joi VS prettier

Code in Docusaurus This module validates and processes frontmatter objects by using Joi library for the data validation.

Once you've leaped into thinking as a serverless problem solver, it makes a lot of sense to standardize some tooling and frameworks. The old adage right tool for the job is what I like about this layer of the pyramid. For instance, if a problem requires flexibility in data and your team enjoys validating schema with Joi then you might use TypeScript with a Node.js runtime with your lambdas. If you prefer the developer experience and small footprint and simplicity of Go then use the Go 1.x runtime. You might find you don't need "compute" at all, so using intrinsic functions in State Machines might be plenty.

Validation: request data validation using Joi

I'm using Joi on my server to validate form input, do you think I still need honeypot fields? It sounds like it might be worth looking into IP rate limiting as well, I don't think Joi can help with that.

What does your library provide that others don't? For example: https://github.com/colinhacks/zodhttps://github.com/hapijs/joihttps://github.com/jquense/yuphttps://github.com/gcanti/io-tshttps://github.com/pelotom/runtypeshttps://github.com/sindresorhus/ow

Yup's API is heavily inspired by Joi, but leaner and built with client-side validation as its primary use-case. Yup separates the parsing and validating functions into separate steps. cast() transforms data while validate checks that the input is the correct shape. Each can be performed together (such as HTML form validation) or seperately (such as deserializing trusted data from APIs).

Yup is a Javascript object schema validator: it lets you define a schema to describe how a valid object should look like, and allows you to validate an object using this schema. If you know Joi, Yup is heavily inspired by it, except it relies on client-side validation as its primary use-case.

Again a widely used open source validation library like Joi can help you easily create schemas and transform the data into safe objects.

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.