More from Ryan Mulligan
Managing the position of an element as it travels across the length of its parent container can be tricky. Assuming they both have dynamic, responsive dimensions, we might rely on JS to check the width and/or height of each element and do some calculations for a proper end result. The classic FLIP technique has proven to be a solid solution in the past. For a modern approach, the View Transition API can also work well here. I now realize there's a much simpler approach using container query units and a dash of CSS wizardry. The demo Select the container query units option if it's not already, then click and hold the container to witness the magic. Try changing the element dimensions or resizing the parent container using its handle on the bottom right. Open CodePen demo Jump down to the solution if you'd like to get right into it. Otherwise, join me on a transformative journey to this final result. Transition exploration The following CSS will transition an element smoothly to the right when its parent container is pressed: .element { transition: transform 200ms ease-out; } .parent:active .element { transform: translateX(100%); } Individual transform properties are also available and well supported in modern browsers. I tend to use them more frequently when writing simple transforms like this. In the demo, we'll find the translate property is being transitioned. Let's update the above code example to something similar: .element { transition: translate 200ms ease-out; } .parent:active .element { translate: 100%; } Keep in mind that there's a pre-defined order for independent transform properties. Stefan's article explains the fundamental differences between transform functions and individual transforms. Not an issue with our current examples, but something to remember when multiple individual transforms are being applied. Check out the demo with x checked and the percentage option selected. When we click and hold the container, the element transitions the width of itself to the right. We can see that this percentage is based on the element's dimensions. While handy, it doesn't achieve our goal of moving the element all the way to the opposite side. Explicit dimensions If we knew the exact dimensions of the parent container, we could declare a calc() function where the element's full percentage is subtracted from the explicit parent size. .parent { width: 300px; } .element { transition: translate 200ms ease-out; } .parent:active .element { translate: calc(300px - 100%); } It works, but it's uncommon to have explicit dimensions declared like that. Our elements need to be flexible and responsive in any context. What can we do instead? Position properties Properties like top and left are available to us. Could we transition the element by doing something like this? .element { position: relative; left: 0; transition: 200ms ease-out; transition-property: translate, left; } .parent:active .element { left: 100%; translate: -100%; } Seems that we can, at least in the context of the demo. However, animating position properties has a negative impact on layout and creates performance issues. The browser works harder to recalculate element positions, repaint pixels, and then composite the result. This inevitably leads to janky or sluggish animations. GPU-accelerated properties such as transform and translate avoid triggering repaints so animations run buttery-smooth and fluid. Fair enough. We'll focus on moving the element using transform properties. It's time to reveal the strongest solution. The solution In the demo's controls, check that container query units is selected. Click and hold the container. Watch as the element smoothly transitions to the opposite side of the parent container. Try changing the element dimensions using the sliders, or resize the parent with the resize handle on its bottom right. It still works! Here's the gist when we only need to transition to the opposite side of the parent horizontally. .parent { container-type: inline-size; } .element { transition: translate 200ms ease-out; } .parent:active .element { translate: calc(100cqi - 100%); } If we want to transition vertically or in both directions, we'll need the size value for our container-type so that containment is applied to the block and inline directions. The example below translates the element along the y-axis. .parent { container-type: size; } .element { transition: translate 200ms ease-out; } .parent:active .element { translate: 0 calc(100cqb - 100%); } By setting a container-type on the parent, the element is able to access the parent size via container query length units: 1cqi is 1% of the inline size. 1cqb is 1% of the block size. Notice that we're using logical properties instead of physical ones. If this isn't familiar territory, I recommend Ahmad's excellent Digging Into CSS Logical Properties article to learn more. 100cqi is the full inline size of the parent container. We can recall from earlier that a transform percentage reflects the element's dimensions. Once we subtract 100% from that container query unit, the element can gracefully transition to its proper position on the opposite side of the container. Take a moment to enjoy the wonder and magic that is modern CSS. Helpful resources Container Queries and Units How to create high-performance CSS animations Order in CSS transformations – transform functions vs individual transforms Digging Into CSS Logical Properties
Hey there. It has been a minute since my last post. I was semi-recently tagged by Zach Leatherman to (optionally) participate in this year's Blog Questions Challenge. I had planned on doing it then. But life really hit hard as we entered this year and it has not let up. Energy dedicated to my personal webspace has been non-existent. I am tired. Hopefully this post can help shake off some of the rust, bring me back to writing and sharing with you lovely folks. I won't be tagging anyone to do this challenge. However, if you're inspired to write your own after reading mine, I'd love for you to share it with me. Why did you start blogging in the first place? Blogging has always been a part of my web experience. Earliest I can remember is building my band a GeoCities website back in high school. I'd share short passages about new song ideas, how last night's show went, stuff like that. I also briefly had a Xanga blog running. My memory is totally faded on what exactly I wrote in there—I'm not eager to dig up high school feelings either—but fairly certain all of those entries are just lost digital history. Having an "online journal" was such a fresh idea at the time. Sharing felt more natural and real before the social media platforms took over. [blows raspberry] I've completely dated myself and probably sound like "old man yells at cloud" right now. Anyway, I pretty much stopped blogging for a while after high school. I turned my efforts back to pen on paper, keeping journals of lyrics, thoughts, and feelings mostly to myself. My dev-focused blogging that you may be familiar with really only spans the last decade, give or take a couple years. What platform are you using to manage your blog and why? At the moment and the forseeable future, I'm using 11ty. I published a short post about migrating to 11ty back in 2021. I still feel the same sentiments and still admire those same people. And many new community friends as well! Have you blogged on other platforms before? I've definitely used WordPress but I can't remember what the heck I was even blogging about during that time. Then I switched to just writing posts directly in HTML files and FTP'ing them up to some server somewhere. Pretty silly in retrospect, but boy did I feel alive. How do you write your posts? Always via laptop, never on my phone. I manage posts in markdown files, push them up to a GitHub repo and let that automatically redeploy my site on Netlify. Editing content is done in VSCode. I've debated switching to some lightweight CMS, connecting to Notion or Obsidian, but why introduce any more complexity and mess with what works fine for me? When do you feel most inspired to write? Typically I'll write up a post about something new I discovered while on my wild coding escapades, whether at work or in my free time. If I have trouble finding solutions to my particular problem on the world wide webs, I'm even more inclined to post about it. Most of my ideas are pursued on weekends, but I've had some early morning or late night weekday sessions. What I'm trying to say is that anytime is a good time for blogging. It's like pizza when it's on a bagel. Do you publish immediately after writing, or do you let it simmer a bit as a draft? It depends. If I had been writing for a long period of time, I find it best to take a breather before publishing. When I feel ready, I'll post and share with a small group for feedback, find grammatical errors. Then I eventually add it to whatever social channels feel right. Used to be Twitter, but straight up screw that garbage temple. I'll likely post on Bluesky, toot on Mastodon. Other times I'll slap a new post on this site and not share it on any socials. Let the RSS feeds do their magic. What's your favorite post on your blog? I don't know if I have a favorite. Can I love them all equally? Well, besides that CSS Marquee one. Damn that blog post for becoming so popular. Any future plans for your blog? Once things settle down in life, I think I'll be ready for a redesign. I had a blast building the current version inspired by Super Mario Wonder. Until then? More blogging. It won't be super soon, but I do have a few zesty article ideas percolating in this old, tired brain.
I recently stumbled on a super cool, well-executed hover effect from the clerk.com website where a bloom of tiny pixels light up, their glow staggering from the center to the edges of its container. With some available free time over this Thanksgiving break, I hacked together my own version of a pixel canvas background shimmer. It quickly evolved into a pixel-canvas Web Component that can be enjoyed in the demo below. The component script and demo code have also been pushed up to a GitHub repo. Open CodePen demo Usage Include the component script and then insert a pixel-canvas custom element inside the container it should fill. <script type="module" src="pixel-canvas.js"></script> <div class="container"> <pixel-canvas></pixel-canvas> <!-- other elements --> </div> The pixel-canvas stretches to the edges of the parent container. When the parent is hovered, glimmering pixel fun ensues. Options The custom element has a few optional attributes available to customize the effect. Check out the CodePen demo's html panel to see how each variation is made. data-colors takes a comma separated list of color values. data-gap sets the amount of space between each pixel. data-speed controls the general duration of the shimmer. This value is slightly randomized on each pixel that, in my opinion, adds a little more character. data-no-focus is a boolean attribute that tells the Web Component to not run its animation whenever sibling elements are focused. The animation runs on sibling focus by default. There's likely more testing and tweaking necessary before I'd consider using this anywhere, but my goal was to run with this inspiration simply for the joy of coding. What a mesmerizing concept. I tip my hat to the creative engineers over at Clerk.
Imagine the following section on a website: A collection of elements, like a series of cards with marketing information, are presented in a grid display. The elements are arranged in rows of three. When there are an odd number of elements left over, they will be center-aligned horizontally. There are a few ways to accomplish styling such a layout. Controlling Leftover Grid Items with Pseudo-selectors by Michelle Barker shares a clever CSS Grid solution. But here's a twist: What if the centered odd number of elements should appear in the first row instead of the last? I've included a CodePen demo at the end of this article if you'd like to jump ahead. Otherwise, continue on a journey of style discovery. Grid Stacks Is it a trapezoid grid? Brick grid? Grid pyramid? Pyragrid? For the sake of this article, I ultimately picked a more generic name, calling it Grid Stack. Here's how we'll build a Grid Stack that contains five cards displayed in a three-column grid. .grid-stack { display: grid; grid-template-columns: repeat(6, 1fr); > * { grid-column-end: span 2; } > :first-child { grid-column-start: 2; } } CSS nesting is being used here, which is newly supported across major browsers. Not feeling ready for that yet? We can move the nested rules into their own top-level rulesets. They just need to start with the parent selector name, i.e. .grid-stack > * { } The parent grid-stack container produces a template with six columns. Notice that the grid-template-columns repeat count is double the amount of columns we want visually present in each row. Each child element will then span across two columns instead of one. Finally, the first child element is aligned to the start of the second column. The result is a visually centered top row. Grid lines (enabled in dev tools) help show where each child element is positioned on the grid. Variations So far, the styles we've created only apply when there are five cards positioned across three columns. We may want different variations depending on our designs. Three cards displayed in two columns? Seven cards in four? Let's tweak the above ruleset to utilize a CSS variable for the grid-template-columns repeat count. Recall that this value should be twice the amount of expected columns. .grid-stack { display: grid; grid-template-columns: repeat(calc(var(--columns) * 2), 1fr); > * { grid-column-end: span 2; } > :first-child { grid-column-start: 2; } } The --columns value gets doubled as it passes through the CSS calc() function. Now we're able to define the preferred amount of columns directly on the parent container. <div class="grid-stack" style="--columns: 2"></div> <div class="grid-stack" style="--columns: 3"></div> <div class="grid-stack" style="--columns: 4"></div> Demo Open CodePen demo Bonus! Pyramid stacks In the above demo, you may have discovered some configurations for the Grid Stack that result in a pyramid-style stack. Maybe now we can call it a pyragrid? Still not sure about that one... Anyway, to achieve this layout involves a few extra ingredients. We'll need to adjust the grid-column-start position of the first element in each row. Let's jump right to the last example with the grid-stack-15 selector: .grid-stack-15 { --columns: 5; > :first-child { grid-column-start: 5; } > :nth-child(2) { grid-column-start: 4; } > :nth-child(4) { grid-column-start: 3; } > :nth-child(7) { grid-column-start: 2; } } This calls for a five-column grid visually, so it sets --columns: 5. Recall that this value gets doubled and outputs a template of ten columns. We'll nudge the first item in each row with grid-column-start. The top row element's start position is equal to the --column value. Subsequent rules will decrease this value by 1. It's surely possible to develop a Sass or PostCSS function that could dynamically generate this CSS output but that seemed a bit overkill for the demo. As an added bonus, check out Temani Afif's Stack Overflow answer that styles elements in a pyramid using float and shape-outside. Very cool! Limitations Each layout variation expects a specific odd-number of child elements to be rendered. I have explored ways of automatically adjusting the layout based on the element count but there were too many edge cases to consider. It created more problems than it solved. Additionally, while these layouts work nicely on a wider viewport, it may not fare as well where less space is available. A media or container query ruleset can ensure our content adapts appropriately, but it certainly couldn't be a one-size-fits-all conditional set of styles. From the community Updated on September 5th — Kevin Powell reached out on Mastodon and shared a CodePen Example that uses :has(:nth-child():last-child) to result in this layout. I certainly dig the approach! Keep in mind that the same aforementioned limitations still apply.
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Four years ago, I wrote “How to pick the least wrong colors.” The gist is: picking a categorical color palette is an optimization problem. There’s no such thing as the right colors. But if you use the right cost function, and the right kind of hill climbing, you can at least get the least wrong ones. Since the original post I’ve been slowly picking away at improvements and new approaches. Now that we’re past the singularity, I’ve put a few coding robots on the job. It’s reassuring that many of my assumptions were good ones! The robots have been able to improve the code, bridging some of the gaps in my own knowledge. Today, I’m publishing an updated version of the algorithm as an npm package, along with a fancy GUI version. While there’s still more to do, I’m proud of how far I’ve been able to take it. What’s new New evaluators More controls The public API and a CLI What’s improved The annealing algorithm Configurable color space and distance metric The results One more thing Acknowledgements What’s new New evaluators Almost as soon as I published the first version, I realized that the cost function lends itself really well to modularity. Beyond my initial evaluation functions, I could design new ones, and provide a framework for anyone to plug in their own. As a recap, my original criteria for good categorical colors, mapped to evaluation functions: Similarity — a way of measuring the similarity of one palette to another, useful for providing art direction and getting brand alignment Energy — the colors should be different from each other so they aren’t liable to be confused from one another Range — the differences between the colors should be consistent so unintended groupings don’t appear Color vision deficiency — simulating the colors under different types of color blindness (red-green, blue-yellow, partial to full tritanopia) Here’s the new evaluators: JND — strongly reject palettes that have two or more colors that are too similar Avoid — the mirror image of the similarity evaluation, push colors away from a user-defined set Contrast — compares colors, keeping them above the WCAG AA color contrast floor. Can be used with a background color to maintain contrast on a chart’s background Saliency — uses color naming study data to prefer colors that are easy to name Name difference — the mirror image of saliency, avoiding colors that share names Each of these evaluators can be weighted, indicating the kinds of tradeoffs and priorities you’d like for your color palette. Additionally, the whole evaluator system is pluggable: you can define your own evaluators and have them drive the optimizer! More controls Colors can now be fixed in place, or pinned to a particular order, making it easier to load in existing palettes and optimize all or just some of the colors. Individual channels of each color can be locked, too, meaning you can keep the saturation or hue of a color fixed while optimizing its lightness. This works in any color space. The public API and a CLI The whole package is now a proper library, with a public API. This means: 1. the whole thing is now distributable through npm, with proper versioning, 2. there’s a CLI, making it much more ergonomic for both humans and agents. The API allows for full configuration of the algorithm, as well as loading in colors to optimize. Output can be in raw color values, CSS properties, or DTCG JSON. There’s also a new reportJndIssues endpoint that allows you to evaluate palettes without optimizing them, which is useful to compare a generated palette to commonly-used ones (like Observable, d3, IBM Carbon, and more). What’s improved The annealing algorithm When I wrote the initial algorithm in 2022, I had just learned about simulated annealing. I’ll be honest: I don’t know much more today than I did then. But with AI-assisted research, I was able to solve some questions I had about the initial implementation. Now, the algorithm picks the correct starting temperature based on some random initial samples. Mutation also happens in a scaled manner, so colors change less towards the end of the optimization schedule. Iterations can be capped to prevent very long runs, and the whole thing is much, much more performant. Configurable color space and distance metric The first version of the algorithm worked in RGB space. Now, it defaults to okhsl, but even this is configurable. Individual channels can be constrained to dial in the palette’s boundaries. Also, you can choose which color distance metric you’d like to use (but the library uses CIEDE2000 by default). This flexibility is powered largely by a move from chroma.js to culori. I’ve learned a ton about color spaces since 2022, so being able to mix and match color spaces with distance metrics has been extremely useful. The results The category-colors library reliably produces better results than other palette-generating tools and industry-standard color palettes. Compared to other palette-generating tools, category-colors has more control. Palettailor, for example, optimizes for pure color difference, without accounting for color vision deficiency. QualPal brings some of the optimization parameters, but doesn’t allow for steering towards or away from arbitrary colors. Scores at 8 colors ΔEMinimum ΔEworst of CVD Name differenceMinimum Uniformitylower is better category-colors 22.6 ±1.6 13.7 ±2.0 0.35 ±0.14 best in column 0.30 ±0.02 best in column QualPal 1.1.0 24.7 21.8 best in column 0.10 0.44 Palettailor 26.6 ±2.4 best in column 4.5 ±1.7 0.34 ±0.16 0.34 ±0.04 Colorgorical 15.8 ±3.3 4.1 ±1.6 0.09 ±0.06 0.42 ±0.03 All numbers are at 8 colors. Rows with ± are mean ± standard deviation over 10 palettes; rows without are deterministic and produce one palette. category-colors and Palettailor are 10 independent runs on the same seeds; Colorgorical’s row is 10 palettes from its authors’ own sampling script at equal criterion weights. QualPal was run with CVD on, matched bounds, and takes no seed. Name difference is Heer & Stone’s 1 − cosine; Colorgorical’s own interface reports a Hellinger distance instead. Shaded cells are the best value in their column. Compared to industry-standard palettes, category-colors can produce more optimal palettes, especially at high cardinality. Scores at 8 colors ΔEMinimum ΔEworst of CVD Name differenceMinimum Uniformitylower is better category-colors 22.6 ±1.6 best in column 13.7 ±2.0 best in column 0.35 ±0.14 0.30 ±0.02 best in column Okabe–Ito 21.3 8.8 0.06 0.34 Observable 10 18.4 0.6 0.40 0.34 Tableau 10 18.1 3.2 0.24 0.32 d3 category10 16.2 1.6 0.84 best in column 0.40 ColorBrewer Set3 13.7 1.9 0.16 0.32 IBM Carbon 12.8 5.0 0.11 0.34 Same run: 8 colors, 10 trials. Reference palettes are deterministic, so they're single values. Shaded cells are the best value in their column. One more thing I’ve built a UI that consumes the package and makes it easy to generate and optimize palettes. This has been the biggest request since I published the initial essay, so it’s the thing I’m excited to share. It’s ridiculously overengineered, but hey, what else are personal projects for? Acknowledgements Many measurements come from published research: Gaurav Sharma, Wencheng Wu and Edul Dalal for CIEDE2000; Gustavo Machado, Manuel Oliveira and Leandro Fernandes for the color vision deficiency simulation; Maureen Stone, Danielle Albers Szafir and Vidya Setlur for the size-dependent just-noticeable-difference result; Jeffrey Heer and Maureen Stone, whose color naming models and the c3 data from the Stanford Visualization Group power both the saliency and name-difference evaluators. Existing palettes: Masataka Okabe and Kei Ito’s Color Universal Design set; Matthew Petroff’s sequences; and Mark Harrower and Cynthia Brewer’s ColorBrewer. Other generators laid a lot of the groundwork: Kecheng Lu and colleagues (Palettailor), Connor Gramazio, David Laidlaw and Karen Schloss (Colorgorical), Johan Larsson (QualPal), and Chin Tseng, Arran Zeyu Wang, Ghulam Jilani Quadri and Danielle Albers Szafir (CatPAW). Andrew McNutt, Maureen Stone and Jeffrey Heer’s color-buddy has also been indispensable. Finally, Dan Burzo’s culori made it easy to make this library colorspace-agnostic.
This is part of a new experiment I started in an effort to document the process of making Niche design.
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Users parse a layout before they read its labels. Whitespace, borders, alignment, color, and motion determine what belongs together. When these cues fight the content, users attach the label, price, warning, status, or action to the wrong object. Proximity, similarity, enclosure, and the other Gestalt cues guide the eye, snapping visual chaos into clarity.
I miss this. Visiting a mill is such an enjoyable, often inspiring experience, yet I don’t do it as much as I used to. Perhaps because once you’d done one worsted weaver it’s hard to justify more. But we’ve never done silk. I did go to Vann... > Read more