Sorting out images in Webpack is not too bad up to a point. The url-loader + file-loader combination is usually enough to satisfy needs. However, when you have too many require() for large images, it can take up to 20s or longer to hot-reload after a compile…
Here’s how to mitigate the situation.
Continue readingIf you @import a lot of scss/sass/css files, the style loader can take a looong time to finish loading. How to improve? Lets take a look at what each of them does:
Due to patent issues with newer schemes [1], Huffman Coding remains to be the go-to compression algorithm of the day, being applied in ZIP, JPEG, PNG… and much more.
The core idea of Huffman Coding, is to use shorter codes to represent more frequent characters. As for why we always see a mysterious tree of zeros and ones, well, that’s essentially how computers store anything: with binary codes. Essentially the goal of constructing the Huffman binary tree is: to assign the most frequent characters to the shortest zero/one path, walking from tree root to end of a branch.
How to create such a tree?
It’s fine performing while data is not large. However with data as huge as all countries’ boundaries, GeoJSON freaks out and blocks the whole page.
Questions:
1. What is famo.us? What makes it special?
A JavaScript framework which helps you create smooth, complex UIs for any screen. Stress on the smooth part. Famo.us elements are styled with position:absolute and their positions are defined by matrix3d webkit transforms. This is what makes Famo.us performant.
List of things to probe around and think about:
The main benefit is to avoid unnecessary browser decode.