task being documentation of the system while other daily action items would be secondary tasks. In some projects we would require documentation to a prerequisite to even getting a +1 on gitlab from your reviewer. There are many ways to do this well. All it needs is a few thoughtful engineers with some actual power in your team.

Regular updates to API documentation foster responsiveness to evolving development stages, user feedback, and stakeholder input, enhancing documentation quality and usability while addressing gaps and issues promptly.

It is important to update documentation frequently it really trips the new developer if he doesn't know what he is doing. It will delay the project and increase security issues.

The best is when the documentation is generated directly from the code, this allows a real clear breakdown of uses, functional rules, etc.

* Acceptance criteria serve as a better reference for developers, testers, and stakeholders during the API development process. * They generally include information such as the endpoints under development, the type of request, status codes, and error messages.

Transparent communication of API development status and plans fosters collaboration, manages expectations, and cultivates user engagement, leveraging tools like GitHub or Trello for efficient information sharing and feedback integration.

Testing and reviewing API documentation is a good entry point for a better user experience. Accurate documentation ensures front-end/back-end developers understand and implement the API correctly, reducing errors and enhancing productivity. Consistency with code and readability aids in quick issue resolution. In short, well-maintained documentation is essential for effective communication, user satisfaction, and streamlined development.

Thorough testing and review of API documentation, integrating tools like Postman and Grammarly, ensures accuracy, clarity, and alignment with user needs, fostering robustness and usability in development stages.

Well the focus shouldn't be on how to document, rather what to document. Use anything to document and let your clients know about it. But what's critical is you should document properly, in simple terms, with examples. Make sure you keep updating as the API evolves.

Make sure your documentation can be easily found. Having a central location is great, but so too is having a hub or map that connects to dispersed documentation which enables anyone to find what they need. This also enables you to holistically keep track of the documentation and make sure it's up to date, or at the very least, lets users know when it was written or last edited to set their expectations. As well as traditional documentation, it's also a great idea to make knowledge maps of people, which will give people points of contacts for different areas of the software.

None of the proposed propositions, its 2024 .... ai is coding, is documenting, is formatting, is coloring, is doing things faster than you without a flaw :)

If AI is used more in development it will probably take care documentation and hence saves time on it. What we should focus is , is the code correct and is the documentation correct.