Schemathesis VS NSwag

I am not aware of any tools like that, but eventually, I plan to add support for gRPC fuzzing to Schemathesis. There were already some discussions and it is more or less clear how to move forward. See https://github.com/schemathesis/schemathesis/discussions/190...

Why is AI needed for this at all? Have you heard about Schemathesis (https://github.com/schemathesis/schemathesis)?

SchemaThesis is a powerful tool, especially when working with web APIs, and here's how it can enhance your testing capabilities:

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

Consolidating the API specification with OpenAPI was a turning point for the project. From that moment we were able to run mock servers to build and test the UI before integrating with the backend, and we were able to validate the backend implementation against the specification. We used prism to run mock servers, and Dredd to validate the server implementation (these days I’d rather use schemathesis).

In this approach, you produce an API specification first, then you build the API against the specification, and then you validate your implementation against the specification using automated API testing tools. This is the most reliable approach for building API servers, since it’s the only one that holds the server accountable and validates the implementation against the source of truth. Unfortunately, this approach isn’t as common as it should be. One of the reasons why it isn’t so common is because it requires you to produce the API specification first, which, as we saw earlier, puts off many developers who don’t know how to work with OpenAPI. However, like I said before, generating OpenAPI specifications doesn’t need to be painful since you can use tools for that. In this approach, you use automated API testing tools to validate your implementation. Tools like Dredd and schemathesis. These tools work by parsing your API specification and automatically generating tests that ensure your implementation complies with the specification. They look at every aspect of your API implementation, including use of headers, status codes, compliance with schemas, and so on. The most advanced of these tools at the moment is schemathesis, which I highly encourage you to check out.

Keep all API versions in the code Another strategy is to have all the different API versions in the same code. So you may have a folder structure that looks like this: api ├── v1 └── v2 Within the API folder, you have one folder for v1 and another one for v2. Each folder has its own schemas and routes as required by the API version they implement. If you use URL-based versioning, v1 is accessible through the example.com/v1 endpoint or the v1.example.com subdomain (whichever strategy you use), and same for v2. Deprecating a version is a simple as its corresponding folder. In any case, I'd recommend you also validate your API implementations in the CI using something like schemathesis. Schemathesis looks at the API documentation and automatically generates hundreds of tests to make sure you're using the right schemas, status codes, and so on. It works best if you design and document the API before implementing, which allows you to include OpenAPI links and other features.

schemathesis – Run generated test scenarios based on your OpenAPI specification

https://github.com/RicoSuter/NSwag

There is no need to be facetious solutions like these exist for many platforms and ecosystems out there.

With best regards.

I'm mostly using it for C# API client generation from backend code - sort of similar to what a tool like NSwag Studio will do. I think NTypewriter has more flexibility though, and having a live view with the VS plugin makes development quick.

NSwag does a wonderful job of generating TypeScript clients from OpenAPI specs. Definitely give it a shot before killing your current setup.

https://github.com/RicoSuter/NSwag (It sucks in any OpenAPI yml, not just ones from Swashbuckle/C#)

I use this https://github.com/RicoSuter/NSwag but it's designed for .Net backends to some extent. But you can use the client generation from the command line or manually with the standalone client app.

Here are three tools that you can use to generate example API requests and responses from OpenAPI specifications. These tools should work well even if your schemas are deeply nested: Nswag (Command Line and GUI): Nswag is a Swagger/OpenAPI toolchain for .NET, TypeScript, and other platforms. It supports code generation, client generation, and API documentation. You can use NswagStudio, which is a graphical interface, or you can use the command line tool called "NSwag.exe" for generating example API requests and responses. GitHub: https://github.com/RicoSuter/NJsonSchema NswagStudio: https://github.com/RicoSuter/NSwag/wiki/NSwagStudio Dredd (Command Line): Dredd is a language-agnostic command-line tool for validating API descriptions against backend implementations. It supports OpenAPI, Swagger, and API Blueprint formats. Dredd can generate example requests and responses and validate whether your API implementation conforms to the API description. GitHub: https://github.com/apiaryio/dredd Documentation: https://dredd.org/en/latest/ Stoplight Studio (GUI): Stoplight Studio is a modern API design and documentation platform that supports OpenAPI and JSON Schema. It allows you to create, edit, and validate OpenAPI specifications and provides a powerful visual interface for generating example API requests and responses. Website: https://stoplight.io/studio/ GitHub: https://github.com/stoplightio/studio These tools should provide you with the ability to generate example API requests and responses from your OpenAPI specifications and handle deeply nested schemas.

I’ve got an ASP.NET Core web API - I integrate NSwag (which I prefer to Swashbuckle - personal preference), run the app locally to generate the actual JSON file. See https://github.com/RicoSuter/NSwag Then I have a Bicep file that creates the API from the OpenAPI specification. Sorry - I don’t do Terraform (most of the Azure samples are of Bicep, but it should be easy to convert).

I have actually found that, but I was hoping for something with more popularity. E.g. this one is for .NET: https://github.com/RicoSuter/NSwag ( you can also generate typescript clients). But I do not want to bring in the dependency to another language, if possible.