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JavaScript Marathon: How to Write Clean Code

Writing clean code is an essential part of any developer’s toolkit. Not only does it ensure legibility, but it also helps you and other developers understand what your code is doing at a quick glance.

In this article, I’ll share with you the key takeaways from Nacho Vazquez’s session on writing clean code. These points can be found in Uncle Bob’s book “Clean Code: A Handbook of Agile Software Craftsmanship”.

Host

Nacho Vazquez @nacho_devc
  • Software Engineer, This Dot Labs

Key Takeaways

  • Clean code is more of an art and intuition!!
  • To become effective at writing clean code, constant practice is needed!
  • In order to write clean code, a combination of proper naming with variables, functions and components is needed.
  • Don't be afraid to use long names for your variables

Naming Lessons for Programming!

JSMarathon  N_V SS #1
  • No abbreviations
  • Avoid disinformation
  • Make meaningful distinctions
  • Pronounceable names
  • Searchable names
  • Use domain-specific names
  • Abstraction and code-splitting is effective, yet needs to be managed carefully
JSMarathon N_V SS #2
  • Abbreviations
    • Don't Repeat Yourself
    • Write Everything Twice
    • Avoid Hasty Abstractions
    • You Ain't Gunna Need It
  • Don't abstract prematurely. Wait until it becomes necessary (if your code starts to become hard to read for example).
JSMarathon N_V SS #3

If you missed the #javascriptmarathon make sure to head on over and watch it. Nacho shares a lot of useful information in such a short period of time alongside practical examples.

This Dot Labs is a development consultancy that is trusted by top industry companies, including Stripe, Xero, Wikimedia, Docusign, and Twilio. This Dot takes a hands-on approach by providing tailored development strategies to help you approach your most pressing challenges with clarity and confidence. Whether it's bridging the gap between business and technology or modernizing legacy systems, you’ll find a breadth of experience and knowledge you need. Check out how This Dot Labs can empower your tech journey.

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Drizzle ORM: A performant and type-safe alternative to Prisma cover image

Drizzle ORM: A performant and type-safe alternative to Prisma

Introduction I’ve written an article about a similar, more well-known TypeScript ORM named Prisma in the past. While it is a fantastic library that I’ve used and have had success with personally, I noted a couple things in particular that I didn’t love about it. Specifically, how it handles relations with add-on queries and also its bulk that can slow down requests in Lambda and other similar serverless environments. Because of these reasons, I took notice of a newer player in the TypeScript ORM space named Drizzle pretty quickly. The first thing that I noticed about Drizzle and really liked is that even though they call it an ‘ORM’ it’s more of a type-safe query builder. It reminds me of a JS query builder library called ‘Knex’ that I used to use years ago. It also feels like the non-futuristic version of EdgeDB which is another technology that I’m pretty excited about, but committing to it still feels like a gamble at this stage in its development. In contrast to Prisma, Drizzle is a ‘thin TypeScript layer on top of SQL’. This by default should make it a better candidate for Lambda’s and other Serverless environments. It could also be a hard sell to Prisma regulars that are living their best life using the incredibly developer-friendly TypeScript API’s that it generates from their schema.prisma files. Fret not, despite its query-builder roots, Drizzle has some tricks up its sleeve. Let’s compare a common query example where we fetch a list of posts and all of it’s comments from the Drizzle docs: ` // Drizzle query const posts = await db.query.posts.findMany({ with: { comments: true, }, }); // Prisma query const posts = await prisma.post.findMany({ include: { comments: true, }, }); ` Sweet, it’s literally the same thing. Maybe not that hard of a sale after all. You will certainly find some differences in their APIs, but they are both well-designed and developer friendly in my opinion. The schema Similar to Prisma, you define a schema for your database in Drizzle. That’s pretty much where the similarities end. In Drizzle, you define your schema in TypeScript files. Instead of generating an API based off of this schema, Drizzle just infers the types for you, and uses them with their TypeScript API to give you all of the nice type completions and things we’re used to in TypeScript land. Here’s an example from the docs: ` import { integer, pgEnum, pgTable, serial, uniqueIndex, varchar } from 'drizzle-orm/pg-core'; // declaring enum in database export const popularityEnum = pgEnum('popularity', ['unknown', 'known', 'popular']); export const countries = pgTable('countries', { id: serial('id').primaryKey(), name: varchar('name', { length: 256 }), }, (countries) => { return { nameIndex: uniqueIndex('nameidx').on(countries.name), } }); export const cities = pgTable('cities', { id: serial('id').primaryKey(), name: varchar('name', { length: 256 }), countryId: integer('countryid').references(() => countries.id), popularity: popularityEnum('popularity'), }); ` I’ll admit, this feels a bit clunky compared to a Prisma schema definition. The trade-off for a lightweight TypeScript API to work with your database can be worth the up-front investment though. Migrations Migrations are an important piece of the puzzle when it comes to managing our applications databases. Database schemas change throughout the lifetime of an application, and the steps to accomplish these changes is a non-trivial problem. Prisma and other popular ORMs offer a CLI tool to manage and automate your migrations, and Drizzle is no different. After creating new migrations, all that is left to do is run them. Drizzle gives you the flexibility to run your migrations in any way you choose. The simplest of the bunch and the one that is recommended for development and prototyping is the drizzle-kit push command that is similar to the prisma db push command if you are familiar with it. You also have the option of running the .sql files directly or using the Drizzle API's migrate function to run them in your application code. Drizzle Kit is a companion CLI tool for managing migrations. Creating your migrations with drizzle-kit is as simple as updating your Drizzle schema. 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How to automatically deploy your full-stack JavaScript app with AWS CodePipeline cover image

How to automatically deploy your full-stack JavaScript app with AWS CodePipeline

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JavaScript Marathon: Building Your Own Style Framework With Vanilla Extract cover image

JavaScript Marathon: Building Your Own Style Framework With Vanilla Extract

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Testing a Fastify app with the NodeJS test runner cover image

Testing a Fastify app with the NodeJS test runner

Introduction Node.js has shipped a built-in test runner for a couple of major versions. Since its release I haven’t heard much about it so I decided to try it out on a simple Fastify API server application that I was working on. It turns out, it’s pretty good! It’s also really nice to start testing a node application without dealing with the hassle of installing some additional dependencies and managing more configurations. Since it’s got my stamp of approval, why not write a post about it? In this post, we will hit the highlights of the testing API and write some basic but real-life tests for an API server. This server will be built with Fastify, a plugin-centric API framework. They have some good documentation on testing that should make this pretty easy. We’ll also add a SQL driver for the plugin we will test. Setup Let's set up our simple API server by creating a new project, adding our dependencies, and creating some files. 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Node’s assert API has been around for a long time, this is what we are using to make our test assertions. To run this test, we can use the following command: By default the Node.js test runner uses the TAP reporter. You can configure it using other reporters or even create your own custom reporters for it to use. Testing our SQL plugin Next, let's take a look at how to test our Fastify Postgres plugin. This one is a bit more involved and gives us an opportunity to use more of the test runner features. In this example, we are using a feature called Subtests. This simply means when nested tests inside of a top-level test. In our top-level test call, we get a test parameter t` that we call methods on in our nested test structure. In this example, we use `t.beforeEach` to create a new Fastify app instance for each test, and call the `test` method to register our nested tests. Along with `beforeEach` the other methods you might expect are also available: `afterEach`, `before`, `after`. Since we don’t want to connect to our Postgres database in our tests, we are using the available Mocking API to mock out the client. This was the API that I was most excited to see included in the Node Test Runner. After the basics, you almost always need to mock some functions, methods, or libraries in your tests. After trying this feature, it works easily and as expected, I was confident that I could get pretty far testing with the new Node.js core API’s. Since my plugin only uses the end method of the Postgres driver, it’s the only method I provide a mock function for. Our second test confirms that it gets called when our Fastify server is shutting down. Additional features A lot of other features that are common in other popular testing frameworks are also available. Test styles and methods Along with our basic test` based tests we used for our Fastify plugins - `test` also includes `skip`, `todo`, and `only` methods. They are for what you would expect based on the names, skipping or only running certain tests, and work-in-progress tests. If you prefer, you also have the option of using the describe` → `it` test syntax. They both come with the same methods as `test` and I think it really comes down to a matter of personal preference. Test coverage This might be the deal breaker for some since this feature is still experimental. As popular as test coverage reporting is, I expect this API to be finalized and become stable in an upcoming version. Since this isn’t something that’s being shipped for the end user though, I say go for it. What’s the worst that could happen really? Other CLI flags —watch` - https://nodejs.org/dist/latest-v20.x/docs/api/cli.html#--watch —test-name-pattern` - https://nodejs.org/dist/latest-v20.x/docs/api/cli.html#--test-name-pattern TypeScript support You can use a loader like you would for a regular node application to execute TypeScript files. Some popular examples are tsx` and `ts-node`. In practice, I found that this currently doesn’t work well since the test runner only looks for JS file types. After digging in I found that they added support to locate your test files via a glob string but it won’t be available until the next major version release. Conclusion The built-in test runner is a lot more comprehensive than I expected it to be. I was able to easily write some real-world tests for my application. If you don’t mind some of the features like coverage reporting being experimental, you can get pretty far without installing any additional dependencies. The biggest deal breaker on many projects at this point, in my opinion, is the lack of straightforward TypeScript support. This is the test command that I ended up with in my application: I’ll be honest, I stole this from a GitHub issue thread and I don’t know exactly how it works (but it does). If TypeScript is a requirement, maybe stick with Jest or Vitest for now 🙂...