I’ve posted before about my work for the Web Almanac this year. To make it easier to calculate the stats about CSS selectors, we looked to use an existing selector parser, but most were too big and/or had dependencies or didn’t account for all selectors we wanted to parse, and we’d need to write our own walk and specificity methods anyway. So I did what I usually do in these cases: I wrote my own!
You can find it here: https://projects.verou.me/parsel/
For some of the statistics we are going to study for this year’s Web Almanac we may end up needing a list of CSS shorthands and their longhands. Now this is typically done by maintaining a data structure by hand or guessing based on property name structure. But I knew that if we were going to do it by hand, it’s very easy to miss a few of the less popular ones, and the naming rule where shorthands are a prefix of their longhands has failed to get standardized and now has even more exceptions than it used to. And even if we do an incredibly thorough job, next year the data structure will be inaccurate, because CSS and its implementations evolve fast. The browser knows what the shorthands are, surely we should be able to get the information from it …right? Then we could use it directly if this is a client-side library, or in the case of the Almanac, where code needs to be fast because it will run on millions of websites, paste the precomputed result into whatever script we run.
First off, some news: I agreed to be this year’s CSS content lead for the Web Almanac! One of the first things to do is to flesh out what statistics we should study to answer the question “What is the state of CSS in 2020?”. You can see last year’s chapter to get an idea of what kind of statistics could help answer that question.
Of course, my first thought was “We should involve the community! People might have great ideas of statistics we could study!”. But what should we use to vote on ideas and make them rise to the top?