grunt VS d3

Many web pages use CSS and JavaScript files to handle various features and styles. Each file, however, requires a separate HTTP request, which can slow down page loading. Concatenation comes into play here. It involves combining multiple CSS or JavaScript files into a single file. As a result, pages load faster, reducing the time spent requesting individual files. Gulp, Grunt, and Webpack are some of the tools that can assist you in speeding up the concatenation process. They enable seamless merging of many files during development, ensuring deployment readiness.

Once you build a simple Vite backend integration, try not to complicate Vite's configuration unless you absolutely must. Vite has become one of the most popular bundlers in the frontend space, but it wasn't the first and it certainly won't be the last. In my 7 years of building for the web, I've used Grunt, Gulp, Webpack, esbuild, and Parcel. Snowpack and Rome came-and-went before I ever had a chance to try them. Bun is vying for the spot of The New Hotness in bundling, Rome has been forked into Biome, and Vercel is building a Rust-based Webpack alternative.

Keep scripts independent: Keep your scripts independent of each other to avoid dependency issues. If you need to run one script after another, use a task runner like Gulp or Grunt to define tasks and their dependencies.

Browserify was great at bundling scripts, but what if we need to transform code - Say compile CoffeeScript to JavaScript, for this, a new group of tools for the web was born, which focussed on running code transforms. These are usually called task runners, and the most popular ones are Grunt and Gulp.

What we see, a decade ago, are that many of the "popular" libraries, frameworks, and methods, not surprisingly, have gone by the wayside, a lot that have remained in current code as difficult-to-removemodernize legacy cruft (Bower, Gulp, Grunt, Backbone, Angular 1, ...), and then we have the small minority that are still here. Some that remain have had their utility lessened/questioned by platform and language improvements (jQuery, lodash, ...), but very, very few exist that are the same now as they were then. Another fun historical reference: issue #118 of "JavaScript Weekly" (February 22, 2013) includes a first link out to asm.js.

Grunt.js is a favorite tool of mine, while it's most commonly viewed as a (legacy) build system, I've found it to be a fairly robust CLI framework for designing local and automated tasks and still actively develop tasks to this day.

User script template that acts as module and tries to simulate imports. I built this to help me develop my user scripts, after learning about Grunt, and I thought I should share.

With the pre-processors, you can shrink your CSS and increase reuse through variables. In almost all working cases, it will be an improvement above vanilla CSS. There are also implementations now, via PostCSS, that add vendor prefixes for you. The major drawback is, of course, that you have to compile your CSS beforehand; usually done via part of your tooling such as Grunt or Gulp.

As far as build tools go I remember how popular Grunt was when it was first released, then it was Gulp, and Babel came along to help you add new us features and get them working on older browsers.

Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/

d3 - very power visualization library enabling dynamic visualizations. docs

Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).

D3.js: A robust library to visualize your data and create interactive data-driven visualizations.

They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.

I made this interactive visualization that attempts to show the real-time frequency and location of births around the world. A country’s annual births (i.e. the country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. more populated areas got a greater fraction of the births). Data Sources and Tools Population and birthrate data for 2023 was obtained from Wikipedia (Population and birth rates). Population distribution across the globe was obtained from Socioeconomic Data and Applications Center (sedac) at Columbia University. Data is processed and visualized at a 1 degree x 1 degree resolution, each of which has a different probability of a birth occurring in a specific time period. D3.js was used to create the map elements and html, css and javascript were used to create the user interface.

When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.

Website: D3.js official site

D3js