taxilang VS http-spec

Under the hood, the tags (and associated query language) are actually Taxi - an OSS meta-language and toolchain we build (and have shared previously).

Taxi is a relatively new entrant in the API space. It's goal is to let developers add simple, (but type-safe) tags into their APIs, so software can understand how different APIs relate to one another.

One of the gripes I have about OpenAPI is that it has a very low signal-to-noise ratio. It was bad in JSON, it's just as bad in YAML, with an added whitespace pedantry.

It's great to see a number of alternatives listed in this thread - there's much more active development in this space then I was aware of, and I hope that some of it gets upstreamed back into OpenAPI.

I'll shamelessly plug our tool in this space - Taxi (https://github.com/taxilang/taxilang), which has a dedicated DSL (not YAML) you can either use standalone, or embeddedd within OpenAPI.

I also happen to think that (for internal teams at least), generating clients on ${apiSpec} is a form of tight coupling, where producer and consumer become tied together. If you can avoid it, you should, as it allows producers and consumers to stay loosely coupled and evolve independetly without the gymnastics of avoiding breaking changes.

I've talked about this before, with proposed solutions.[0]

[0]https://orbitalhq.com/blog/2023-01-16-using-semantic-metadat...

However, we do not need to write the specification by hand, as there are GUI editors to perform that task. We show a couple of examples of Spotlight, which provides an easy-to-use interface:

We use Stoplight Studio https://stoplight.io/ to design APIs, one of the advantages of Stoplight Studio is the Visual interface, it generates OpenAPI specs from the design and supports OpenAPI v3, allowing users to create, edit, and view API designs using the OpenAPI standard.

I'm sorry, but you have completely misunderstood the purpose of Open API.

It is not a specification to define your business logic classes and objects -- either client or server side. Its goal is to define the interface of an API, and to provide a single source of truth that requests and responses can be validated against. It contains everything you need to know to make requests to an API; code generation is nice to have (and I use it myself, but mainly on the server side, for routing and validation), but not something required or expected from OpenAPI

For what it's worth, my personal preferred workflow to build an API is as follows:

1. Build the OpenAPI spec first. A smaller spec could easily be done by hand, but I prefer using a design tool like Stoplight [0]; it has the best Web-based OpenAPI (and JSON Schema) editor I have encountered, and integrates with git nearly flawlessly.

2. Use an automated tool to generate the API code implementation. Again, a static generation tool such as datamodel-code-generator [1] (which generates Pydantic models) would suffice, but for Python I prefer the dynamic request routing and validation provided by pyapi-server [2].

3. Finally, I use automated testing tools such as schemathesis [3] to test the implementation against the specification.

[0] https://stoplight.io/

[1] https://koxudaxi.github.io/datamodel-code-generator/

[2] https://pyapi-server.readthedocs.io

[3] https://schemathesis.readthedocs.io

One of the best tools out there for API design and governance https://stoplight.io/ you can also use the open source tool (also from Stoplight) called Spectral https://stoplight.io/open-source/spectral

Stoplight is a platform for designing, documenting, and testing APIs. Its "Mocks" feature allows you to create mock versions of your API for testing and development purposes. In addition to the mock feature, Stoplight also includes tools for API design, documentation, and testing, making it a comprehensive platform for API development.

Stoplight

JSON visualizer JSON validator YAML validator Collaborative Design & Documentation for APIs