Animations can make a site stand out. Or, they can just as easily kill the experience. When working with web animations, there are a few things that could go wrong like adding animations that serve no purpose, setting durations that are  too long or too quick, or not using right type of animation in the first place. Even if all of these things are done correctly, an animation  style may not feel good, especially if they are not in sync with other animations or in line with the overall personality of the site.

Another important thing to note is that not all digital experiences should share the exact same animations. A marketing website might need different animations than a product website or a mobile app. Although the same basic principles of motion apply for all, there’re some nuances based on content type and screen size. 

For example, say you want to make a boring form more exciting to fill out. You add some delightful animations in each step moving forward, but is that a good idea for a form you know a user needs to visit and fill often? Watching the same animations over and over could get annoying in that case.

Clearly, there are conditions and considerations that will serve animations well. In this article, we’ll discuss about adding animations into product websites. Let’s dig into that a bit and lay down some ground rules for working with them. Not so much a manifesto, but more like a baseline we can reference and sort of rally around.

First off, what’s a good situation for an animation?

When used well, an animation is almost like content — it provides context and has meaning that helps inform the user that something has happened and even what to expect next. Here are a few good situations where animation can do exactly that.

Transitioning UI blocks

This might be the most common use case for animations. When a UI block is moved from its original position, or is added or removed from the DOM, it’s a good idea to let users see that happen.

Loading content

A loading animation is something we’ve all seen and encountered at some point in time! If not, a quick trip to CodePen shows you just how popular loading animations are. They’re ideal as placehholders for content, where users are not only given a hint at what to expect when the content loads, but confidence that something is being loaded at all.

Besides making the site feel fast, it also avoids janky content reflow, which can be super disorienting as elements render at different times.

Client side rendering is so interesting. Look at this janky loading experience. The page itself isn’t particularly slow, but it loads in very awkwardly. A whole thing front-end devs are going to have to get good at. pic.twitter.com/sMcD4nsL98

— Chris Coyier (@chriscoyier) October 30, 2018

Loading placeholders are best, of course, when you know the height of content blocks ahead of time.

Hinting

This is generally a one-time animation where the point is to give users a hint for where to look or what to do next. Some UIs are complex by nature. A little glow or ripple can help guide users through the process of completing a task or calling out a particular feature.

It doesn’t have to be all up in the user’s face. Instead, a little visual hint that informs without taking over the entire experience will do just fine.

Micro-interactions

Generally used on individual elements, micro-interactions give users instant visual feedback after performing an action. They instill confidence that a performed action has taken place and that something happened as a result — all while adding a little delight at the same time. 

These do not have to be fancy, like Twitter’s heart animation, but they totally should indicate some kind of feedback or response to the user’s action. Just check out how subtle — yet delightful — that is when a user does something as small as adding an item from one line to another:

OK, so when should we avoid animations?

We’ve just seen handful of situations where animations make a lot of sense. Let’s spell out the opposite conditions where animations generally contribute very little or nothing to the user experience. In other words, they become noticeable for bad reasons and are probably best left out of the equation.

Route transitions

Yes, we usually don’t see these sorts of animations on product websites but it’s worth mentioning to understand why they don’t make sense. These transitions work better on mobile apps because of the small screen area. On desktop screens there’s much larger area to animate. To animate the whole content smoothly, you’ll require to set more duration than on mobile screen. This will simply annoy the users making them wait to see the content as they are already used to see instant content visibility on the web. And in the worst cases, route transitions can not only be distracting, but a severe accessibility concern when it comes to motion sensitivity.

• 

On initial load of page content

You may do it in marketing websites when you want to educate users or move their focus  to a particular block. For product websites, it will be again annoying to see the same animation each time users navigates between pages.

When it’s unexpected

It’s a good idea to consider a user’s state of mind while they use a particular feature. Is visual feedback expected where the animation is being used? If not, it can confuse more than it helps.

For example, checkout this calculator app. There’s nothing new in the UI pattern when numbers are entered and calculations run. Users already know where to focus. There’s no point in making users wait before they can see results or surprise them with something that provides no additional meaning or benefit.

When you’re unsure how well it performs

It’s worth bearing in mind that not all devices, internet connections, and browsers are equal in the eyes of animation. Eric Bailey sums this up nicely in his deep-dive on the prefers-reduced-motion media query:

We also need to acknowledge that not every device that can access the web can also render animation, or render animation smoothly. When animation is used on a low-power or low quality device that “technically” supports it, the overall user experience suffers. Some people even deliberately seek this experience out as a feature.

The heading above that quote is a sage reminder: Animation is progressive enhancement. If we plan on using an animation — especially ones that threaten to dominate the experience — we’ve gotta at least consider a way to opt out of it and whether the experience still works without the animation. prefers-reduced-motion is the best place to start.

When the purpose isn’t clear

Lastly, I’d say don’t add animations wherever you’re not absolutely sure about the purpose it serves. Superfluous animation can be distracting and hurt more than it helps. This tweet from 2018 is still very true:

How long should an animation last?

The length of an animation is just as important as the type of animation being used. Wait too long, and the animation can appear to drag on. Go too fast, and the nice details of the animation can get lost (in best cases) or completely disorient the user (in worse cases).

So, how long should we set the duration of an animation? I’ll give you a classic answer: It depends.

The bigger the distance, generally the longer the duration

Animations (like the ones we looked at earlier) can be limited to a short duration. But if we’re taking about a massive transition where an object is traveling a long distance, we may feel it needs something a little longer to make sure things don’t move too fast. But avoid using duration longer than 400ms.

Check out this example. Notice how the content takes a little longer to transition because it has a greater distance to travel. But also notice that the it doesn’t have to last too long because the object that leaves fades into the object that enters, and the object that enters comes at a shorter distance rather than making it travel across the entire screen.

Goes to show that even big animations can be optimized in ways that make it feel shorter without getting lost in the mix.

Use a shorter duration when the user triggers the action

This is important and a common mistake. If the user already expects something to happen — and the focus is already clearly where it should be — then there’s no point in making the user wait seconds to complete what they already expect.

On the other hand, if the change is automatically triggered by the system, a longer duration makes sense, as it will allow the user to catch up to speed with the change taking place. Think of tooltips or modals that are not triggered by the user do not require a their immediate attention.

Enter and exit animations can have different durations 

Sometimes it makes sense to keep the animation for an object that is entering view a little faster than an animation for an object that is exiting, especially when the user is expecting to see that content change.

Take the previous example of dropdown menu. When a user clicks on it, they’d want to see the menu items right away — at least, I wouldn’t have to wait to see menu items. When the user clicks, let the submenu enter quickly and then smoothly leave when it’s dismissed so that it avoids distracting the user on the way out, when it’s no longer needed.

But this does not apply for large UI blocks. On larger blocks, for most cases, a duration longer than 200ms is required. In such cases, reversing the durations and letting a block exit faster than it entered ensures it won’t block the existing page view.

Animation duration across the product should be in sync with each other and with the brand’s personality

I’ve came across many products where one feature has really nice animations and another is simply too quick, slow or lacks any animation at all. 

Even worse is when animations within the same feature aren’t in sync.

That’s where having a style guide with thoughtful animation guidelines that can be used consistently across the experience can be a huge help.

How simple is too simple? Or how complex is too complex?

The complexity of an animation ought to be based on how frequently users are expected to encounter it, among the other things we’ve looked at so far. The more often users are expected to see it, the simpler the animation should be. This should override the previous rules of duration where necessary.

For example, the below animation would work in a main menu, but using the same staggering effect in drop-down menus across the product is just too much to take in. There is indeed a point of diminishing returns in animations, just as there is in economics.

But, hey, if this sort of complex animation is used sparingly in intentional instances, then it can be incredibly delightful!

But yes, you can be creative with the animations where there’s a decision pending at the user or while processing data. This makes waiting times more engaging, like when network breaks or a wrong passcode is submitted.

Which easing function should you use?

Ease? Ease in? Ease out? Ease in and out? Some cubic bezier curve?

The right easing adheres to the laws of physics. Disney’s principles of animation is the gold standard when it comes to that.

For enter animations, use bounce effect if you want immediate attention of the user, otherwise use a smooth acceleration (and deceleration, for that matter) that is incremental rather than linear. Bouncing should reflect gravity. Brandon Gregory’s post on natural-feeling animations provides all kinds of examples that fall in line with the laws of physics.

You can refer to this Gist by Adam Argyle for defining easings in CSS.

Lights, camera, and… intentional action!

Attention to detail is what separates outstanding animations from ordinary (or even straight up broken) ones. If you’re in the process of learning web animations or currently working on a project that calls for them, I sure hope this post can serve as a set of useful ground rules to help you get the most out of your work.

Apart from the rules, I’d also mention that good animations take time and practice. Sure, a lot of the stuff I covered here is somewhat anecdotal and based on personal experience, but that’s the result of developing an eye for animations after years of working with them. Learn, try, improve, and keep learning. Otherwise, you may end up with a collection of animations that deliver poor user experiences and even hurt the accessibility of your site.

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If you use <input type="number">, some browsers give you an input that has UI for incrementing the number, like up/down arrows (often called “spinners”).

That’s a bit helpful sometimes. But people have certainly explored fancier ways of updating that number. “Scrubbing” is one of those ways. I always think of Photoshop here, which has supported this interaction for a long time:

I saw a demo from Dominik Jančík the other day where they do this within a block of code. See how (if you’re on a device with a mouse) you can hover over the numbers and “scrub” from left to right to increase or decrease the numbers:

Dominik inquired about putting it on CodePen itself. I think that would be cool too, but I’m also a little leery of changes to the core editor, as I’ve been snakebitten by it before. It’s the perfect sort of thing for a CodeMirror and/or Monaco and/or Ace plugin, though, if anyone is so inclined.

It must already exist somehow for Ace because the Khan Academy editor supports it in their editor.

I poked around looking for other examples, and came across a good one from Fabrice Weinberg with lots of options:

I thought I had a memory of Lea Verou’s Dabblet doing this, but I think I remembered wrong. It does do some cool popups though:

It also supports ⌥+↑ and ⌥+↓ for incrementing numbers. CodePen does that! We support Emmet, which powers that feature.

Key Binding	Increment
Ctrl+↑	Number + 1
Ctrl+↓	Number – 1
Ctr+Alt+↑	Number + 10
Ctrl+Alt+↓	Number – 10
Alt+ ↑	Number + 0.1
Alt+ ↓	Number – 0.1

Y’all ever run across a number scrubber UX that you really like?

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Eric Bailey eviscerates the notion that the term “a11y” isn’t accessible. It’s a hot take that I’ve had myself, embarrassingly enough.

I never see people asking why WWI is written out the way it is, either. Won’t people confuse that with the first Wonder Woman movie? Or the first season of Westworld? Or some new Weight Watchers product? I also never see people questioning technical numeronyms like P2P, S3, or W3C?

If you are seeing the term for the first time and are confused, it’s extremely easy to search for and figure out. There are heaping piles of examples of people using it for very legitimate sites, products, conferences, and more. It’s no more of a spell-checking foul as any other industry jargon and easy enough to ignore.

Plus, you can always introduce it with semantic HTML:

Like any other abbreviation, I observe the Web Content Accessibility Guideline’s (WCAG) Success Criterion 3.1.4. Like any other acronym or industry jargon, I spell out the term in full the first time it appears in my writing, then follow it up with the acronym it represents:

Accessibility (<abbr>a11y</abbr>)

It reminds me of the term serverless. The obligatory hot take on it is that servers are still in use, but the quicker you get over it, the quicker you can get to realizing it’s a powerful industry-changing idea.

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Remember the last time you dealt with a UI-related bug that left you scratching your head for hours? Maybe the issue was happening at random, or occurring under specific circumstances (device, OS, browser, user action), or was just hidden in one of the many front-end technologies that are part of the project?

I was recently reminded of how convoluted UI bugs can be. I recently fixed an interesting bug that was affecting some SVGs in Safari browsers with no obvious pattern or reason. I had searched for any similar issues to get some clue about what was going on, but I found no useful results. Despite the obstacles, I managed to fix it.

I analyzed the problem by using some useful debugging strategies that I’ll also cover in the article. After I submitted the fix, I was reminded of the advice Chris has tweeted out a while back.

Write the article you wish you found when you googled something.

— Chris Coyier (@chriscoyier) October 30, 2017

…and here we are.

Here’s the problem

I found the following bug on a project I’ve been working on. This was on a live site.

I created a CodePen example to demonstrate the issue so you can check it out for yourself. If we open the example in Safari, the buttons might look as expected on load. But if we click on the first two larger buttons, the issue rears its ugly head. 

Whenever a browser paint event happens, the SVG in the larger buttons render incorrectly. It simply gets cut off. It might happen randomly on load. It might even happen when the screen is resized. Whatever the situation, it happens!

Here’s how I approached the problem.

First off, let’s consider the environment

It’s always a good idea to go over the details of the project to understand the environment and conditions under which the bug is present.

• This particular project is using React (but is not required for following this article).
• The SVGs are imported as React components and are inlined in HTML by webpack.
• The SVGs have been exported from a design tool and have no syntax errors.
• The SVGs have some CSS applied to them from a stylesheet.
• The affected SVGs are positioned inside a <button> HTML element.
• The issue occurs only in Safari (and was noticed on version 13).

Down the rabbit hole

Let’s take a look at the issue and see if we can make some assumptions about what is going on. Bugs like this one get convoluted, and we won’t immediately know what is going on. We don’t have to be 100% correct in our first try because we’ll go step-by-step and form hypotheses that we can test to narrow down the possible causes. 

Forming a hypothesis

At first, this looks like a CSS issue. Some styles might be applied on a hover event that breaks the layout or the overflow property of the SVG graphic. It also looks like the issue is happening at random, whenever Safari renders the page (paint event when resizing the screen, hover, click, etc.).

Let’s start with the simple and most obvious route and assume that CSS is the cause of the issue. We can consider the possibility that there is a bug in the Safari browser that causes SVG to render incorrectly when some specific style applies to the SVG element, like a flex layout, for example.

By doing so, we’ve formed a hypothesis. Our next step is to set up a test that is either going to confirm or contradict the hypothesis. Each test result will produce new facts about the bug and help form further hypotheses. 

Problem simplification

We’ll use a debugging strategy called problem simplification to try and pinpoint the issue. Cornell University’s CS lecture describes this strategy as “an approach to gradually eliminate portions of the code that are not relevant to the bug.”

By assuming the issue lies within CSS, we can end up pinpointing the issue or eliminating the CSS from the equation, reducing the number of possible causes and the complexity of the problem. 

Let’s try and confirm our hypothesis. If we temporarily exclude all non-browser stylesheets, the issue should not occur. I did that in my source code by commenting out the following line of code in my project.

import 'css/app.css';

I have created a handy CodePen example to demonstrate these elements without CSS included. In React, we are importing SVG graphics as components, and they are inlined in HTML using webpack.

If we open this pen on Safari and click on the button, we are still getting the issue. It still happens when the page loads, but on CodePen we have to force it by clicking the button. We can conclude that the CSS isn’t the culprit, but we can also see that only the two out of five buttons break under this condition. Let’s keep this in mind and move on to the next hypothesis.

Isolating the issue

Our next hypothesis states that Safari has a bug when rendering SVG inside an HTML <button> element. Since the issue has occurred on the first two buttons, we’ll isolate the first button and see what happens.

Sarah Drasner explains the importance of isolation and I highly recommend reading her article if you want to learn more about debugging tools and other approaches.

Isolation is possibly the strongest core tenets in all of debugging. Our codebases can be sprawling, with different libraries, frameworks, and they can include many contributors, even people who aren’t working on the project anymore. Isolating the problem helps us slowly whittle away non-essential parts of the problem so that we can singularly focus on a solution.

A “reduced test case” it is also often called. 

I moved this button to a separate and empty test route (blank page). I created the following CodePen to demonstrate that state. Even though we’ve concluded that the CSS is not the cause of the issue, we should keep it excluded until we’ve found out the real cause of the bug, to keep the problem simple as possible.

If we open this pen in Safari, we can see that we can no longer reproduce the issue and the SVG graphic displays as expected after clicking the button. We shouldn’t consider this change as an acceptable bug fix, but it gives a good starting point in creating a minimal reproducible example.

A minimal reproducible example

The main difference between the previous two examples is the button combination. After trying out all possible combinations, we can conclude that this issue occurs only when a paint event occurs on a larger SVG graphic that is alongside a smaller SVG graphic on the same page.

We created a minimal reproducible example that allows us to reproduce the bug without any unnecessary elements. With minimal reproducible example, we can study the issue in more detail and accurately pinpoint the part of the code causing it.

I’ve created the following CodePen to demonstrate the minimal reproducible example.

If we open this demo in Safari and click on a button, we can see the issue in action and form a hypothesis that these two SVGs somehow conflict with one another. If we overlay the second SVG graphic over the first, we can see that the size of the cropped circle on the first SVG graphic matches the exact dimensions of the smaller SVG graphic.

Divide and conquer

We’ve narrowed down the issue to the combination of two SVG graphics. Now we’re going to narrow things down to the specific SVG code that’s messing things up. If we only have a basic understanding of SVG code and want to pinpoint the issue, we can use a binary tree search strategy with a divide-and-conquer approach. Cornell University’s CS lecture describes this approach:

For example, starting from a large piece of code, place a check halfway through the code. If the error doesn’t show up at that point, it means the bug occurs in the second half; otherwise, it is in the first half. 

In SVG, we can try deleting <filter> (and also <defs> since it’s empty anyway) from the first SVG. Let’s first check what <filter> does. This article by Sara Soueidan explains it best.

Just like linear gradients, masks, patterns, and other graphical effects in SVG, filters have a conveniently-named dedicated element: the <filter> element.

A <filter> element is never rendered directly; its only usage is as something that can be referenced using the filter attribute in SVG, or the url() function in CSS.

In our SVG, <filter> applies a slight inset shadow at the bottom of the SVG graphic. After we delete it from the first SVG graphic, we expect the inner shadow to be gone. If the issue persists, we can conclude that something is wrong with the rest of the SVG markup.

I’ve created the following CodePen to showcase this test.

As we can see, the issue persists anyway. The inset bottom shadow is displayed even though we’ve removed the code. Not only that, now the bug appears on every browser. We can conclude that the issue lies within the rest of the SVG code. If we delete the remaining id from <g filter="url(#filter0_ii)">, the shadow is fully removed. What is going on?

Let’s take another look at the previously mentioned definition of the <filter> property and notice the following detail:

A <filter> element is never rendered directly; its only usage is as something that can be referenced using the filter attribute in SVG.

(Emphasis mine)

So we can conclude that the filter definition from the second SVG graphic is being applied to the first SVG graphic and causing the error.

Fixing the issue

We now know that issue is related to the <filter> property. We also know that both SVGs have the filter property since they use it for the inset shadow on the circle shape. Let’s compare the code between the two SVGs and see if we can explain and fix the issue.

I’ve simplified the code for both SVG graphics so we can clearly see what is going on. The following snippet shows the code for the first SVG.

<svg width="46" height="46" viewBox="0 0 46 46">
  <g filter="url(#filter0_ii)">
    <!-- ... -->
  </g>
  <!-- ... -->
  <defs>
    <filter id="filter0_ii" x="0" y="0" width="46" height="46">
      <!-- ... -->
    </filter>
  </defs>
</svg>

And the following snippet shows the code for the second SVG graphic.

<svg width="28" height="28" viewBox="0 0 28 28">
  <g filter="url(#filter0_ii)">
    <!-- ... -->
  </g>
  <!-- ... -->
  <defs>
    <filter id="filter0_ii" x="0" y="0" width="28" height="28">
      <!-- ... -->
    </filter>
  </defs>
</svg>

We can notice that the generated SVGs use the same id property id=filter0_ii. Safari applied the filter definition it read last (which, in our case, is the second SVG markup) and caused the first SVG to become cropped to the size of the second filter (from 46px to 28px). The id property should have a unique value in DOM. By having two or more id properties on a page, browsers cannot understand which reference to apply, and the filter property redefines on each paint event, dependent on the racing condition that causes the issue to appear randomly.

Let’s try assigning unique id attribute values to each SVG graphic and see if that fixes the issue.

If we open the CodePen example in Safari and click the button, we can see that we fixed the issue by assigning a unique ID to <filter> property in each SVG graphic file. If we think about the fact that we have non-unique value for an attribute like id, it means that this issue should be present on all browsers. For some reason, other browsers (including Chrome and Firefox) seem to handle this edge-case without any bugs, although this might be just a coincidence.

Wrapping up

That was quite a ride! We started barely knowing anything about an issue that seemingly occurred at random, to fully understanding and fixing it. Debugging UI and understanding visual bugs can be difficult if the cause of the issue is unclear or convoluted. Luckily, some useful debugging strategies can help us out.

First, we simplified the problem by forming hypotheses which helped us eliminate the components that were unrelated to the issue (style, markup, dynamic events, etc.). After that, we isolated the markup and found the minimal reproducible example which allowed us to focus on a single chunk of code. Finally, we pinpointed the issue with a divide-and-conquer strategy, and fixed it.

Thank you for taking the time to read this article. Before I go, I’d like to leave you with one final debugging strategy that is also featured in Cornell University’s CS lecture. 

Remember to take a break, relax and clear your mind between debugging attempts.

 If too much time is spent on a bug, the programmer becomes tired and debugging may become counterproductive. Take a break, clear your mind; after some rest, try to think about the problem from a different perspective.

References

• Cornell University CS 312 Lecture 26 – Debugging Techniques
• Debugging Tips and Tricks
• Reduced Test Cases
• SVG Filters 101

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Remy documented this the other day. Firefox supports a Highlight keyword and both Chrome and Safari support a -webkit-focus-ring-color keyword. So if you, for example, have removed focus from something and want to put it back in the same style as the browser default, or want to apply a focus style to an element when it isn’t directly in focus itself, this can be useful.

For example:

button:focus + span {
  outline: 5px auto Highlight;
  outline: 5px auto -webkit-focus-ring-color;
}

Looks good to me. It’s especially helpful with the sorta weird new Chrome double-outline style that would be slightly tricky to replicate otherwise.

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Shawn Wang thinks there are deeper, perhaps more uncomfortable, places to go with developer experience (DX) beyond the surface-level stuff that we recently covered. Sure, sure, documentation, CLIs, good demos. But there are much harder questions to answer that are part of the real DX. Shawn lists eight really good ones. I’ll share this one:

No product launches feature complete. Nobody expects you to. The true test is whether you address it up front or hide it like a dirty secret. As developers explore your offering, they will find things they want, that you don’t have, and will tell you about it. How long do you make developers dig to find known holes in your product? Do developers have confidence you will ship or reject these features promptly, or are they for a “v2” that will never come?

Direct Link to Article — Permalink

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The best way to learn is to build. Let’s learn about this hot new buzzword, Jamstack, by building a site with React, Netlify (Serverless) Functions, and Airtable. One of the ingredients of Jamstack is static hosting, but that doesn’t mean everything on the site has to be static. In fact, we’re going to build an app with full-on CRUD capability, just like a tutorial for any web technology with more traditional server-side access might.

Why these technologies, you ask?

You might already know this, but the “JAM” in Jamstack stands for JavaScript, APIs, and Markup. These technologies individually are not new, so the Jamstack is really just a new and creative way to combine them. You can read more about it over at the Jamstack site.

One of the most important benefits of Jamstack is ease of deployment and hosting, which heavily influence the technologies we are using. By incorporating Netlify Functions (for backend CRUD operations with Airtable), we will be able to deploy our full-stack application to Netlify. The simplicity of this process is the beauty of the Jamstack.

As far as the database, I chose Airtable because I wanted something that was easy to get started with. I also didn’t want to get bogged down in technical database details, so Airtable fits perfectly. Here’s a few of the benefits of Airtable:

1. You don’t have to deploy or host a database yourself
2. It comes with an Excel-like GUI for viewing and editing data
3. There’s a nice JavaScript SDK

What we’re building

For context going forward, we are going to build an app where you can use to track online courses that you want to take. Personally, I take lots of online courses, and sometimes it’s hard to keep up with the ones in my backlog. This app will let track those courses, similar to a Netflix queue.

 

One of the reasons I take lots of online courses is because I make courses. In fact, I have a new one available where you can learn how to build secure and production-ready Jamstack applications using React and Netlify (Serverless) Functions. We’ll cover authentication, data storage in Airtable, Styled Components, Continuous Integration with Netlify, and more! Check it out  →

Airtable setup

Let me start by clarifying that Airtable calls their databases “bases.” So, to get started with Airtable, we’ll need to do a couple of things.

1. Sign up for a free account
2. Create a new “base”
3. Define a new table for storing courses

Next, let’s create a new database. We’ll log into Airtable, click on “Add a Base” and choose the “Start From Scratch” option. I named my new base “JAMstack Demos” so that I can use it for different projects in the future.

Next, let’s click on the base to open it.

You’ll notice that this looks very similar to an Excel or Google Sheets document. This is really nice for being able tower with data right inside of the dashboard. There are few columns already created, but we add our own. Here are the columns we need and their types:

1. name (single line text)
2. link (single line text)
3. tags (multiple select)
4. purchased (checkbox)

We should add a few tags to the tags column while we’re at it. I added “node,” “react,” “jamstack,” and “javascript” as a start. Feel free to add any tags that make sense for the types of classes you might be interested in.

I also added a few rows of data in the name column based on my favorite online courses:

1. Build 20 React Apps
2. Advanced React Security Patterns
3. React and Serverless

The last thing to do is rename the table itself. It’s called “Table 1” by default. I renamed it to “courses” instead.

Locating Airtable credentials

Before we get into writing code, there are a couple of pieces of information we need to get from Airtable. The first is your API Key. The easiest way to get this is to go your account page and look in the “Overview” section.

Next, we need the ID of the base we just created. I would recommend heading to the Airtable API page because you’ll see a list of your bases. Click on the base you just created, and you should see the base ID listed. The documentation for the Airtable API is really handy and has more detailed instructions for find the ID of a base.

Lastly, we need the table’s name. Again, I named mine “courses” but use whatever you named yours if it’s different.

Project setup

To help speed things along, I’ve created a starter project for us in the main repository. You’ll need to do a few things to follow along from here:

1. Fork the repository by clicking the fork button
2. Clone the new repository locally
3. Check out the starter branch with git checkout starter

There are lots of files already there. The majority of the files come from a standard create-react-app application with a few exceptions. There is also a functions directory which will host all of our serverless functions. Lastly, there’s a netlify.toml configuration file that tells Netlify where our serverless functions live. Also in this config is a redirect that simplifies the path we use to call our functions. More on this soon.

The last piece of the setup is to incorporate environment variables that we can use in our serverless functions. To do this install the dotenv package.

npm install dotenv

Then, create a .env file in the root of the repository with the following. Make sure to use your own API key, base ID, and table name that you found earlier.

AIRTABLE_API_KEY=<YOUR_API_KEY>
AIRTABLE_BASE_ID=<YOUR_BASE_ID>
AIRTABLE_TABLE_NAME=<YOUR_TABLE_NAME>

Now let’s write some code!

Setting up serverless functions

To create serverless functions with Netlify, we need to create a JavaScript file inside of our /functions directory. There are already some files included in this starter directory. Let’s look in the courses.js file first.

const  formattedReturn  =  require('./formattedReturn');
const  getCourses  =  require('./getCourses');
const  createCourse  =  require('./createCourse');
const  deleteCourse  =  require('./deleteCourse');
const  updateCourse  =  require('./updateCourse');
exports.handler  =  async  (event)  =>  {
  return  formattedReturn(200, 'Hello World');
};

The core part of a serverless function is the exports.handler function. This is where we handle the incoming request and respond to it. In this case, we are accepting an event parameter which we will use in just a moment.

We are returning a call inside the handler to the formattedReturn function, which makes it a bit simpler to return a status and body data. Here’s what that function looks like for reference.

module.exports  =  (statusCode, body)  =>  {
  return  {
    statusCode,
    body: JSON.stringify(body),
  };
};

Notice also that we are importing several helper functions to handle the interaction with Airtable. We can decide which one of these to call based on the HTTP method of the incoming request.

• HTTP GET → getCourses
• HTTP POST → createCourse
• HTTP PUT → updateCourse
• HTTP DELETE → deleteCourse

Let’s update this function to call the appropriate helper function based on the HTTP method in the event parameter. If the request doesn’t match one of the methods we are expecting, we can return a 405 status code (method not allowed).

exports.handler = async (event) => {
  if (event.httpMethod === 'GET') {
    return await getCourses(event);
  } else if (event.httpMethod === 'POST') {
    return await createCourse(event);
  } else if (event.httpMethod === 'PUT') {
    return await updateCourse(event);
  } else if (event.httpMethod === 'DELETE') {
    return await deleteCourse(event);
  } else {
    return formattedReturn(405, {});
  }
};

Updating the Airtable configuration file

Since we are going to be interacting with Airtable in each of the different helper files, let’s configure it once and reuse it. Open the airtable.js file.

In this file, we want to get a reference to the courses table we created earlier. To do that, we create a reference to our Airtable base using the API key and the base ID. Then, we use the base to get a reference to the table and export it.

require('dotenv').config();
var Airtable = require('airtable');
var base = new Airtable({ apiKey: process.env.AIRTABLE_API_KEY }).base(
  process.env.AIRTABLE_BASE_ID
);
const table = base(process.env.AIRTABLE_TABLE_NAME);
module.exports = { table };

Getting courses

With the Airtable config in place, we can now open up the getCourses.js file and retrieve courses from our table by calling table.select().firstPage(). The Airtable API uses pagination so, in this case, we are specifying that we want the first page of records (which is 20 records by default).

const courses = await table.select().firstPage();
return formattedReturn(200, courses);

Just like with any async/await call, we need to handle errors. Let’s surround this snippet with a try/catch.

try {
  const courses = await table.select().firstPage();
  return formattedReturn(200, courses);
} catch (err) {
  console.error(err);
  return formattedReturn(500, {});
}

Airtable returns back a lot of extra information in its records. I prefer to simplify these records with only the record ID and the values for each of the table columns we created above. These values are found in the fields property. To do this, I used the an Array map to format the data the way I want.

const { table } = require('./airtable');
const formattedReturn = require('./formattedReturn');
module.exports = async (event) => {
  try {
    const courses = await table.select().firstPage();
    const formattedCourses = courses.map((course) => ({
      id: course.id,
      ...course.fields,
    }));
    return formattedReturn(200, formattedCourses);
  } catch (err) {
    console.error(err);
    return formattedReturn(500, {});
  }
};

How do we test this out? Well, the netlify-cli provides us a netlify dev command to run our serverless functions (and our front-end) locally. First, install the CLI:

npm install -g netlify-cli

Then, run the netlify dev command inside of the directory.

This beautiful command does a few things for us:

• Runs the serverless functions
• Runs a web server for your site
• Creates a proxy for front end and serverless functions to talk to each other on Port 8888.

Let’s open up the following URL to see if this works:

We are able to use /api/* for our API because of the redirect configuration in the netlify.toml file.

If successful, we should see our data displayed in the browser.

Creating courses

Let’s add the functionality to create a course by opening up the createCourse.js file. We need to grab the properties from the incoming POST body and use them to create a new record by calling table.create().

The incoming event.body comes in a regular string which means we need to parse it to get a JavaScript object.

const fields = JSON.parse(event.body);

Then, we use those fields to create a new course. Notice that the create() function accepts an array which allows us to create multiple records at once.

const createdCourse = await table.create([{ fields }]);

Then, we can return the createdCourse:

return formattedReturn(200, createdCourse);

And, of course, we should wrap things with a try/catch:

const { table } = require('./airtable');
const formattedReturn = require('./formattedReturn');
module.exports = async (event) => {
  const fields = JSON.parse(event.body);
  try {
    const createdCourse = await table.create([{ fields }]);
    return formattedReturn(200, createdCourse);
  } catch (err) {
    console.error(err);
    return formattedReturn(500, {});
  }
};

Since we can’t perform a POST, PUT, or DELETE directly in the browser web address (like we did for the GET), we need to use a separate tool for testing our endpoints from now on. I prefer Postman, but I’ve heard good things about Insomnia as well.

Inside of Postman, I need the following configuration.

• url: localhost:8888/api/courses
• method: POST
• body: JSON object with name, link, and tags

After running the request, we should see the new course record is returned.

We can also check the Airtable GUI to see the new record.

Tip: Copy and paste the ID from the new record to use in the next two functions.

Updating courses

Now, let’s turn to updating an existing course. From the incoming request body, we need the id of the record as well as the other field values.

We can specifically grab the id value using object destructuring, like so:

const {id} = JSON.parse(event.body);

Then, we can use the spread operator to grab the rest of the values and assign it to a variable called fields:

const {id, ...fields} = JSON.parse(event.body);

From there, we call the update() function which takes an array of objects (each with an id and fields property) to be updated:

const updatedCourse = await table.update([{id, fields}]);

Here’s the full file with all that together:

const { table } = require('./airtable');
const formattedReturn = require('./formattedReturn');
module.exports = async (event) => {
  const { id, ...fields } = JSON.parse(event.body);
  try {
    const updatedCourse = await table.update([{ id, fields }]);
    return formattedReturn(200, updatedCourse);
  } catch (err) {
    console.error(err);
    return formattedReturn(500, {});
  }
};

To test this out, we’ll turn back to Postman for the PUT request:

• url: localhost:8888/api/courses
• method: PUT
• body: JSON object with id (the id from the course we just created) and the fields we want to update (name, link, and tags)

I decided to append “Updated!!!” to the name of a course once it’s been updated.

We can also see the change in the Airtable GUI.

Deleting courses

Lastly, we need to add delete functionality. Open the deleteCourse.js file. We will need to get the id from the request body and use it to call the destroy() function.

const { id } = JSON.parse(event.body);
const deletedCourse = await table.destroy(id);

The final file looks like this:

const { table } = require('./airtable');
const formattedReturn = require('./formattedReturn');
module.exports = async (event) => {
  const { id } = JSON.parse(event.body);
  try {
    const deletedCourse = await table.destroy(id);
    return formattedReturn(200, deletedCourse);
  } catch (err) {
    console.error(err);
    return formattedReturn(500, {});
  }
};

Here’s the configuration for the Delete request in Postman.

• url: localhost:8888/api/courses
• method: PUT
• body: JSON object with an id (the same id from the course we just updated)

And, of course, we can double-check that the record was removed by looking at the Airtable GUI.

Displaying a list of courses in React

Whew, we have built our entire back end! Now, let’s move on to the front end. The majority of the code is already written. We just need to write the parts that interact with our serverless functions. Let’s start by displaying a list of courses.

Open the App.js file and find the loadCourses function. Inside, we need to make a call to our serverless function to retrieve the list of courses. For this app, we are going to make an HTTP request using fetch, which is built right in.

Thanks to the netlify dev command, we can make our request using a relative path to the endpoint. The beautiful thing is that this means we don’t need to make any changes after deploying our application!

const res = await fetch('/api/courses');
const courses = await res.json();

Then, store the list of courses in the courses state variable.

setCourses(courses)

Put it all together and wrap it with a try/catch:

const loadCourses = async () => {
  try {
    const res = await fetch('/api/courses');
    const courses = await res.json();
    setCourses(courses);
  } catch (error) {
    console.error(error);
  }
};

Open up localhost:8888 in the browser and we should our list of courses.

Adding courses in React

Now that we have the ability to view our courses, we need the functionality to create new courses. Open up the CourseForm.js file and look for the submitCourse function. Here, we’ll need to make a POST request to the API and send the inputs from the form in the body.

The JavaScript Fetch API makes GET requests by default, so to send a POST, we need to pass a configuration object with the request. This options object will have these two properties.

1. method → POST
2. body → a stringified version of the input data

await fetch('/api/courses', {
  method: 'POST',
  body: JSON.stringify({
    name,
    link,
    tags,
  }),
});

Then, surround the call with try/catch and the entire function looks like this:

const submitCourse = async (e) => {
  e.preventDefault();
  try {
    await fetch('/api/courses', {
      method: 'POST',
      body: JSON.stringify({
        name,
        link,
        tags,
      }),
    });
    resetForm();
    courseAdded();
  } catch (err) {
    console.error(err);
  }
};

Test this out in the browser. Fill in the form and submit it.

After submitting the form, the form should be reset, and the list of courses should update with the newly added course.

Updating purchased courses in React

The list of courses is split into two different sections: one with courses that have been purchased and one with courses that haven’t been purchased. We can add the functionality to mark a course “purchased” so it appears in the right section. To do this, we’ll send a PUT request to the API.

Open the Course.js file and look for the markCoursePurchased function. In here, we’ll make the PUT request and include both the id of the course as well as the properties of the course with the purchased property set to true. We can do this by passing in all of the properties of the course with the spread operator and then overriding the purchased property to be true.

const markCoursePurchased = async () => {
  try {
    await fetch('/api/courses', {
      method: 'PUT',
      body: JSON.stringify({ ...course, purchased: true }),
    });
    refreshCourses();
  } catch (err) {
    console.error(err);
  }
};

To test this out, click the button to mark one of the courses as purchased and the list of courses should update to display the course in the purchased section.

Deleting courses in React

And, following with our CRUD model, we will add the ability to delete courses. To do this, locate the deleteCourse function in the Course.js file we just edited. We will need to make a DELETE request to the API and pass along the id of the course we want to delete.

const deleteCourse = async () => {
  try {
    await fetch('/api/courses', {
      method: 'DELETE',
      body: JSON.stringify({ id: course.id }),
    });
    refreshCourses();
  } catch (err) {
    console.error(err);
  }
};

To test this out, click the “Delete” button next to the course and the course should disappear from the list. We can also verify it is gone completely by checking the Airtable dashboard.

Deploying to Netlify

Now, that we have all of the CRUD functionality we need on the front and back end, it’s time to deploy this thing to Netlify. Hopefully, you’re as excited as I am about now easy this is. Just make sure everything is pushed up to GitHub before we move into deployment.

If you don’t have a Netlify, account, you’ll need to create one (like Airtable, it’s free). Then, in the dashboard, click the “New site from Git” option. Select GitHub, authenticate it, then select the project repo.

Next, we need to tell Netlify which branch to deploy from. We have two options here.

1. Use the starter branch that we’ve been working in
2. Choose the master branch with the final version of the code

For now, I would choose the starter branch to ensure that the code works. Then, we need to choose a command that builds the app and the publish directory that serves it.

1. Build command: npm run build
2. Publish directory: build

Netlify recently shipped an update that treats React warnings as errors during the build proces. which may cause the build to fail. I have updated the build command to CI = npm run build to account for this.

Lastly, click on the “Show Advanced” button, and add the environment variables. These should be exactly as they were in the local .env that we created.

The site should automatically start building.

We can click on the “Deploys” tab in Netlify tab and track the build progress, although it does go pretty fast. When it is complete, our shiny new app is deployed for the world can see!

Welcome to the Jamstack!

The Jamstack is a fun new place to be. I love it because it makes building and hosting fully-functional, full-stack applications like this pretty trivial. I love that Jamstack makes us mighty, all-powerful front-end developers!

I hope you see the same power and ease with the combination of technology we used here. Again, Jamstack doesn’t require that we use Airtable, React or Netlify, but we can, and they’re all freely available and easy to set up. Check out Chris’ serverless site for a whole slew of other services, resources, and ideas for working in the Jamstack. And feel free to drop questions and feedback in the comments here!

---

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As a web developer, there is an interesting bit of back and forth that always comes along with setting up a new application. Even using a full stack web framework like Ruby on Rails can be non-trivial to set up and deploy, especially if it’s your first time doing so in a while.

Personally I have always enjoyed being able to dig in and write the actual bit of application logic more so than setting up the apps themselves. Lately I have become a big fan of React applications together with a GraphQL API and storing state with the Apollo library.

Setting up a React application has become very easy in the past few years, but setting up a backend with a GraphQL API? Not so much. So when I was working on a project recently, I decided to look for an easier way to integrate a GraphQL API and was delighted to find FaunaDB.

FaunaDB is a NoSQL database as a service that makes provisioning a GraphQL API an incredibly simple process, and even comes with a free tier. Frankly I was surprised and really impressed with how quickly I was able to go from zero to a working API.

The service also touts its production readiness, with a focus on making scalability much easier than if you were managing your own backend. Although I haven’t explored its more advanced features yet, if it’s anything like my first impression then the prospects and implications of using FaunaDB are quite exciting. For now, I can confirm that for many of my projects, it provides an excellent solution for managing state together with a React application.

While working on my project, I did run into a few configuration issues when making all of the frameworks work together which I think could’ve been addressed with a guide that focuses on walking through standing up an application in its entirety. So in this article, I’m going to do a thorough walkthrough of setting up a small to-do React application on Heroku, then persisting data to that application with FaunaDB using the Apollo library. You can find the full source code here.

Our Application

For this walkthrough, we’re building a to-do list where a user can take the following actions:

• Add a new item
• Mark an item as complete
• Remove an item

From a technical perspective, we’re going to accomplish this by doing the following:

• Creating a React application
• Deploying the application to Heroku
• Provisioning a new FaunaDB database
• Declaring a GraphQL API schema
• Provisioning a new database key
• Configuring Apollo in our React application to interact with our API
• Writing application logic and consume our API to persist information

Here’s a preview of what the final result will look like:

Creating the React Application

First we’ll create a boilerplate React application and make sure it runs. Assuming you have create-react-app installed, the commands to create a new application are:

create-react-app fauna-todo
cd fauna-todo
yarn start

After which you should be able to head to http://localhost:3000 and see the generated homepage for the application.

Deploying to Heroku

As I mentioned above, deploying React applications has become awesomely easy over the last few years. I’m using Heroku here since it’s been my go-to platform as a service for a while now, but you could just as easily use another service like Netlify (though of course the configuration will be slightly different). Assuming you have a Heroku account and the Heroku CLI installed, then this article shows that you only need a few lines of code to create and deploy a React application.

git init
heroku create -b https://github.com/mars/create-react-app-buildpack.git
git push heroku master

And your app is deployed! To view it you can run:

heroku open

Provisioning a FaunaDB Database

Now that we have a React app up and running, let’s add persistence to the application using FaunaDB. Head to fauna.com to create a free account. After you have an account, click “New Database” on the dashboard, and enter in a name of your choosing:

Creating an API via GraphQL Schema in FaunaDB

In this example, we’re going to declare a GraphQL schema then use that file to automatically generate our API within FaunaDB. As a first stab at the schema for our to-do application, let’s suppose that there is simply a collection of “Items” with “name” as its sole field. Since I plan to build upon this schema later and like being able to see the schema itself at a glance, I’m going to create a schema.graphql file and add it to the top level of my React application. Here is the content for this file:

type Item {
 name: String
}
type Query {
 allItems: [Item!]
}

If you’re unfamiliar with the concept of defining a GraphQL schema, think of it as a manifest for declaring what kinds of objects and queries are available within your API. In this case, we’re saying that there is going to be an Item type with a name string field and that we are going to have an explicit query allItems to look up all item records. You can read more about schemas in this Apollo article and types in this graphql.org article. FaunaDB also provides a reference document for declaring and importing a schema file.

We can now upload this schema.graphql file and use it to generate a GraphQL API. Head to the FaunaDB dashboard again and click on “GraphQL” then upload your newly created schema file here:

Congratulations! You have created a fully functional GraphQL API. This page turns into a “GraphQL Playground” which lets you interact with your API. Click on the “Docs” tab in the sidebar to see the available queries and mutations.

Note that in addition to our allItems query, FaunaDB has generated the following queries/mutations automatically on our behalf:

• findItemByID
• createItem
• updateItem
• deleteItem

All of these were derived by declaring the Item type in our schema file. Pretty cool right? Let’s give these queries and mutations a spin to familiarize ourselves with them. We can execute queries and mutations directly in the “GraphQL Playground.” Let’s first run a query for items. Enter this query into the left pane of the playground:

query MyItemQuery {
 allItems {
   data {
    name
   }
 }
}

Then click on the play button to run it:

The result is listed on the right pane, and unsurprisingly returns no results since we haven’t created any items yet. Fortunately createItem was one of the mutations that was automatically generated from the schema and we can use that to populate a sample item. Let’s run this mutation:

mutation MyItemCreation {
 createItem(data: { name: "My first todo item" }) {
   name
 }
}

You can see the result of the mutation in the right pane. It seems like our item was created successfully, but just to double check we can re-run our first query and see the result:

You can see that if we add our first query back to the left pane in the playground that the play button gives you a choice as to which operation you’d like to perform. Finally, note in step 3 of the screenshot above that our item was indeed created successfully.

In addition to running the query above, we can also look in the “Collections” tab of FaunaDB to view the collection directly:

Provisioning a New Database Key

Now that we have the database itself configured, we need a way for our React application to access it.

For the sake of simplicity in this application, this will be done with a secret key that we can add as an environment variable to our React application. We aren’t going to have authentication for individual users. Instead we’ll generate an application key which has permission to create, read, update, and delete items.

Authentication and authorization are substantial topics on their own — if you would like to learn more on how FaunaDB handles them as a follow up exercise to this guide, you can read all about the topic here.

The application key we generate has an associate set of permissions that are grouped together in a “role.” Let’s begin by first defining a role that has permission to perform CRUD operations on items, as well as perform the allItems query. Start by going to the “Security” tab, then clicking on “Manage Roles”:

There are 2 built in roles, admin and server. We could in theory use these roles for our key, but this is a bad idea as those keys would allow whoever has access to this key to perform database level operations such as creating new collections or even destroy the database itself. So instead, let’s create a new role by clicking on “New Custom Role” button:

You can name the role whatever you’d like, here we’re using the name ItemEditor and giving the role permission to read, write, create, and delete items — as well as permission to read the allItems index.

Save this role then, head to the “Security” tab and create a new key:

When creating a key, make sure to select “ItemEditor” for the role and whatever name you please:

Next you’ll be presented with your secret key which you’ll need to copy:

In order for React to load the key’s value as an environment variable, create a new file called .env.local which lives at the root level of your React application. In this file, add an entry for the generated key:

REACT_APP_FAUNA_SECRET=fnADzT7kXcACAFHdiKG-lIUWq-hfWIVxqFi4OtTv

Important: Since it’s not good practice to store secrets directly in source control in plain text, make sure that you also have a .gitignore file in your project’s root directory that contains .env.local so that your secrets won’t be added to your git repo and shared with others.

It’s critical that this variable’s name starts with “REACT_APP_” otherwise it won’t be recognized when the application is started. By adding the value to the .env.local file, it will still be loaded for the application when running locally. You’ll have to explicitly stop and restart your application with yarn start in order to see these changes take.

If you’re interested in reading more about how environment variables are loaded in apps created via create-react-app, there is a full explanation here. We’ll cover adding this secret as an environment variable in Heroku later on in this article.

Connecting to FaunaDB in React with Apollo

In order for our React application to interact with our GraphQL API, we need some sort of GraphQL client library. Fortunately for us, the Apollo client provides an elegant interface for making API requests as well as caching and interacting with the results.

To install the relevant Apollo packages we’ll need, run:

yarn add @apollo/client graphql @apollo/react-hooks

Now in your src directory of your application, add a new file named client.js with the following content:

import { ApolloClient, InMemoryCache } from "@apollo/client";
export const client = new ApolloClient({
 uri: "https://graphql.fauna.com/graphql",
 headers: {
   authorization: `Bearer ${process.env.REACT_APP_FAUNA_SECRET}`,
 },
 cache: new InMemoryCache(),
});

What we’re doing here is configuring Apollo to make requests to our FaunaDB database. Specifically, the uri makes the request to Fauna itself, then the authorization header indicates that we’re connecting to the specific database instance for the provided key that we generated earlier.

There are 2 important implications from this snippet of code:

1. The authorization header contains the key with the “ItemEditor” role, and is currently hard coded to use the same header regardless of which user is looking at our application. If you were to update this application to show a different to-do list for each user, you would need to login for each user and generate a token which could instead be passed in this header. Again, the FaunaDB documentation covers this concept if you care to learn more about it.
2. As with any time you add a layer of caching to a system (as we are doing here with Apollo), you introduce the potential to have stale data. FaunaDB’s operations are strongly consistent, and you can configure Apollo’s fetchPolicy to minimize the potential for stale data. In order to prevent stale reads to our cache, we’ll use a combination of refetch queries and specifying response fields in our mutations.

Next we’ll replace the contents of the home page’s component. Head to App.js and replace its content with:

import React from "react";
import { ApolloProvider } from "@apollo/client";
import { client } from "./client";
function App() {
 return (
   <ApolloProvider client={client}>
     <div style=>
       <h3>My Todo Items</h3>
       <div>items to get loaded here</div>
     </div>
   </ApolloProvider>
 );
}

Note: For this sample application I’m focusing on functionality over presentation, so you’ll see some inline styles. While I certainly wouldn’t recommend this for a production-grade application, I think it does at least demonstrate any added styling in the most straightforward manner within a small demo.

Visit http://localhost:3000 again and you’ll see:

Which contains the hard coded values we’ve set in our jsx above. What we would really like to see however is the to-do item we created in our database. In the src directory, let’s create a component called ItemList which lists out any items in our database:

import React from "react";
import gql from "graphql-tag";
import { useQuery } from "@apollo/react-hooks";
const ITEMS_QUERY = gql`
 {
   allItems {
     data {
       _id
       name
     }
   }
 }
`;
export function ItemList() {
 const { data, loading } = useQuery(ITEMS_QUERY);
if (loading) {
   return "Loading...";
 }
return (
   <ul>
     {data.allItems.data.map((item) => {
       return <li key={item._id}>{item.name}</li>;
     })}
   </ul>
 );
}

Then update App.js to render this new component  —  see the full commit in this example’s source code to see this step in its entirety. Previewing your app in again, you’ll see that your to-do item has loaded:

Now is a good time to commit your progress in git. And since we’re using Heroku, deploying is a snap:

git push heroku master
heroku open

When you run heroku open though, you’ll see that the page is blank. If we inspect the network traffic and request to FaunaDB, we’ll see an error about how the database secret is missing:

Which makes sense since we haven’t configured this value in Heroku yet. Let’s set it by going to the Heroku dashboard, selecting your application, then clicking on the “Settings” tab. In there you should add the REACT_APP_FAUNA_SECRET key and value used in the .env.local file earlier. Reusing this key is done for demonstration purposes. In a “real” application, you would probably have a separate database and separate keys for each environment.

If you would prefer to use the command line rather than Heroku’s web interface, you can use the following command and replace the secret with your key instead:

heroku config:set REACT_APP_FAUNA_SECRET=fnADzT7kXcACAFHdiKG-lIUWq-hfWIVxqFi4OtTv

Important: as noted in the Heroku docs, you need to trigger a deploy in order for this environment variable to apply in your app:

git commit — allow-empty -m 'Add REACT_APP_FAUNA_SECRET env var'
git push heroku master
heroku open

After running this last command, your Heroku-hosted app should appear and load the items from your database.

Adding New To-Do Items

We now have all of the pieces in place for accessing our FaunaDB database both locally and a hosted Heroku environment. Now adding items is as simple as calling the mutation we used in the GraphQL Playground earlier. Here is the code for an AddItem component, which uses a bare bones html form to call the createItem mutation:

import React from "react";
import gql from "graphql-tag";
import { useMutation } from "@apollo/react-hooks";
const CREATE_ITEM = gql`
 mutation CreateItem($data: ItemInput!) {
   createItem(data: $data) {
     _id
   }
 }
`;
const ITEMS_QUERY = gql`
 {
   allItems {
     data {
       _id
       name
     }
   }
 }
`;
export function AddItem() {
 const [showForm, setShowForm] = React.useState(false);
 const [newItemName, setNewItemName] = React.useState("");
const [createItem, { loading }] = useMutation(CREATE_ITEM, {
   refetchQueries: [{ query: ITEMS_QUERY }],
   onCompleted: () => {
     setNewItemName("");
     setShowForm(false);
   },
 });
if (showForm) {
   return (
     <form
       onSubmit={(e) => {
         e.preventDefault();
         createItem({ variables: { data: { name: newItemName } } });
       }}
     >
       <label>
         <input
           disabled={loading}
           type="text"
           value={newItemName}
           onChange={(e) => setNewItemName(e.target.value)}
           style=
         />
       </label>
       <input disabled={loading} type="submit" value="Add" />
     </form>
   );
 }
return <button onClick={() => setShowForm(true)}>Add Item</button>;
}

After adding a reference to AddItem in our App component, we can verify that adding items works as expected. Again, you can see the full commit in the demo app for a recap of this step.

Deleting New To-Do Items

Similar to how we called the automatically generated AddItem mutation to add new items, we can call the generated DeleteItem mutation to remove items from our list. Here’s what our updated ItemList component looks like after adding this mutation:

import React from "react";
import gql from "graphql-tag";
import { useMutation, useQuery } from "@apollo/react-hooks";
const ITEMS_QUERY = gql`
 {
   allItems {
     data {
       _id
       name
     }
   }
 }
`;
const DELETE_ITEM = gql`
 mutation DeleteItem($id: ID!) {
   deleteItem(id: $id) {
     _id
   }
 }
`;
export function ItemList() {
 const { data, loading } = useQuery(ITEMS_QUERY);
const [deleteItem, { loading: deleteLoading }] = useMutation(DELETE_ITEM, {
   refetchQueries: [{ query: ITEMS_QUERY }],
 });
if (loading) {
   return <div>Loading...</div>;
 }
return (
   <ul>
     {data.allItems.data.map((item) => {
       return (
         <li key={item._id}>
           {item.name}{" "}
           <button
             disabled={deleteLoading}
             onClick={(e) => {
               e.preventDefault();
               deleteItem({ variables: { id: item._id } });
             }}
           >
             Remove
           </button>
         </li>
       );
     })}
   </ul>
 );
}

Reloading our app and adding another item should result in a page that looks like this:

If you click on the “Remove” button for any item, the DELETE_ITEM mutation is fired and the entire list of items is fired upon completion as specified per the refetchQuery option. 

One thing you may have noticed is that in our ITEMS_QUERY, we’re specifying _id as one of the fields we’d like in the result set from our query. This _id field is automatically generated by FaunaDB as a unique identifier for each collection, and should be used when updating or deleting a record.

Marking Items as Complete

This wouldn’t be a fully functional to-do list without the ability to mark items as complete! So let’s add that now. By the time we’re done, we expect the app to look like this:

The first step we need to take is updating our Item schema within FaunaDB since right now the only information we store about an item is its name. Heading to our schema.graphql file, we can add a new field to track the completion state for an item:

type Item {
 name: String
 isComplete: Boolean
}
type Query {
 allItems: [Item!]
}

Now head to the GraphQL tab in the FaunaDB console and click on the “Update Schema” link to upload the newly updated schema file.

Note: there is also an “Override Schema” option, which can be used to rewrite your database’s schema from scratch if you’d like. One consideration to make when choosing to override the schema completely is that the data is deleted from your database. This may be fine for a test environment, but a test or production environment would require a proper database migration instead.

Since the changes we’re making here are additive, there won’t be any conflict with the existing schema so we can keep our existing data.

You can view the mutation itself and its expected schema in the GraphQL Playground in FaunaDB:

This tells us that we can call the deleteItem mutation with a data parameter of type ItemInput. As with our other requests, we could test this mutation in the playground if we wanted. For now, we can add it directly to the application. In ItemList.js, let’s add this mutation with this code as outlined in the example repository.

The references to UPDATE_ITEM are the most relevant changes we’ve made. It’s interesting to note as well that we don’t need the refetchQueries parameter for this mutation. When the update mutation returns, Apollo updates the corresponding item in the cache based on its identifier field (_id in this case) so our React component re-renders appropriately as the cache updates.

We now have all of the functionality for an initial version of a to-do application. As a final step, push your branch one more time to Heroku:

git push heroku master
heroku open

Conclusion

Take a moment to pat yourself on the back! You’ve created a brand-new React application, added persistence at a database level with FaunaDB, and can do deployments available to the entire world with the push of a branch to Heroku.

Now that we’ve covered some of the concepts behind provisioning and interacting with FaunaDB, setting up any similar project in the future is an amazingly fast process. Being able to provision a GraphQL-accessible database in minutes is a dream for me when it comes to spinning up a new project. Not only that, but this is a production grade database that you don’t have to worry about configuring or scaling — and instead get to focus on writing the rest of your application instead of playing the role of a database administrator.

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