Collective #547





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Chakra UI

Chakra UI is a simple, modular and accessible component library that gives you all the building blocks you need to build your React applications.

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Burn

An amazing paper burn image transition made with Three.js by Yoichi Kobayashi.

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Popup Pump

Matthew Rayfield’s hilarious popup windows experiment where you can enlarge a browser window by “pumping” another one.

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PowerToys

PowerToys is a set of utilities for power users to tune and streamline their Windows experience for greater productivity.

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SVG to JSX

An SVG to JSX plugin for Figma so you can get the JSX code automatically inside Figma. By Sara Vieira.

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Offline listings

Remy Sharp shares how he implemented offline access to his page, showing recently visited blog posts.

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Starship

Starship is a fast and minimal prompt for any shell that is highly customizable.

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Collective #547 was written by Pedro Botelho and published on Codrops.

Getting Started With ReGraph — The Graph Visualization Toolkit for React

At Cambridge Intelligence, we recently launched an Early Access Program (EAP) for ReGraph, our brand new graph data visualization toolkit for React developers. The response from evaluators has been fantastic, and now we’re inviting more organizations to join the ReGraph EAP.

To help you get started with ReGraph, this step-by-step tutorial covers everything you need to know. Once we’ve created our visualization in a React app, we’ll load an example network of suspected terrorists and show how easy it is to apply the key analysis techniques your users need to uncover threats.

Styling In Modern Web Apps

Styling In Modern Web Apps

Styling In Modern Web Apps

Ajay NS

If you search for how to style apps for the web, you’ll come across many different approaches and libraries, some even changing day by day. Block Element Modifier (BEM); preprocessors such as Less and SCSS; CSS-in-JS libraries, including JSS and styled-components; and, lately, design systems. You come across all of these in articles and blogs, tutorials and talks, and — of course — debates on Twitter.

How do we choose between them? Why do so many approaches exist in the first place? If you’re already comfortable with one method, why even consider moving to another?

In this article, I’m going to take a look at the tools I have used for production apps and sites I’ve worked on, comparing features from what I’ve actually encountered rather than summarizing the content from their readmes. This is my journey through BEM, SCSS, styled-components, and design systems in particular; but note that even if you use different libraries, the basic principles and approach remain the same for each of them.

CSS Back In The Day

When websites were just getting popular, CSS was primarily used to add funky designs to catch the user’s attention, such as neon billboards on a busy street:

Microsoft’s first site (left) and MTV’s site from the early 2000s. (Large preview)

Its use wasn’t for layout, sizing, or any of the basic needs we routinely use CSS for today, but as an optional add-on to make things fancy and eye-catching. As features were added to CSS, newer browsers supporting a whole new range of functionality and features appeared, and the standard for websites and user interfaces evolved — CSS became an essential part of web development.

It’s rare to find websites without a minimum of a couple hundred lines of custom styling or a CSS framework (at least, sites that don’t look generic or out of date):

Wired’s modern responsive site from InVision’s responsive web design examples post. (Large preview)

What came next is quite predictable. The complexity of user interfaces kept on increasing, along with the use of CSS; but without any guidelines suggested and with a lot of flexibility, styling became complicated and dirty. Developers had their own ways of doing things, with it all coming down to somehow getting things to look the way the design said it was supposed to be.

This, in turn, led to a number of common issues that many developers faced, like managing big teams on a project, or maintaining a project over a long period of time, while having no clear guides. One of the main reasons this happens even now, sadly, is that CSS is still often dismissed as unimportant and not worth paying much attention to.

CSS Is Not Easy To Manage

There’s nothing built into CSS for maintenance and management when it comes to large projects with teams, and so the common problems faced with CSS are:

  • Lack of code structure or standards greatly reduces readability;
  • Maintainability as project size increases;
  • Specificity issues due to code not being readable in the first place.

If you’ve worked with Bootstrap, you’ll have noticed you’re unable to override the default styles and you might have fixed this by adding !important or considering the specificity of selectors. Think of a big project’s style sheets, with their large number of classes and styles applied to each element. Working with Bootstrap would be fine because it has great documentation and it aims to be used as a solid framework for styling. This obviously won’t be the case for most internal style sheets, and you’ll be lost in a world of cascaded styles.

In projects, this would be like a couple thousand lines of CSS in a single file, with comments if you’re lucky. You could also see a couple of !important used to finally get certain styles to work overriding others.

!important does not fix bad CSS. (Large preview)

You may have faced specificity issues but not understood how specificity works. Let’s take a look.

(Large preview)

Which of the styles applied to the same element would be applied to the image on the right, assuming they both point to it?

What is the order of weight of selectors such as inline styles, IDs, classes, attributes, and elements? Okay, I made it easy there; they’re in order of weight:

Start at 0; add 1,000 for a style attribute; add 100 for each id; add 10 for each attribute, class or pseudo-class; add 1 for each element name or pseudo-element.

This is a simplified way of calculating and representing specificity which works in usual cases, but do note that the real representation would look like: (0,0,0,0). Here, the first number signifies the style attribute, second the ID, and so on. Each selector can actually have a value greater than 9 and it’s only when there is an equal number of selectors of highest weight that selectors of lower weight are considered.

So, for instance, taking the above example:

(Large preview)
(Large preview)

Do you see why the second example was the correct answer? The id selector clearly has far more weight than element selectors. This is essentially the reason why your CSS rule sometimes doesn’t seem to apply. You can read about this in detail in Vitaly Friedman’s article, “CSS Specificity: Things You Should Know”.

The larger the codebase, the greater the number of classes. These might even apply to or override different styles based on specificity, so you can see how quickly it can become difficult to deal with. Over and above this we deal with code structure and maintainability: it’s the same as the code in any language. We have atomic design, web components, templating engines; there’s a need for the same in CSS, and so we’ve got a couple of different approaches that attempt to solve these different problems.

Block Element Modifier (BEM)

“BEM is a design methodology that helps you to create reusable components and code sharing in front-end development.”

— getbem.com

The idea behind BEM is to create components out of parts of apps that are reused or are independent. Diving in, the design process is similar to atomic design: modularize things and think of each of them as a reusable component.

I chose to start out managing styles with BEM as it was very similar the way React (that I was already familiar with) breaks down apps into reusable components.

(Large preview)

Using BEM

BEM is nothing more than a guide: no new framework or language to learn, just CSS with a naming convention to organize things better. Following this methodology, you can implement the patterns you’ve already been using, but in a more structured manner. You can also quite easily do progressive enhancements to your existing codebase as it requires no additional tooling configuration or any other complexities.

Advantages

  • At its heart BEM manages reusable components, preventing random global styles overriding others. In the end, we have more predictable code, which solves a lot of our specificity problems.
  • There’s not much of a learning curve; it is just the same old CSS with a couple of guides to improve maintainability. It is an easy way of making code modular by using CSS itself.

Drawbacks

  • While promoting reusability and maintainability, a side effect of the BEM naming principle is making naming the classes difficult and time-consuming.
  • The more nested your component is in the block, the longer and more unreadable the class names become. Deeply nested or grandchild selectors often face this issue.
<div class="card__body">
  <p class="card__body__content">Lorem ipsum lorem</p>
  <div class="card__body__links">
    <!-- Grandchild elements -->
    <a href="#" class="card__body__links__link--active">Link</a>
  </div>
</div>

That was just a quick intro to BEM and how it solves our problems. If you’d like to take a deeper look into its implementation, check out “BEM For Beginners” published here in Smashing Magazine.

Sassy CSS (SCSS)

Put blandly, SCSS is CSS on steroids. Additional functionality such as variables, nesting selectors, reusable mixins, and imports help SCSS make CSS more of a programming language. For me, SCSS was fairly easy to pick up (go through the docs if you haven’t already) and once I got to grips with the additional features, I’d always prefer to use it over CSS just for the convenience it provided. SCSS is a preprocessor, meaning the compiled result is a plain old CSS file; the only thing you need to set up is tooling to compile down to CSS in the build process.

Super handy features

  • Imports help you split style sheets into multiple files for each component/section, or whichever makes readability easier.
// main.scss
@import "_variables.scss";
@import "_mixins.scss";

@import "_global.scss";
@import "_navbar.scss";
@import "_hero.scss";
  • Mixins, loops, and variables help with the DRY principle and also make the process of writing CSS easier.
@mixin flex-center($direction) {
  display: flex;
  align-items: center;
  justify-content: center;
  flex-direction: $direction;
}

.box {
  @include flex-center(row);
}

Note: SCSS mixin: Check out more handy SCSS features over here.

  • Nesting of selectors improves readability as it works the same way HTML elements are arranged: in a nested fashion. This approach helps you recognize hierarchy at a glance.

BEM With SCSS

It is possible to group the code for components into blocks, and this greatly improves readability and helps in ease of writing BEM with SCSS:

This code is relatively less heavy and complicated as opposed to nesting multiple layers. (Large preview)

Note: For further reading on how this would work, check out Victor Jeman’s “BEM with Sass” tutorial.

Styled-Components

This is one of the most widely used CSS-in-JS libraries. Without endorsing this particular library, it has worked well for me, and I’ve found its features quite useful for my requirements. Take your time in exploring other libraries out there and pick the one that best matches your needs.

I figured a good way to get to know styled-components was to compare the code to plain CSS. Here’s a quick look at how to use styled-components and what it’s all about:

Instead of adding classes to elements, each element with a class is made into a component. The code does look neater than the long class names we have with BEM.

Interestingly, what styled-components does under the hood is take up the job of adding relevant classes to elements as per what’s specified. This is essentially what we do in style sheets (note that it is in no way related to inline styling).

import styled from 'styled-components';
    
const Button = styled.button`
  background-color: palevioletred;
  color: papayawhip;
`;

// Output
<style>
  .dRUXBm {
    background-color: palevioletred;
    color: papayawhip;
  }
</style>

<button class="dRUXBm" />

Note: Styled-components under the hood: read more about inline styling vs CSS-in-JS in “Writing your styles in JS ≠ writing inline styles” by Max Stoiber.

Why Are Styled-Components One Of The Widely Used CSS-In-JS Libraries?

For styling, here we’re just using template literals with normal CSS syntax. This allows you to use the full power of JavaScript to handle the styling for you: conditionals, properties passed in as arguments (using an approach similar to React), and essentially all the functionality that can be implemented by JavaScript.

While SCSS has variables, mixins, nesting, and other features, styled-components only adds on, making it even more powerful. Its approach, based heavily on components, might seem daunting at first since it’s different from traditional CSS. But as you get used to the principles and techniques, you’ll notice that everything possible with SCSS can be done in styled-components, as well as a lot more. You just use JavaScript instead.

const getDimensions = size => {
  switch(size) {
    case 'small': return 32;
    case 'large': return 64;
    default: return 48;
  }
}

const Avatar = styled.img`
  border-radius: 50%;
  width: ${props => getDimensions(props.size)}px;
  height: ${props => getDimensions(props.size)}px;
`;

const AvatarComponent = ({ src }) => (
  <Avatar src={src} size="large" />
);

Note: Template literals in styled-components allow you to use JS directly for conditional styling and more.

Another thing to note is how perfectly this fits into the world of web components. A React component has its own functionality with JavaScript, JSX template, and now CSS-in-JS for styling: it’s fully functional all by itself and handles everything required internally.

Without us realizing, that was the answer to a problem we’ve been talking about for too long: specificity. While BEM was a guideline to enforce component-based structure for elements and styles but still relying on classes, styled-components impose it for you.

Styled-components has a couple of additional features I’ve found especially useful: themes, which can configure a global prop (variable) passed down to each styled-component; automatic vendor prefixing; and automatic clean-up of unused code. The amazingly supportive and active community is just the icing on the cake.

Note: There’s a lot more to check out and take advantage of. Read more in the styled-components docs.

Quick Recap On Features
  • Template literals are used for syntax, the same as traditional CSS.
  • It imposes modular design.
  • It solves specificity issues by handling class names for you.
  • Everything that can be done with SCSS and more, implemented with JS.
Why It Might Not Be For You
  • It obviously relies on JavaScript, which means without it the styles don’t load, resulting in a cluttered mess.
  • Previously readable class names are replaced with hashes that really have no meaning.
  • The concept of components rather than cascading classes might be a bit hard to wrap your head around, especially since this affects the way you arrange things a lot.

Design Systems

As usage of web components increases, as well as the need for atomic design (basically breaking down UI into basic building blocks), many companies are choosing to create component libraries and design systems. Unlike the technologies or approaches on how to handle styling mentioned above, design systems represent an organizational approach to handling components and consistent design across whole platforms or apps.

It’s possible to use an approach we’ve discussed within a design system to organize styles, while the design system itself focuses on the building blocks of the apps rather than internal implementations.

“Design systems are essentially collections of rules, constraints, and principles implemented in design and code.”

Design systems and component libraries are aimed at whole ecosystems spanning different platforms and media, and can determine the overall outlook of the company itself.

“A design system is an amalgamation of style, components, and voice.”
IBM’s Carbon design system
IBM’s Carbon design system (Large preview)

Once they gain momentum, tech businesses sometimes have to scale up extremely fast, and it can be hard for the design and development teams to keep up. Different apps, new features and flows, constant reevaluation, changes, and enhancements are to be shipped as rapidly as possible when the business requires them.

Take the case of a simple modal; for instance, one screen has a confirmation modal which simply accepts a negative or positive action. This is worked on by Developer A. Then the design team ships another screen that has a modal comprising a small form with a few inputs — Developer B takes this up. Developers A and B work separately and have no idea that both of them are working on the same pattern, building two different components that are essentially the same at base level. If different developers worked on the different screens we might even see UI inconsistencies committed to the codebase.

Now imagine a large company of multiple designers and developers — you could end up with a whole collection of components and flows that are supposed to be consistent, but instead are distinct components existing independently.

The main principle of design systems is to help meet business requirements: build and ship new features, functionality, and even full apps while maintaining standards, quality, and consistency of design.

Here are some examples of popular design systems:

When talking about styling in particular, we’d be specifically interested in the component library part, although the design system itself is far more than just a collection of components. A component handles its functionality, template, and styling internally. A developer working on the app needn’t be aware of all of the internal working of the components, but would just need to know how to put them together within the app.

Now imagine a couple of these components that are further made reusable and maintainable, and then organized into a library. Developing apps could be almost as simple as drag-and-drop (well, not exactly, but a component could be pulled in without worrying about any internal aspects of its working). That’s essentially what a component library does.

(Large preview)
(Large preview)

Why You Might Want To Think About Building A Design System

  • As mentioned earlier, it helps the engineering and design teams keep up with rapidly changing business needs while maintaining standards and quality.
  • It ensures consistency of design and code throughout, helping considerably with maintainability over a long period of time.
  • One of the greatest features of design systems is that they bring the design and development teams closer, making work more of a continuous collaboration. Rather than whole pages of mock-ups given to developers to work on from scratch, components and their behaviors are well-defined first. It’s a whole different approach, but a better and faster way to develop consistent interfaces.

Why It Might Not Be The Best Fit For You

  • Design systems require a lot of time and effort up front to plan things out and organize from scratch — both code- and design-wise. Unless really required, it might not be worth delaying the development process to focus on building the design system at first.
  • If a project is relatively small, a design system can add unnecessary complexity and end up a waste of effort when what was actually required was just a couple of standards or guidelines to ensure consistency. Because several high-profile companies have adopted design systems, the hype can influence developers into thinking this is the always best approach, without analyzing the requirements and ensuring this could actually be practical.
Different appearances of a button
Different appearances of a button (Large preview)

Conclusion

Styling applications is a world in itself, one not often given the importance and attention it deserves. With complex modern user interfaces, it’s only matter of time before your app becomes a mess of unordered styles, reducing consistency and making it harder for new code to be added or changes made to the existing codebase.

Distilling what we’ve discussed so far: BEM, along with SCSS, could help you organize your style sheets better, take a programming approach to CSS, and create meaningful structured class names for cleaner code with minimal configuration. Building over a front-end framework like React or Vue, you might it find it convenient to hand class naming to a CSS-in-JS library if you’re comfortable with a component-based approach, putting an end to all your specificity issues, along with a couple of other benefits. For larger applications and multiple platforms, you might even consider building a design system in combination with one of the other methods, to boost development speeds while maintaining consistency.

Essentially, depending on your requirements and the size and scale of your software, it’s important to spend time determining your best approach to styling.

Smashing Editorial (dm, og, yk, il)

Front-End Documentation, Style Guides and the Rise of MDX

You can have the best open source project in the world but, if it doesn’t have good documentation, chances are it’ll never take off. In the office, good documentation could save you having to repeatedly answer the same questions. Documentation ensures that people can figure out how things work if key employees decide to leave the company or change roles. Well documented coding guidelines help bring consistency to a codebase.

If you’re writing long-form text, Markdown is clearly a great alternative to authoring HTML. Sometimes though, Markdown syntax isn’t enough. It’s always been possible to write straight HTML inside of Markdown documents. This includes custom elements so, if you’re building a design system with native web components, it’s easy to incorporate them inside your text-based documentation. If you’re working with React (or any other framework that speaks JSX, like Preact or Vue), you can do the same thing by using MDX.

This article is a broad overview of the tools available for writing documentation and for building style guides. Not all the tools listed here make use of MDX but it’s increasingly being incorporated into documentation tooling.

What is MDX?

A .mdx file has exactly the same syntax as a regular Markdown file, but lets you import interactive JSX components and embed them within your content. Support for Vue components is in alpha. It’s easy to get MDX set up with Create React App. There are MDX plugins for Next.js and Gatsby. The forthcoming version two release of Docusaurus will also come with built-in support.

Writing documentation with Docusaurus

Docusaurus is made by Facebook and used by every Facebook open source project, apart from React. It’s also used by many major open source projects outside of Facebook, including Redux, Prettier, Gulp and Babel.

A screenshot of logos of all the various frameworks that support Docusaurus, including React, Gulp, Jest, Babel, Redux and Prettier.
Projects making use of Docusaurus.

You can use Docusaurus to document anything — it isn’t front-end specific. Docusaurus uses React under the hood, but you don’t have to know that framework to make use of it. It’ll take your Markdown files and turn them into a nicely-structured, well-formatted and readable documentation site, with a nice design right out of the box.

A screenshot of the Redux documentation homepage with the headline Getting Started with Redux.
The Redux site shows the typical Docusaurus layout

Sites created with Docusaurus can also include a Markdown-based blog. Prism.js is included by default for zero-setup syntax highlighting. While relatively new, Docusaurus has proven popular, being voted the number one new tool of 2018 on StackShare.

Other options for written content

Docusaurus specifically caters to building documentation. Of course, there are a million and one ways to make a website — so you could roll your own solution with any back-end language, CMS, or static site generator.

The documentation sites for React, IBM’s design system, Apollo and Ghost CMS use Gatsby, for example — a generic static site generator often used for blogs. If you work with the Vue framework, VuePress is becoming a popular option. MkDocs is an open source static site generator for creating documentation, written in Python and configured with a single YAML file. GitBook is a popular paid product that’s free for open-source and non-profit teams. If you're building internal documentation and want something easy, the reading experience on GitHub itself isn’t half bad, so you could just commit some Markdown files and leave it at that.

Documenting components: Docz, Storybook and Styleguidist

Style guides, design systems, pattern libraries — whatever you want to call them — have become a hugely popular area of concern in the last decade. What’s really made the difference in turning them from vanity projects into useful tools isn’t the pontificating of thought leaders but the emergence of component-driven frameworks, like React, and the tools mentioned here.

Storybook, Docz and Styleguidist all do much the same thing: display interactive UI components and document their API. A project may have dozens or even hundreds of components to keep track of — all with a variety to states and styles. If you want components to be reused, people have to know that they exist. We aid discoverability when we catalog components. A style guide gives an easily searchable and scannable overview of all your UI components. This helps to maintain visual consistency and avoid duplicating work.

These tools provide a convenient way to review different states. It can be difficult to reproduce every state of a component in the context of a real application. Rather than needing to click through an actual app, developing a component in isolation can be helpful. Hard-to-reach states (like a loading state, for example) can be mocked.

Dan Green wrote a nice synopsis of the benefits of using Storybook, but it applies equally to Docz and Styleguidist:

"Storybook has made it really easy for designers who code to collaborate with engineers. By working in storybook they don't need to get a whole environment running (docker container, etc). For Wave, we have many important components that are only visible in the middle of a process that is short lived and time consuming to reproduce (i.e. a loading screen that only shows while a user is having their payment account set up). Before Storybook, we didn't have a good way to work on these components and were forced to temporary hacks in order to make them visible. Now, with Storybook we have an isolated place to easily work on them, which has the bonus feature of being easily accessible for designers and PMs. It also makes it really easy for us to show off these states in sprint demos."

- Dan Green, Wave Financial

As well as visualizing different states side-by-side and listing props, its often helpful to have written content about a component — whether its explaining the design rationale, use-cases, or describing the results of user-testing. Markdown is easy enough for *anybody* to learn — ideally a style guide should be a joint resource for designers and developers that both disciplines contribute to. Docz, Styleguidist and Storybook all offer a way to seamlessly intermingle Markdown with the components themselves.

Docz

Currently, Docz is a React-only project, but is working on support for Preact, Vue and web components. Docz is the newest of the three tools, but has already amounted over 14,000+ stars on GitHub. It is, to my mind, the easiest solution to work with. Docz provides two components — <Playground> and <Props>. These are imported and used directly in .mdx files.

import { Playground, Props } from "docz";
import Button from "../src/Button";

## You can _write_ **markdown**
### You can import and use components

<Button>click</Button>

You can wrap your own React components with <Playground> to create the equivalent of an embedded CodePen or CodeSandbox — a view of your component alongside editable code.

<Playground>
  <Button>click</Button>
</Playground>

<Props> will show all the available props for a given React component, default values, and whether the prop is required.

<Props of={Button} />

I personally find this MDX-based approach the simplest to understand and the easiest to work with.

A screenshot of a Code Sandbox project making use of the tool to document the code for a Button component.

If you’re a fan of the React-based static-site generator Gatsby, Docz offers great integration.

Styleguidist

Just like with Docz, examples are written using Markdown syntax. Styleguidist uses Markdown code blocks (triple backticks) in regular .md files rather than MDX:

```js
<Button onClick={() => console.log('clicked')>Push Me</Button>
```

Code blocks in Markdown usually just show the code. With Styleguidist, any code block with a language tag of js, jsx or javascript will be rendered as a React component along with the code. Just like with Docz, the code is editable — you can change props and instantly see the result.

A screenshot of the output of the documentation for a pink button made with Styleguidist.

Styleguidist will automatically create a table of props from either PropTypes, Flow or Typescript declarations.

A screenshot of a table of values that Styleguidiist generated for the pink button documentation, including values it accepts.

Styleguidist currently supports React and Vue.

Storybook

Storybook markets itself as "a development environment for UI components." Rather than writing examples of components inside Markdown or MDX files, you write *stories* inside Javascript files. A *story* documents a particular state of a component. A component might have stories for a loading state and a disabled state, for example.

storiesOf('Button', module)
  .add('disabled', () => (
    <Button disabled>lorem ipsum</Button>
  ))

Storybook is less straightforward to use than Styleguidist and Docz. At over 36,000 GitHub stars though, it’s the most popular option. It’s an open source project with 657 contributors and a full-time maintainer. It is used by, among others, Airbnb, Algolia, Atlassian, Lyft, and Salesforce. Storybook supports more frameworks than any other offering — React, React Native, Vue, Angular, Mithril, Ember, Riot, Svelte and plain HTML are all supported.

Writing documentation about components currently requires addons. In a future release, Storybook is taking inspiration from Docz and adopting MDX.

# Button

Some _notes_ about your button written with **markdown syntax**.

<Story name="disabled">
  <Button disabled>lorem ipsum</Button>
</Story>

Storybook’s new Docs feature is being rolled out incrementally over the next couple of months and looks set to be a big step forward.

Wrapping up

The benefits of pattern libraries have been extolled at nauseating length in a million Medium articles. When done well, they aid visual consistency and facilitate the creation of cohesive products. Of course, none of these tools can magic up a design system. That takes careful thought about both design and CSS. But when it comes time to communicate that system to the rest of an organization, Docz, Storybook and Styleguidist are all great options.

The post Front-End Documentation, Style Guides and the Rise of MDX appeared first on CSS-Tricks.

Make it hard to screw up driven development

Development is complicated. Our job is an ongoing battle between getting the job done and doing that job in a safe, long-lasting way.

Developers say things like, "I'm just going to do this quick and dirty first," because it's taken as fact that if you code anything quickly, it not only will be prone to mistakes, but that you'll be deliberately not honoring established conventions and skipping tasks that make for more solid code.

There is probably no practical way to make it impossible to write sloppy, bad code, but it is fascinating to consider how tooling has evolved to make it harder.

Let's get all Poka-yoke on development.

The obvious ones are automated code quality tools.

Say you're writing JavaScript. ESLint is a mega-popular tool that looks at your code as you are writing it and lets you know about issues.

ESLint is configurable and those configurations can be enforced to a team's liking. If you'd prefer to use some strong and established conventions, I believe the most popular out there is AirBnbs configuration.

There are alternatives to everything, of course. This post isn't so much about a comprehensive tooling list as it is about considering the types of tools that help us push us toward writing better code. That said, stylelint is good for CSS, PHP_CodeSniffer is good for PHP, and Rubocop is good for Ruby.

Prettier is in a similar, but unique category. It is like a "beautifier" for your code, in that it helps you reformat it not only to look good but to follow team conventions (e.g. single quotes! Two space indentions!) as well. The most common way to use Prettier is that it runs as you save the file. So perhaps you write quickly and don't worry about formatting as much, because it happens for you the second you save. There is an interesting side-benefit of quality here as Prettier can fail, and if it does, you have a problem in the syntax of your code you need to fix. Super useful.

Prettier failing.

I'm intrigued by tools like Sonarlint, Code Climate, and Resharper that look, to me, essentially like linters, but deliver only a best-practice analysis rather than configuring things yourself. It also claims to understand your code at a deeper level. Webhint and Deepscan look similarly interesting. Feel free to correct me if I have this wrong because I haven't gotten a chance to use any of them yet.

Taking linting a step further, you can make passing lint tests a requirement before files can even be committed into Git. Git hooks are the ticket here, and the most popular tool for managing them is Husky.

Similarly, actual tests are powerful preventers of bad code.

It's always smart to write tests. Deploying code that breaks features is embarrassing, a waste of time, and can negatively impact your business. Yet we do it all too often. The whole point of tests is to prevent that.

Things like Jest for JavaScript and RSpec for Ruby are useful, and considered unit testing. It's work! You manually write functions that expect certain results. I expect that if I call a function with these parameters it returns this value!

Test-Driven Development (TDD) is a practice in which you write the test before you write the actual code that does the thing you're trying to do. It's a nice way to work if you can pull it off, as you've got code coverage from the get-go.

Another type of automated testing is integration (also known as end-to-end) testing. I'm a fan of Cypress for that. It simulates a user actually using a browser. Go to this URL! Click this! Fill out this field and submit the form! Does this thing exist now? Is the URL what it's supposed to be? Is this other thing visible? That kind of testing is powerful in that a lot of things have to be going right for these to pass, so there is a ton of implied testing.

As a CSS kinda guy, I'm also a fan of tests that watch to make sure the site looks how it's supposed to look and there aren't unintended consequences of styling changings. Percy is awesome for that (see our video).

And while we're talking about all the different types of automated testing you can do, there are all sorts of tools to automate some level of accessibiilty testing. Plus, there are tools like Calibre and SpeedCurve that automate Lighthouse for watching performance.

Languages and language features that help us, wittingly or not

Take JSX, for example. It's entirely possible to write bad HTML in JSX, but you can't write broken HTML. The component will error out entirely and you'll know as you're working. That's not even close to the reason JSX exists, but I find it an interesting side effect. I've fixed many bugs in my career that had to do with malformed HTML causing problems, ranging from tiny side effects to massive layout blunders.

Prettier is catching the problem here, but we'd see an error in the console if this compiled and went to the browser.

Similarly, a tool like Emmet can help generate valid HTML. I use Emmet all the time, and didn't even think of that until it was mentioned to me.

I also think of React features, like PropTypes, that throw errors when missing or unexpected data is thrown at them. Not to mention you can configure your linter to yell at you if you're missing the PropType. That's pretty powerful testing to be enforced for a fairly small amount of labor (compared to, say, writing a test). You can even force them to help with accessibility.

It would be impossible to not mention TypeScript here. One of the major points of using TypeScript is code safety. The fact that it's getting huge (listen to Laurie Voss on this) points to the fact that we want to enforce that safety. I remember when Angular 2 came out, there were long, solid explanations as to why. People also talk about the tooling improvements you get with TypeScript: advanced autocompletion, navigation, and refactoring. They are all, in a way, also about code safety — having the editor help you write correct file names and function names. TypeScript or not, any sort of autocomplete/IntelliSense is great to have.

The whole idea of this post came from me thinking about how GraphQL has this "you can't screw it up" quality to it. You can't ask for data that isn't there, as it will error right as you're working with it — and then you'll fix it. And you can't get back data that you aren't expecting, as you've described exactly what you want back and that's what GraphQL does. It's not that you can't write bad code that uses GraphQL or write a bad GraphQL implementation, but the technology sort of encourages better code and I'm fascinated by that.

CSS-in-JS, while that's probably too broad a term generally, applies to this discussion. Most of the solutions on that spectrum involve some kind of style scoping, and style scoping provides this "you can't screw it up" topic we're focusing on. You can't cause unintended side effects when the selector you've just written compiles to something you've never hand-written, like .SpecificComponent_root_34lkj4x.

Your co-workers are an awesome line of defense

First, give y'allselves a system. Nothing goes to the master branch directly, and everything has to be a Merge/Pull Request. That gives you a spot to talk about code quality — not to mention a place where you can run a suite of automated tests before the code is dangerously close to production.

GitLab has a concept of approvers for a Merge Request. You pick some people that have to approve the branch before it can be merged.

GitHub has the same concept with protected branches. Perhaps the best thing you can do to prevent bad code is to widen the responsibility. There is always a risk this just becomes a glance-at-the-code-for-two-seconds-and-give-it-a-👍 motion, but that's on y'all to make sure reviews are taken seriously. I've seen lots of value in a requirement that many sets of eyeballs need to be on code before it goes out. "Given enough eyeballs, all bugs are shallow" and all that.


We'll always be screwing up code, but we can also always be finding ways not to.

The post Make it hard to screw up driven development appeared first on CSS-Tricks.

Get Started With Node: An Introduction To APIs, HTTP And ES6+ JavaScript

Get Started With Node: An Introduction To APIs, HTTP And ES6+ JavaScript

Get Started With Node: An Introduction To APIs, HTTP And ES6+ JavaScript

Jamie Corkhill

You’ve probably heard of Node.js as being an “asynchronous JavaScript runtime built on Chrome’s V8 JavaScript engine”, and that it “uses an event-driven, non-blocking I/O model that makes it lightweight and efficient”. But for some, that is not the greatest of explanations.

What is Node in the first place? What exactly does it mean for Node to be “asynchronous”, and how does that differ from “synchronous”? What is the meaning “event-driven” and “non-blocking” anyway, and how does Node fit into the bigger picture of applications, Internet networks, and servers?

We’ll attempt to answer all of these questions and more throughout this series as we take an in-depth look at the inner workings of Node, learn about the HyperText Transfer Protocol, APIs, and JSON, and build our very own Bookshelf API utilizing MongoDB, Express, Lodash, Mocha, and Handlebars.

What Is Node.js

Node is only an environment, or runtime, within which to run normal JavaScript (with minor differences) outside of the browser. We can use it to build desktop applications (with frameworks like Electron), write web or app servers, and more.

Blocking/Non-Blocking And Synchronous/Asynchronous

Suppose we are making a database call to retrieve properties about a user. That call is going to take time, and if the request is “blocking”, then that means it will block the execution of our program until the call is complete. In this case, we made a “synchronous” request since it ended up blocking the thread.

So, a synchronous operation blocks a process or thread until that operation is complete, leaving the thread in a “wait state”. An asynchronous operation, on the other hand, is non-blocking. It permits execution of the thread to proceed regardless of the time it takes for the operation to complete or the result it completes with, and no part of the thread falls into a wait state at any point.

Let’s look at another example of a synchronous call that blocks a thread. Suppose we are building an application that compares the results of two Weather APIs to find their percent difference in temperature. In a blocking manner, we make a call to Weather API One and wait for the result. Once we get a result, we call Weather API Two and wait for its result. Don’t worry at this point if you are not familiar with APIs. We’ll be covering them in an upcoming section. For now, just think of an API as the medium through which two computers may communicate with one another.

A graphic depicting the fact Synchronous Operations take a long time complete
Time progression of synchronous blocking operations (Large preview)

Allow me to note, it’s important to recognize that not all synchronous calls are necessarily blocking. If a synchronous operation can manage to complete without blocking the thread or causing a wait state, it was non-blocking. Most of the time, synchronous calls will be blocking, and the time they take to complete will depend on a variety of factors, such as the speed of the API’s servers, the end user’s internet connection download speed, etc.

In the case of the image above, we had to wait quite a while to retrieve the first results from API One. Thereafter, we had to wait equally as long to get a response from API Two. While waiting for both responses, the user would notice our application hang — the UI would literally lock up — and that would be bad for User Experience.

In the case of a non-blocking call, we’d have something like this:

A graphic depicting the fact that Asynchronous Non-Blocking Operations are almost 50 percent faster
Time progression of asynchronous non-blocking operations (Large preview)

You can clearly see how much faster we concluded execution. Rather than wait on API One and then wait on API Two, we could wait for both of them to complete at the same time and achieve our results almost 50% faster. Notice, once we called API One and started waiting for its response, we also called API Two and began waiting for its response at the same time as One.

At this point, before moving into more concrete and tangible examples, it is important to mention that, for ease, the term “Synchronous” is generally shortened to “Sync”, and the term “Asynchronous” is generally shortened to “Async”. You will see this notation used in method/function names.

Callback Functions

You might be wondering, “if we can handle a call asynchronously, how do we know when that call is finished and we have a response?” Generally, we pass in as an argument to our async method a callback function, and that method will “call back” that function at a later time with a response. I’m using ES5 functions here, but we’ll update to ES6 standards later.

function asyncAddFunction(a, b, callback) {
  callback(a + b); //This callback is the one passed in to the function call below.
}

asyncAddFunction(2, 4, function(sum) {
  //Here we have the sum, 2 + 4 = 6.
});

Such a function is called a “Higher-Order Function” since it takes a function (our callback) as an argument. Alternatively, a callback function might take in an error object and a response object as arguments, and present them when the async function is complete. We’ll see this later with Express. When we called asyncAddFunction(...), you’ll notice we supplied a callback function for the callback parameter from the method definition. This function is an anonymous function (it does not have a name) and is written using the Expression Syntax. The method definition, on the other hand, is a function statement. It’s not anonymous because it actually has a name (that being “asyncAddFunction”).

Some may note confusion since, in the method definition, we do supply a name, that being “callback”. However, the anonymous function passed in as the third parameter to asyncAddFunction(...) does not know about the name, and so it remains anonymous. We also can’t execute that function at a later point by name, we’d have to go through the async calling function again to fire it.

As an example of a synchronous call, we can use the Node.js readFileSync(...) method. Again, we’ll be moving to ES6+ later.

var fs = require('fs');
var data = fs.readFileSync('/example.txt'); // The thread will be blocked here until complete.

If we were doing this asynchronously, we’d pass in a callback function which would fire when the async operation was complete.

var fs = require('fs');
var data = fs.readFile('/example.txt', function(err, data) { //Move on, this will fire when ready.
  if(err) return console.log('Error: ', err);
  console.log('Data: ', data); // Assume var data is defined above.
});
// Keep executing below, don’t wait on the data.

If you have never seen return used in that manner before, we are just saying to stop function execution so we don’t print the data object if the error object is defined. We could also have just wrapped the log statement in an else clause.

Like our asyncAddFunction(...), the code behind the fs.readFile(...) function would be something along the lines of:

function readFile(path, callback) {
 // Behind the scenes code to read a file stream.
 // The data variable is defined up here.
 callback(undefined, data); //Or, callback(err, undefined);
}

Allow us to look at one last implementation of an async function call. This will help to solidify the idea of callback functions being fired at a later point in time, and it will help us to understand the execution of a typical Node.js program.

setTimeout(function {
  // ...
}, 1000);

The setTimeout(...) method takes a callback function for the first parameter which will be fired after the number of milliseconds specified as the second argument has occurred.

Let’s look at a more complex example:

console.log('Initiated program.');

setTimeout(function {
  console.log('3000 ms (3 sec) have passed.');
}, 3000);

setTimeout(function {
  console.log('0 ms (0 sec) have passed.');
}, 0);

setTimeout(function {
  console.log('1000 ms (1 sec) has passed.');
}, 1000);

console.log('Terminated program');

The output we receive is:

Initiated program.
Terminated program.
0 ms (0 sec) have passed.
1000 ms (1 sec) has passed.
3000 ms (3 sec) have passed.

You can see that the first log statement runs as expected. Instantaneously, the last log statement prints to the screen, for that happens before 0 seconds have surpassed after the second setTimeout(...). Immediately thereafter, the second, third, and first setTimeout(...) methods execute.

If Node.js was not non-blocking, we’d see the first log statement, wait 3 seconds to see the next, instantaneously see the third (the 0-second setTimeout(...), and then have to wait one more second to see the last two log statements. The non-blocking nature of Node makes all timers start counting down from the moment the program is executed, rather than the order in which they are typed. You may want to look into Node APIs, the Callstack, and the Event Loop for more information about how Node works under the hood.

It is important to note that just because you see a callback function does not necessarily mean there is an asynchronous call in the code. We called the asyncAddFunction(…) method above “async” because we are assuming the operation takes time to complete — such as making a call to a server. In reality, the process of adding two numbers is not async, and so that would actually be an example of using a callback function in a fashion that does not actually block the thread.

Promises Over Callbacks

Callbacks can quickly become messy in JavaScript, especially multiple nested callbacks. We are familiar with passing a callback as an argument to a function, but Promises allow us to tack, or attach, a callback to an object returned from a function. This would allow us to handle multiple async calls in a more elegant manner.

As an example, suppose we are making an API call, and our function, not so uniquely named ‘makeAPICall(...)’, takes a URL and a callback.

Our function, makeAPICall(...), would be defined as

function makeAPICall(path, callback) {
  // Attempt to make API call to path argument.
  // ...
  callback(undefined, res); // Or, callback(err, undefined); depending upon the API’s response.
}

and we would call it with:

makeAPICall('/example', function(err1, res1) {
  if(err1) return console.log('Error: ', err1);
  // ...
});

If we wanted to make another API call using the response from the first, we would have to nest both callbacks. Suppose I need to inject the userName property from the res1 object into the path of the second API call. We would have:

makeAPICall('/example', function(err1, res1) {
  if(err1) return console.log('Error: ', err1);
  makeAPICall('/newExample/' + res1.userName, function(err2, res2) {
    if(err2) return console.log('Error: ', err2);
    console.log(res2);
  });
});

Note: The ES6+ method to inject the res1.userName property rather than string concatenation would be to use “Template Strings”. That way, rather than encapsulate our string in quotes (‘, or “), we would use backticks (\), located beneath the Escape key on your keyboard. Then, we would use the notation ${} to embed any JS expression inside the brackets. In the end, our earlier path would be: /newExample/${res.UserName}, wrapped in backticks.

It is clear to see that this method of nesting callbacks can quickly become quite inelegant, so-called the “JavaScript Pyramid of Doom”. Jumping in, if we were using promises rather than callbacks, we could refactor our code from the first example as such:

makeAPICall('/example').then(function(res) { // Success callback.
  // ...
}, function(err) { // Failure callback.
  console.log('Error:', err);
});

The first argument to the then() function is our success callback, and the second argument is our failure callback. Alternatively, we could lose the second argument to .then(), and call .catch() instead. Arguments to .then() are optional, and calling .catch() would be equivalent to .then(successCallback, null).

Using .catch(), we have:

makeAPICall('/example').then(function(res) { // Success callback.
  // ...
}).catch(function(err) {  // Failure Callback
  console.log('Error: ', err);
});

We can also restructure this for readability:

makeAPICall('/example')
  .then(function(res) {
    // ...
  })
  .catch(function(err) {
    console.log('Error: ', err);
  });

It is important to note that we can’t just tack a .then() call on to any function and expect it to work. The function we are calling has to actually return a promise, a promise that will fire the .then() when that async operation is complete. In this case, makeAPICall(...) will do it’s thing, firing either the then() block or the catch() block when completed.

To make makeAPICall(...) return a Promise, we assign a function to a variable, where that function is the Promise constructor. Promises can be either fulfilled or rejected, where fulfilled means that the action relating to the promise completed successfully, and rejected meaning the opposite. Once the promise is either fulfilled or rejected, we say it has settled, and while waiting for it to settle, perhaps during an async call, we say that the promise is pending.

The Promise constructor takes in one callback function as an argument, which receives two parameters — resolve and reject, which we will call at a later point in time to fire either the success callback in .then(), or the .then() failure callback, or .catch(), if provided.

Here is an example of what this looks like:

var examplePromise = new Promise(function(resolve, reject) {
  // Do whatever we are going to do and then make the appropiate call below:
  resolve('Happy!'); // — Everything worked.
  reject('Sad!'); // — We noticed that something went wrong.
}):

Then, we can use:

examplePromise.then(/* Both callback functions in here */);
// Or, the success callback in .then() and the failure callback in .catch().

Notice, however, that examplePromise can’t take any arguments. That kind of defeats the purpose, so we can return a promise instead.

function makeAPICall(path) {
  return new Promise(function(resolve, reject) {
    // Make our async API call here.
    if (/* All is good */) return resolve(res); //res is the response, would be defined above.
    else return reject(err); //err is error, would be defined above.
  });
}

Promises really shine to improve the structure, and subsequently, elegance, of our code with the concept of “Promise Chaining”. This would allow us to return a new Promise inside a .then() clause, so we could attach a second .then() thereafter, which would fire the appropriate callback from the second promise.

Refactoring our multi API URL call above with Promises, we get:

makeAPICall('/example').then(function(res) { // First response callback. Fires on success to '/example' call.
  return makeAPICall(`/newExample/${res.UserName}`); // Returning new call allows for Promise Chaining.
}, function(err) { // First failure callback. Fires if there is a failure calling with '/example'.
  console.log('Error:', err);
}).then(function(res) { // Second response callback. Fires on success to returned '/newExample/...' call.
  console.log(res);
}, function(err) { // Second failure callback. Fire if there is a failure calling with '/newExample/...'
  console.log('Error:', err);
});

Notice that we first call makeAPICall('/example'). That returns a promise, and so we attach a .then(). Inside that then(), we return a new call to makeAPICall(...), which, in and of itself, as seen earlier, returns a promise, permitting us chain on a new .then() after the first.

Like above, we can restructure this for readability, and remove the failure callbacks for a generic catch() all clause. Then, we can follow the DRY Principle (Don’t Repeat Yourself), and only have to implement error handling once.

makeAPICall('/example')
  .then(function(res) { // Like earlier, fires with success and response from '/example'.
    return makeAPICall(`/newExample/${res.UserName}`); // Returning here lets us chain on a new .then().
   })
  .then(function(res) { // Like earlier, fires with success and response from '/newExample'.
    console.log(res);
   })
  .catch(function(err) { // Generic catch all method. Fires if there is an err with either earlier call.
    console.log('Error: ', err);
   });

Note that the success and failure callbacks in .then() only fire for the status of the individual Promise that .then() corresponds to. The catch block, however, will catch any errors that fire in any of the .then()s.

ES6 Const vs. Let

Throughout all of our examples, we have been employing ES5 functions and the old var keyword. While millions of lines of code still run today employing those ES5 methods, it is useful to update to current ES6+ standards, and we’ll refactor some of our code above. Let’s start with const and let.

You might be used to declaring a variable with the var keyword:

var pi = 3.14;

With ES6+ standards, we could make that either

let pi = 3.14;

or

const pi = 3.14;

where const means “constant” — a value that cannot be reassigned to later. (Except for object properties — we’ll cover that soon. Also, variables declared const are not immutable, only the reference to the variable is.)

In old JavaScript, block scopes, such as those in if, while, {}. for, etc. did not affect var in any way, and this is quite different to more statically typed languages like Java or C++. That is, the scope of var is the entire enclosing function — and that could be global (if placed outside a function), or local (if placed within a function). To demonstrate this, see the following example:

function myFunction() {
  var num = 5;
  console.log(num); // 5
  console.log('--');
  for(var i = 0; i < 10; i++)
  {
    var num = i;
    console.log(num); //num becomes 0 — 9
  }
  console.log('--');
  console.log(num); // 9
  console.log(i); // 10
}

myFunction();

Output:

5
---
0
1 2 3 ... 7 8 9
---
9
10

The important thing to notice here is that defining a new var num inside the for scope directly affected the var num outside and above the for. This is because var’s scope is always that of the enclosing function, and not a block.

Again, by default, var i inside for() defaults to myFunction’s scope, and so we can access i outside the loop and get 10.

In terms of assigning values to variables, let is equivalent to var, it’s just that let has block scoping, and so the anomalies that occurred with var above will not happen.

function myFunction() {
  let num = 5;
  console.log(num); // 5
  for(let i = 0; i < 10; i++)
  {
    let num = i;
    console.log('--');
    console.log(num); // num becomes 0 — 9
  }
  console.log('--');
  console.log(num); // 5
  console.log(i); // undefined, ReferenceError
}

Looking at the const keyword, you can see that we attain an error if we try to reassign to it:

const c = 299792458; // Fact: The constant "c" is the speed of light in a vacuum in meters per second.
c = 10; // TypeError: Assignment to constant variable.

Things become interesting when we assign a const variable to an object:

const myObject = {
  name: 'Jane Doe'
};

// This is illegal: TypeError: Assignment to constant variable.
myObject = {
  name: 'John Doe'
};

// This is legal. console.log(myObject.name) -> John Doe
myObject.name = 'John Doe';

As you can see, only the reference in memory to the object assigned to a const object is immutable, not the value its self.

ES6 Arrow Functions

You might be used to creating a function like this:

function printHelloWorld() {
  console.log('Hello, World!');
}

With arrow functions, that would become:

const printHelloWorld = () => {
  console.log('Hello, World!');
};

Suppose we have a simple function that returns the square of a number:

const squareNumber = (x) => {
  return x * x;
}

squareNumber(5); // We can call an arrow function like an ES5 functions. Returns 25.

You can see that, just like with ES5 functions, we can take in arguments with parentheses, we can use normal return statements, and we can call the function just like any other.

It’s important to note that, while parentheses are required if our function takes no arguments (like with printHelloWorld() above), we can drop the parentheses if it only takes one, so our earlier squareNumber() method definition can be rewritten as:

const squareNumber = x => { // Notice we have dropped the parentheses for we only take in one argument.
  return x * x;
}

Whether you choose to encapsulate a single argument in parentheses or not is a matter of personal taste, and you will likely see developers use both methods.

Finally, if we only want to implicitly return one expression, as with squareNumber(...) above, we can put the return statement in line with the method signature:

const squareNumber = x => x * x;

That is,

const test = (a, b, c) => expression

is the same as

const test = (a, b, c) => { return expression }

Note, when using the above shorthand to implicitly return an object, things become obscure. What stops JavaScript from believing the brackets within which we are required to encapsulate our object is not our function body? To get around this, we wrap the object’s brackets in parentheses. This explicitly lets JavaScript know that we are indeed returning an object, and we are not just defining a body.

const test = () => ({ pi: 3.14 }); // Spaces between brackets are a formality to make the code look cleaner.

To help solidify the concept of ES6 functions, we’ll refactor some of our earlier code allowing us to compare the differences between both notations.

asyncAddFunction(...), from above, could be refactored from:

function asyncAddFunction(a, b, callback){
  callback(a + b);
}

to:

const aysncAddFunction = (a, b, callback) => {
  callback(a + b);
};

or even to:

const aysncAddFunction = (a, b, callback) => callback(a + b); // This will return callback(a + b).

When calling the function, we could pass an arrow function in for the callback:

asyncAddFunction(10, 12, sum => { // No parentheses because we only take one argument.
  console.log(sum);
}

It is clear to see how this method improves code readability. To show you just one case, we can take our old ES5 Promise based example above, and refactor it to use arrow functions.

makeAPICall('/example')
  .then(res => makeAPICall(`/newExample/${res.UserName}`))
  .then(res => console.log(res))
  .catch(err => console.log('Error: ', err));

Now, there are some caveats with arrow functions. For one, they do not bind a this keyword. Suppose I have the following object:

const Person = {
  name: 'John Doe',
  greeting: () => {
    console.log(`Hi. My name is ${this.name}.`);
  }
}

You might expect a call to Person.greeting() will return “Hi. My name is John Doe.” Instead, we get: “Hi. My name is undefined.” That is because arrow functions do not have a this, and so attempting to use this inside an arrow function defaults to the this of the enclosing scope, and the enclosing scope of the Person object is window, in the browser, or module.exports in Node.

To prove this, if we use the same object again, but set the name property of the global this to something like ‘Jane Doe’, then this.name in the arrow function returns ‘Jane Doe’, because the global this is within the enclosing scope, or is the parent of the Person object.

this.name = 'Jane Doe';

const Person = {
  name: 'John Doe',
  greeting: () => {
    console.log(`Hi. My name is ${this.name}.`);
  }
}

Person.greeting(); // Hi. My name is Jane Doe

This is known as ‘Lexical Scoping’, and we can get around it by using the so-called ‘Short Syntax’, which is where we lose the colon and the arrow as to refactor our object as such:

const Person = {
  name: 'John Doe',
  greeting() {
    console.log(`Hi. My name is ${this.name}.`);
  }
}

Person.greeting() //Hi. My name is John Doe.

ES6 Classes

While JavaScript never supported classes, you could always emulate them with objects like the above. EcmaScript 6 provides support for classes using the class and new keywords:

class Person {
   constructor(name) {
      this.name = name;
   }
   greeting() {
      console.log(`Hi. My name is ${this.name}.`);
   }
}

const person = new Person(‘John’);
person.greeting(); // Hi. My name is John.

The constructor function gets called automatically when using the new keyword, into which we can pass arguments to initially set up the object. This should be familiar to any reader who has experience with more statically typed object-oriented programming languages like Java, C++, and C#.

Without going into too much detail about OOP concepts, another such paradigm is “inheritance”, which is to allow one class to inherit from another. A class called Car, for example, will be very general — containing such methods as “stop”, “start”, etc., as all cars need. A sub-set of the class called SportsCar, then, might inherit fundamental operations from Car and override anything it needs custom. We could denote such a class as follows:

class Car {
   constructor(licensePlateNumber) {
      this.licensePlateNumber = licensePlateNumber;
   }
   start() {}
   stop() {}
   getLicensePlate() {
      return this.licensePlateNumber;
   }
   // …
}


class SportsCar extends Car {
   constructor(engineRevCount, licensePlateNumber) {
      super(licensePlateNumber); // Pass licensePlateNumber up to the parent class.
      this.engineRevCount = engineRevCount;
   }
   start() {
      super.start();
   }
   stop() {
      super.stop();
   }
   getLicensePlate() {
      return super.getLicensePlate();
   }
   getEngineRevCount() {
      return this.engineRevCount;
   }
}

You can clearly see that the super keyword allows us to access properties and methods from the parent, or super, class.

JavaScript Events

An Event is an action that occurs to which you have the ability to respond. Suppose you are building a login form for your application. When the user presses the “submit” button, you can react to that event via an “event handler” in your code — typically a function. When this function is defined as the event handler, we say we are “registering an event handler”. The event handler for the submit button click will likely check the formatting of the input provided by the user, sanitize it to prevent such attacks as SQL Injections or Cross Site Scripting (please be aware that no code on the client-side can ever be considered safe. Always sanitize data on the server — never trust anything from the browser), and then check to see if that username and password combination exits within a database to authenticate a user and serve them a token.

Since this is an article about Node, we’ll focus on the Node Event Model.

We can use the events module from Node to emit and react to specific events. Any object that emits an event is an instance of the EventEmitter class.

We can emit an event by calling the emit() method and we listen for that event via the on() method, both of which are exposed through the EventEmitter class.

const EventEmitter = require('events');

const myEmitter = new EventEmitter();

With myEmitter now an instance of the EventEmitter class, we can access emit() and on():

const EventEmitter = require('events');

const myEmitter = new EventEmitter();

myEmitter.on('someEvent', () => {
  console.log('The "someEvent" event was fired (emitted)');
});

myEmitter.emit('someEvent'); // This will call the callback function above.

The second parameter to myEmitter.on() is the callback function that will fire when the event is emitted — this is the event handler. The first parameter is the name of the event, which can be anything we like, although the camelCase naming convention is recommended.

Additionally, the event handler can take any number of arguments, which are passed down when the event is emitted:

const EventEmitter = require('events');

const myEmitter = new EventEmitter();

myEmitter.on('someEvent', (data) => {
  console.log(`The "someEvent" event was fired (emitted) with data: ${data}`);
});

myEmitter.emit('someEvent', 'This is the data payload');

By using inheritance, we can expose the emit() and on() methods from ‘EventEmitter’ to any class. This is done by creating a Node.js class, and using the extends reserved keyword to inherit the properties available on EventEmitter:

const EventEmitter = require('events');

class MyEmitter extends EventEmitter {
  // This is my class. I can emit events from a MyEmitter object.
}

Suppose we are building a vehicle collision notification program that receives data from gyroscopes, accelerometers, and pressure gauges on the car’s hull. When a vehicle collides with an object, those external sensors will detect the crash, executing the collide(...) function and passing to it the aggregated sensor data as a nice JavaScript Object. This function will emit a collision event, notifying the vendor of the crash.

const EventEmitter = require('events');

class Vehicle extends EventEmitter {
  collide(collisionStatistics) {
    this.emit('collision', collisionStatistics)
  }
}

const myVehicle = new Vehicle();
myVehicle.on('collision', collisionStatistics => {
  console.log('WARNING! Vehicle Impact Detected: ', collisionStatistics);
  notifyVendor(collisionStatistics);
});

myVehicle.collide({ ... });

This is a convoluted example for we could just put the code within the event handler inside the collide function of the class, but it demonstrates how the Node Event Model functions nonetheless. Note that some tutorials will show the util.inherits() method of permitting an object to emit events. That has been deprecated in favor of ES6 Classes and extends.

The Node Package Manager

When programming with Node and JavaScript, it’ll be quite common to hear about npm. Npm is a package manager which does just that — permits the downloading of third-party packages that solve common problems in JavaScript. Other solutions, such as Yarn, Npx, Grunt, and Bower exist as well, but in this section, we’ll focus only on npm and how you can install dependencies for your application through a simple Command Line Interface (CLI) using it.

Let’s start simple, with just npm. Visit the NpmJS homepage to view all of the packages available from NPM. When you start a new project that will depend on NPM Packages, you’ll have to run npm init through the terminal in your project’s root directory. You will be asked a series of questions which will be used to create a package.json file. This file stores all of your dependencies — modules that your application depends on to function, scripts — pre-defined terminal commands to run tests, build the project, start the development server, etc., and more.

To install a package, simply run npm install [package-name] --save. The save flag will ensure the package and its version is logged in the package.json file. Since npm version 5, dependencies are saved by default, so --save may be omitted. You will also notice a new node_modules folder, containing the code for that package you just installed. This can also be shortened to just npm i [package-name]. As a helpful note, the node_modules folder should never be included in a GitHub repository due to its size. Whenever you clone a repo from GitHub (or any other version management system), be sure to run the command npm install to go out and fetch all the packages defined in the package.json file, creating the node_modules directory automatically. You can also install a package at a specific version: npm i [package-name]@1.10.1 --save, for example.

Removing a package is similar to installing one: npm remove [package-name].

You can also install a package globally. This package will be available across all projects, not just the one your working on. You do this with the -g flag after npm i [package-name]. This is commonly used for CLIs, such as Google Firebase and Heroku. Despite the ease this method presents, it is generally considered bad practice to install packages globally, for they are not saved in the package.json file, and if another developer attempts to use your project, they won’t attain all the required dependencies from npm install.

APIs & JSON

APIs are a very common paradigm in programming, and even if you are just starting out in your career as a developer, APIs and their usage, especially in web and mobile development, will likely come up more often than not.

An API is an Application Programming Interface, and it is basically a method by which two decoupled systems may communicate with each other. In more technical terms, an API permits a system or computer program (usually a server) to receive requests and send appropriate responses (to a client, also known as a host).

Suppose you are building a weather application. You need a way to geocode a user’s address into a latitude and longitude, and then a way to attain the current or forecasted weather at that particular location.

As a developer, you want to focus on building your app and monetizing it, not putting the infrastructure in place to geocode addresses or placing weather stations in every city.

Luckily for you, companies like Google and OpenWeatherMap have already put that infrastructure in place, you just need a way to talk to it — that is where the API comes in. While, as of now, we have developed a very abstract and ambiguous definition of the API, bear with me. We’ll be getting to tangible examples soon.

Now, it costs money for companies to develop, maintain, and secure that aforementioned infrastructure, and so it is common for corporations to sell you access to their API. This is done with that is known as an API key, a unique alphanumeric identifier associating you, the developer, with the API. Every time you ask the API to send you data, you pass along your API key. The server can then authenticate you and keep track of how many API calls you are making, and you will be charged appropriately. The API key also permits Rate-Limiting or API Call Throttling (a method of throttling the number of API calls in a certain timeframe as to not overwhelm the server, preventing DOS attacks — Denial of Service). Most companies, however, will provide a free quota, giving you, as an example, 25,000 free API calls a day before charging you.

Up to this point, we have established that an API is a method by which two computer programs can communicate with each other. If a server is storing data, such as a website, and your browser makes a request to download the code for that site, that was the API in action.

Let us look at a more tangible example, and then we’ll look at a more real-world, technical one. Suppose you are eating out at a restaurant for dinner. You are equivalent to the client, sitting at the table, and the chef in the back is equivalent to the server.

Since you will never directly talk to the chef, there is no way for him/her to receive your request (for what order you would like to make) or for him/her to provide you with your meal once you order it. We need someone in the middle. In this case, it’s the waiter, analogous to the API. The API provides a medium with which you (the client) may talk to the server (the chef), as well as a set of rules for how that communication should be made (the menu — one meal is allowed two sides, etc.)

Now, how do you actually talk to the API (the waiter)? You might speak English, but the chef might speak Spanish. Is the waiter expected to know both languages to translate? What if a third person comes in who only speaks Mandarin? What then? Well, all clients and servers have to agree to speak a common language, and in computer programming, that language is JSON, pronounced JAY-sun, and it stands for JavaScript Object Notation.

At this point, we don’t quite know what JSON looks like. It’s not a computer programming language, it’s just, well, a language, like English or Spanish, that everyone (everyone being computers) understands on a guaranteed basis. It’s guaranteed because it’s a standard, notably RFC 8259, the JavaScript Object Notation (JSON) Data Interchange Format by the Internet Engineering Task Force (IETF).

Even without formal knowledge of what JSON actually is and what it looks like (we’ll see in an upcoming article in this series), we can go ahead introduce a technical example operating on the Internet today that employs APIs and JSON. APIs and JSON are not just something you can choose to use, it’s not equivalent to one out of a thousand JavaScript frameworks you can pick to do the same thing. It is THE standard for data exchange on the web.

Suppose you are building a travel website that compares prices for aircraft, rental car, and hotel ticket prices. Let us walk through, step-by-step, on a high level, how we would build such an application. Of course, we need our User Interface, the front-end, but that is out of scope for this article.

We want to provide our users with the lowest price booking method. Well, that means we need to somehow attain all possible booking prices, and then compare all of the elements in that set (perhaps we store them in an array) to find the smallest element (known as the infimum in mathematics.)

How will we get this data? Well, suppose all of the booking sites have a database full of prices. Those sites will provide an API, which exposes the data in those databases for use by you. You will call each API for each site to attain all possible booking prices, store them in your own array, find the lowest or minimum element of that array, and then provide the price and booking link to your user. We’ll ask the API to query its database for the price in JSON, and it will respond with said price in JSON to us. We can then use, or parse, that accordingly. We have to parse it because APIs will return JSON as a string, not the actual JavaScript data type of JSON. This might not make sense now, and that’s okay. We’ll be covering it more in a future article.

Also, note that just because something is called an API does not necessarily mean it operates on the web and sends and receives JSON. The Java API, for example, is just the list of classes, packages, and interfaces that are part of the Java Development Kit (JDK), providing programming functionality to the programmer.

Okay. We know we can talk to a program running on a server by way of an Application Programming Interface, and we know that the common language with which we do this is known as JSON. But in the web development and networking world, everything has a protocol. What do we actually do to make an API call, and what does that look like code-wise? That’s where HTTP Requests enter the picture, the HyperText Transfer Protocol, defining how messages are formatted and transmitted across the Internet. Once we have an understanding of HTTP (and HTTP verbs, you’ll see that in the next section), we can look into actual JavaScript frameworks and methods (like fetch()) offered by the JavaScript API (similar to the Java API), that actually allow us to make API calls.

HTTP And HTTP Requests

HTTP is the HyperText Transfer Protocol. It is the underlying protocol that determines how messages are formatted as they are transmitted and received across the web. Let’s think about what happens when, for example, you attempt to load the home page of Smashing Magazine in your web browser.

You type the website URL (Uniform Resource Locator) in the URL bar, where the DNS server (Domain Name Server, out of scope for this article) resolves the URL into the appropriate IP Address. The browser makes a request, called a GET Request, to the Web Server to, well, GET the underlying HTML behind the site. The Web Server will respond with a message such as “OK”, and then will go ahead and send the HTML down to the browser where it will be parsed and rendered accordingly.

There are a few things to note here. First, the GET Request, and then the “OK” response. Suppose you have a specific database, and you want to write an API to expose that database to your users. Suppose the database contains books the user wants to read (as it will in a future article in this series). Then there are four fundamental operations your user may want to perform on this database, that is, Create a record, Read a record, Update a record, or Delete a record, known collectively as CRUD operations.

Let’s look at the Read operation for a moment. Without incorrectly assimilating or conflating the notion of a web server and a database, that Read operation is very similar to your web browser attempting to get the site from the server, just as to read a record is to get the record from the database.

This is known as an HTTP Request. You are making a request to some server somewhere to get some data, and, as such, the request is appropriately named “GET”, capitalization being a standard way to denote such requests.

What about the Create portion of CRUD? Well, when talking about HTTP Requests, that is known as a POST request. Just as you might post a message on a social media platform, you might also post a new record to a database.

CRUD’s Update allows us to use either a PUT or PATCH Request in order to update a resource. HTTP’s PUT will either create a new record or will update/replace the old one.

Let’s look at this a bit more in detail, and then we’ll get to PATCH.

An API generally works by making HTTP requests to specific routes in a URL. Suppose we are making an API to talk to a DB containing a user’s booklist. Then we might be able to view those books at the URL .../books. A POST requests to .../books will create a new book with whatever properties you define (think id, title, ISBN, author, publishing data, etc.) at the .../books route. It doesn’t matter what the underlying data structure is that stores all the books at .../books right now. We just care that the API exposes that endpoint (accessed through the route) to manipulate data. The prior sentence was key: A POST request creates a new book at the ...books/ route. The difference between PUT and POST, then, is that PUT will create a new book (as with POST) if no such book exists, or, it will replace an existing book if the book already exists within that aforementioned data structure.

Suppose each book has the following properties: id, title, ISBN, author, hasRead (boolean).

Then to add a new book, as seen earlier, we would make a POST request to .../books. If we wanted to completely update or replace a book, we would make a PUT request to .../books/id where id is the ID of the book we want to replace.

While PUT completely replaces an existing book, PATCH updates something having to do with a specific book, perhaps modifying the hasRead boolean property we defined above — so we’d make a PATCH request to …/books/id sending along the new data.

It can be difficult to see the meaning of this right now, for thus far, we’ve established everything in theory but haven’t seen any tangible code that actually makes an HTTP request. We shall, however, get to that soon, covering GET in this article, ad the rest in a future article.

There is one last fundamental CRUD operation and it’s called Delete. As you would expect, the name of such an HTTP Request is “DELETE”, and it works much the same as PATCH, requiring the book’s ID be provided in a route.

We have learned thus far, then, that routes are specific URLs to which you make an HTTP Request, and that endpoints are functions the API provides, doing something to the data it exposes. That is, the endpoint is a programming language function located on the other end of the route, and it performs whatever HTTP Request you specified. We also learned that there exist such terms as POST, GET, PUT, PATCH, DELETE, and more (known as HTTP verbs) that actually specify what requests you are making to the API. Like JSON, these HTTP Request Methods are Internet standards as defined by the Internet Engineering Task Force (IETF), most notably, RFC 7231, Section Four: Request Methods, and RFC 5789, Section Two: Patch Method, where RFC is an acronym for Request for Comments.

So, we might make a GET request to the URL .../books/id where the ID passed in is known as a parameter. We could make a POST, PUT, or PATCH request to .../books to create a resource or to .../books/id to modify/replace/update a resource. And we can also make a DELETE request to .../books/id to delete a specific book.

A full list of HTTP Request Methods can be found here.

It is also important to note that after making an HTTP Request, we’ll receive a response. The specific response is determined by how we build the API, but you should always receive a status code. Earlier, we said that when your web browser requests the HTML from the web server, it’ll respond with “OK”. That is known as an HTTP Status Code, more specifically, HTTP 200 OK. The status code just specifies how the operation or action specified in the endpoint (remember, that’s our function that does all the work) completed. HTTP Status Codes are sent back by the server, and there are probably many you are familiar with, such as 404 Not Found (the resource or file could not be found, this would be like making a GET request to .../books/id where no such ID exists.)

A complete list of HTTP Status Codes can be found here.

MongoDB

MongoDB is a non-relational, NoSQL database similar to the Firebase Real-time Database. You will talk to the database via a Node package such as the MongoDB Native Driver or Mongoose.

In MongoDB, data is stored in JSON, which is quite different from relational databases such as MySQL, PostgreSQL, or SQLite. Both are called databases, with SQL Tables called Collections, SQL Table Rows called Documents, and SQL Table Columns called Fields.

We will use the MongoDB Database in an upcoming article in this series when we create our very first Bookshelf API. The fundamental CRUD Operations listed above can be performed on a MongoDB Database.

It’s recommended that you read through the MongoDB Docs to learn how to create a live database on an Atlas Cluster and make CRUD Operations to it with the MongoDB Native Driver. In the next article of this series, we will learn how to set up a local database and a cloud production database.

Building A Command Line Node Application

When building out an application, you will see many authors dump their entire code base at the beginning of the article, and then attempt to explain each line thereafter. In this text, I’ll take a different approach. I’ll explain my code line-by-line, building the app as we go. I won’t worry about modularity or performance, I won’t split the codebase into separate files, and I won’t follow the DRY Principle or attempt to make the code reusable. When just learning, it is useful to make things as simple as possible, and so that is the approach I will take here.

Let us be clear about what we are building. We won’t be concerned with user input, and so we won’t make use of packages like Yargs. We also won’t be building our own API. That will come in a later article in this series when we make use of the Express Web Application Framework. I take this approach as to not conflate Node.js with the power of Express and APIs since most tutorials do. Rather, I’ll provide one method (of many) by which to call and receive data from an external API which utilizes a third-party JavaScript library. The API we’ll be calling is a Weather API, which we’ll access from Node and dump its output to the terminal, perhaps with some formatting, known as “pretty-printing”. I’ll cover the entire process, including how to set up the API and attain API Key, the steps of which provide the correct results as of January 2019.

We’ll be using the OpenWeatherMap API for this project, so to get started, navigate to the OpenWeatherMap sign-up page and create an account with the form. Once logged in, find the API Keys menu item on the dashboard page (located over here). If you just created an account, you’ll have to pick a name for your API Key and hit “Generate”. It could take at least 2 hours for your new API Key to be functional and associated with your account.

Before we start building out the application, we’ll visit the API Documentation to learn how to format our API Key. In this project, we’ll be specifying a zip code and a country code to attain the weather information at that location.

From the docs, we can see that the method by which we do this is to provide the following URL:

api.openweathermap.org/data/2.5/weather?zip={zip code},{country code}

Into which we could input data:

api.openweathermap.org/data/2.5/weather?zip=94040,us

Now, before we can actually attain relevant data from this API, we’ll need to provide our new API Key as a query parameter:

api.openweathermap.org/data/2.5/weather?zip=94040,us&appid={YOUR_API_KEY}

For now, copy that URL into a new tab in your web browser, replacing the {YOUR_API_KEY} placeholder with the API Key you obtained earlier when you registered for an account.

The text you can see is actually JSON — the agreed upon language of the web as discussed earlier.

To inspect this further, hit Ctrl + Shift + I in Google Chrome to open the Chrome Developer tools, and then navigate to the Network tab. At present, there should be no data here.

Empty Chrome Dev Tools Network Tab
The empty Google Chrome Developer Tools(Large preview)

To actually monitor network data, reload the page, and watch the tab be populated with useful information. Click the first link as depicted in the image below.

Populated Chrome Dev Tools Network Tab
The populated Google Chrome Developer Tools (Large preview)

Once you click on that link, we can actually view HTTP specific information, such as the headers. Headers are sent in the response from the API (you can also, in some cases, send your own headers to the API, or you can even create your own custom headers (often prefixed with x-) to send back when building your own API), and just contain extra information that either the client or server may need.

In this case, you can see that we made an HTTP GET Request to the API, and it responded with an HTTP Status 200 OK. You can also see that the data sent back was in JSON, as listed under the “Response Headers” section.

Google Dev Tools depicting the Headers from the API response
Headers in the response from the API (Large preview)

If you hit the preview tab, you can actually view the JSON as a JavaScript Object. The text version you can see in your browser is a string, for JSON is always transmitted and received across the web as a string. That’s why we have to parse the JSON in our code, to get it into a more readable format — in this case (and in pretty much every case) — a JavaScript Object.

You can also use the Google Chrome Extension “JSON View” to do this automatically.

To start building out our application, I’ll open a terminal and make a new root directory and then cd into it. Once inside, I’ll create a new app.js file, run npm init to generate a package.json file with the default settings, and then open Visual Studio Code.

mkdir command-line-weather-app && cd command-line-weather-app
touch app.js
npm init
code .

Thereafter, I’ll download Axios, verify it has been added to my package.json file, and note that the node_modules folder has been created successfully.

In the browser, you can see that we made a GET Request by hand by manually typing the proper URL into the URL Bar. Axios is what will allow me to do that inside of Node.

Starting now, all of the following code will be located inside of the app.js file, each snippet placed one after the other.

The first thing I’ll do is require the Axios package we installed earlier with

const axios = require('axios');

We now have access to Axios, and can make relevant HTTP Requests, via the axios constant.

Generally, our API calls will be dynamic — in this case, we might want to inject different zip codes and country codes into our URL. So, I’ll be creating constant variables for each part of the URL, and then put them together with ES6 Template Strings. First, we have the part of our URL that will never change as well as our API Key:

const API_URL = 'https://api.openweathermap.org/data/2.5/weather?zip=';
const API_KEY = 'Your API Key Here';

I’ll also assign our zip code and country code. Since we are not expecting user input and are rather hard coding the data, I’ll make these constant as well, although, in many cases, it will be more useful to use let.

const LOCATION_ZIP_CODE = '90001';
const COUNTRY_CODE = 'us';

We now need to put these variables together into one URL to which we can use Axios to make GET Requests to:

const ENTIRE_API_URL = `${API_URL}${LOCATION_ZIP_CODE},${COUNTRY_CODE}&appid=${API_KEY}`;

Here is the contents of our app.js file up to this point:

const axios = require('axios');

// API specific settings.
const API_URL = 'https://api.openweathermap.org/data/2.5/weather?zip=';
const API_KEY = 'Your API Key Here';

const LOCATION_ZIP_CODE = '90001';
const COUNTRY_CODE = 'us';

const ENTIRE_API_URL = `${API_URL}${LOCATION_ZIP_CODE},${COUNTRY_CODE}&appid=${API_KEY}`;

All that is left to do is to actually use axios to make a GET Request to that URL. For that, we’ll use the get(url) method provided by axios.

axios.get(ENTIRE_API_URL)

axios.get(...) actually returns a Promise, and the success callback function will take in a response argument which will allow us to access the response from the API — the same thing you saw in the browser. I’ll also add a .catch() clause to catch any errors.

axios.get(ENTIRE_API_URL)
    .then(response => console.log(response))
    .catch(error => console.log('Error', error));

If we now run this code with node app.js in the terminal, you will be able to see the full response we get back. However, suppose you just want to see the temperature for that zip code — then most of that data in the response is not useful to you. Axios actually returns the response from the API in the data object, which is a property of the response. That means the response from the server is actually located at response.data, so let’s print that instead in the callback function: console.log(response.data).

Now, we said that web servers always deal with JSON as a string, and that is true. You might notice, however, that response.data is already an object (evident by running console.log(typeof response.data)) — we didn’t have to parse it with JSON.parse(). That is because Axios already takes care of this for us behind the scenes.

The output in the terminal from running console.log(response.data) can be formatted — “pretty-printed” — by running console.log(JSON.stringify(response.data, undefined, 2)). JSON.stringify() converts a JSON object into a string, and take in the object, a filter, and the number of characters by which to indent by when printing. You can see the response this provides:

{
  "coord": {
    "lon": -118.24,
    "lat": 33.97
  },
  "weather": [
    {
      "id": 800,
      "main": "Clear",
      "description": "clear sky",
      "icon": "01d"
    }
  ],
  "base": "stations",
  "main": {
    "temp": 288.21,
    "pressure": 1022,
    "humidity": 15,
    "temp_min": 286.15,
    "temp_max": 289.75
  },
  "visibility": 16093,
  "wind": {
    "speed": 2.1,
    "deg": 110
  },
  "clouds": {
    "all": 1
  },
  "dt": 1546459080,
  "sys": {
    "type": 1,
    "id": 4361,
    "message": 0.0072,
    "country": "US",
    "sunrise": 1546441120,
    "sunset": 1546476978
  },
  "id": 420003677,
  "name": "Lynwood",
  "cod": 200
}

Now, it is clear to see that the temperature we are looking for is located on the main property of the response.data object, so we can access it by calling response.data.main.temp. Let’s look at out application’s code up to now:

const axios = require('axios');

// API specific settings.
const API_URL = 'https://api.openweathermap.org/data/2.5/weather?zip=';
const API_KEY = 'Your API Key Here';

const LOCATION_ZIP_CODE = '90001';
const COUNTRY_CODE = 'us';

const ENTIRE_API_URL = `${API_URL}${LOCATION_ZIP_CODE},${COUNTRY_CODE}&appid=${API_KEY}`;

axios.get(ENTIRE_API_URL)
    .then(response => console.log(response.data.main.temp))
    .catch(error => console.log('Error', error));

The temperature we get back is actually in Kelvin, which is a temperature scale generally used in Physics, Chemistry, and Thermodynamics due to the fact that it provides an “absolute zero” point, which is the temperature at which all thermal motion of all inner particles cease. We just need to convert this to Fahrenheit or Celcius with the formulas below:

F = K * 9/5 &mdash; 459.67 C = K &mdash; 273.15

Let’s update our success callback to print the new data with this conversion. We’ll also add in a proper sentence for the purposes of User Experience:

axios.get(ENTIRE_API_URL)
    .then(response => {
        // Getting the current temperature and the city from the response object.
        const kelvinTemperature = response.data.main.temp;
        const cityName = response.data.name;
        const countryName = response.data.sys.country;

        // Making K to F and K to C conversions.
        const fahrenheitTemperature = (kelvinTemperature * 9/5) — 459.67;
        const celciusTemperature = kelvinTemperature — 273.15;

        // Building the final message.
        const message = (
            `Right now, in \
            ${cityName}, ${countryName} the current temperature is \
            ${fahrenheitTemperature.toFixed(2)} deg F or \
            ${celciusTemperature.toFixed(2)} deg C.`.replace(/\s+/g, ' ')
        );

        console.log(message);
    })
    .catch(error => console.log('Error', error));

The parentheses around the message variable are not required, they just look nice — similar to when working with JSX in React. The backslashes stop the template string from formatting a new line, and the replace() String prototype method gets rid of white space using Regular Expressions (RegEx). The toFixed() Number prototype methods rounds a float to a specific number of decimal places — in this case, two.

With that, our final app.js looks as follows:

const axios = require('axios');

// API specific settings.
const API_URL = 'https://api.openweathermap.org/data/2.5/weather?zip=';
const API_KEY = 'Your API Key Here';

const LOCATION_ZIP_CODE = '90001';
const COUNTRY_CODE = 'us';

const ENTIRE_API_URL = `${API_URL}${LOCATION_ZIP_CODE},${COUNTRY_CODE}&appid=${API_KEY}`;

axios.get(ENTIRE_API_URL)
    .then(response => {
        // Getting the current temperature and the city from the response object.
        const kelvinTemperature = response.data.main.temp;
        const cityName = response.data.name;
        const countryName = response.data.sys.country;

        // Making K to F and K to C conversions.
        const fahrenheitTemperature = (kelvinTemperature * 9/5) — 459.67;
        const celciusTemperature = kelvinTemperature — 273.15;

        // Building the final message.
        const message = (
            `Right now, in \
            ${cityName}, ${countryName} the current temperature is \
            ${fahrenheitTemperature.toFixed(2)} deg F or \
            ${celciusTemperature.toFixed(2)} deg C.`.replace(/\s+/g, ' ')
        );

        console.log(message);
    })
    .catch(error => console.log('Error', error));

Conclusion

We have learned a lot about how Node works in this article, from the differences between synchronous and asynchronous requests, to callback functions, to new ES6 features, events, package managers, APIs, JSON, and the HyperText Transfer Protocol, Non-Relational Databases, and we even built our own command line application utilizing most of that new found knowledge.

In future articles in this series, we’ll take an in-depth look at the Call Stack, the Event Loop, and Node APIs, we’ll talk about Cross-Origin Resource Sharing (CORS), and we’ll build a Full Stack Bookshelf API utilizing databases, endpoints, user authentication, tokens, server-side template rendering, and more.

From here, start building your own Node applications, read the Node documentation, go out and find interesting APIs or Node Modules and implement them yourself. The world is your oyster and you have at your fingertips access to the largest network of knowledge on the planet — the Internet. Use it to your advantage.

Further Reading on SmashingMag:

Smashing Editorial (dm, ra, il)