openapi-python-client VS prettier

On the backend, developers either need to manually document the entire API or rely on auto-generation tools that don’t fully meet their needs. Consumers face the same choice, write code by hand or workaround the bugs in their SDK generator (stated, lovingly, as the maintainer of an OpenAPI client generator). On top of this, these solutions result in inconsistent understandings of the API. Reproducing errors becomes time-consuming and frustrating, which feels like a battle instead of a collaboration. What we need is a shared language to describe how the API works—one that doesn’t add unnecessary layers of abstraction or manual work.

Has anyone tried Kiota, specifically the Python support? How does it compare to https://github.com/openapi-generators/openapi-python-client ?

I think we use these - https://github.com/openapi-generators/openapi-python-client

Thanks for the link, but not necessarily.

How WSDL and the code generation around it worked, was that you'd have a specification of the web API (much like OpenAPI attempts to do), which you could feed into any number of code generators, to get output code which has no coupling to the actual generator at runtime, whereas Pyotr is geared more towards validation and goes into the opposite direction: https://pyotr.readthedocs.io/en/latest/client/

The best analogy that i can think of is how you can also do schema first application development - you do your SQL migrations (ideally in an automated way as well) and then just run a command locally to generate all of the data access classes and/or models for your database tables within your application. That way, you save your time for 80% of the boring and repetitive stuff while minimizing the risks of human error and inconsistencies, while nothing preventing you from altering the generated code if you have specific needs (outside of needing to make it non overrideable, for example, a child class of a generated class). Of course, there's no reason why this can't be applied to server code either - write the spec first and generate stubs for endpoints that you'll just fill out.

Similarly there shouldn't be a need for a special client to generate stubs for OpenAPI, the closest that Python in particular has for now is this https://github.com/openapi-generators/openapi-python-client

However, for some reason, model driven development never really took off, outside of niche frameworks, like JHipster: https://www.jhipster.tech/

Furthermore, for whatever reason formal specs for REST APIs also never really got popular and aren't regarded as the standard, which to me seems silly: every bit of client code that you write will need a specific version to work against, which should be formalized.

Tallying up the results, we get 7/8 "MUST" requirements met. I think that Paperclip + actix-web seems like the most promising candidate. I'm really not opposed to writing the OpenAPI v3 construction myself as I've worked with the structure a fair bit in my openapi-python-client project (shameless plug).

Automatic documentation via OpenAPI, which lets you do things like generate Python code that knows how to talk to your API.

In this post, I also use ESLint + Standard JS as my code formatting tools. Formatting JS/TS code by using ESLint is also subjective and opinionated, arguably most people would rather use Prettier instead, which provides more configurable options.

Let's be honest - setting up tools for a new project can be a frustrating process. Especially when you want to jump straight to coding part. This is often the case with ESLint and Prettier, two popular tools in the JavaScript ecosystem that can sometimes interfere with each other when it comes to code formatting. Fortunately, there's a simple solution to this process, and it's called eslint-plugin-prettier.

From my point of view, Prettier doesn't work well for styling with utility classes. For a discussion see Prettier#7863 or Prettier#5948.

Prettier: An opinionated code formatter that enforces a consistent code style.

Automating code checks with static code analysis allows us to enforce code styling effectively. By integrating tools into our workflow, we can identify errors at an early stage, while coding instead of blocking us at the end. For instance, flake8 checks Python code for style and errors, eslint performs similar checks for JavaScript, and prettier automatically formats code to maintain consistency.

So anyways, I wanted to hook up Emacs with Astro support. For now, I've just been roughing it out there and running Prettier by itself and turning off save on format and auto-complete. It's been scary.

If you're a developer, you're surely familiar with Prettier and ESLint. With over 8 years of existence, they have established themselves as references in the JavaScript ecosystem.

prettier is used to format you text

No formatting inconsistencies: The committed code should follow the organization's code formatting standards(prettier or pretty-quick).

Let’s walk through the steps for a one-time setup to configure husky pre-commit and pre-push hooks, ESLint with code styles conventions, prettier code formatter, and lint-staged. Husky automatically runs a script on each commit or push. This is useful for linting files to enforce code styles that keeps the entire code base following conventions.