Improving Your CSS with Parker

Written by Harry Roberts on CSS Wizardry.

Parker is an absolutely fantastic, beautifully simple static analysis tool that gives you some very insightful metrics about your CSS files. Parker is built and maintained by Katie Fenn, a developer from England who has since become a friend.

I use Parker almost daily, and regularly go through it with my clients and workshop attendees. Parker surfaces some really interesting numbers, and if you know what they represent, you can draw some really valuable insights about your CSS from them.

(As an aside, I have a pretty cool story about Parker:

I was delivering a workshop for a company in the UK a year or two ago, when a woman in attendance asked me Do you ever use Parker? My answer was an enthusiastic Yes! I use Parker all the time! Do you?! , to which she replied Yeah… I built it. That was how/when I met Katie.)

Okay. Let’s go.

If you haven’t got it installed already, you’ll want to do that first. Parker ( parker ) is a command line tool, which can be installed ( install ) globally ( -g ) using npm ( npm ):

$ npm install -g parker

You can then run Parker against a compiled stylesheet like so:

$ parker path/to/stylesheet.css

I’d recommend running your current project’s CSS file through Parker right now. If you don’t have a stylesheet to hand, this one will work pretty well. That one will give you some output like this:

Total Stylesheets: 1 Total Stylesheet Size: 37178 Total Rules: 260 Total Selectors: 365 Total Identifiers: 487 Total Declarations: 522 Selectors Per Rule: 1.4038461538461537 Identifiers Per Selector: 1.6821917808219178 Specificity Per Selector: 9.293150684931506 Top Selector Specificity: 30 Top Selector Specificity Selector: .c-score[data-score^="0."] Total Id Selectors: 0 Total Unique Colors: 25 Unique Colors: #FFFF00,#000000,#C0C0C0,#F3F3F3,#333333,#378BB5,#FFFFFF,#666666,#E4E4E4,#FF2100,#FF4200,#FF6300,#FF8400,#CC9E00,#999600,#668F00,#338700,#317CA1,#CC0000,#ABC123,#98AB1F,#999999,#CCCCCC,#FFFF88,#4099C5 Total Important Keywords: 60 Total Media Queries: 5 Media Queries: screen and (min-width: 1024px),screen and (min-width: 1280px),screen and (min-width: 720px),screen and (min-width: 480px),screen and (min-width: 1200px)

This is the CSS file that I will be using as an example throughout this article.

We’re not going to look at every single one of these metrics in this blog post. Instead, we’ll look at the slightly more abstract data and work out what it represents, and what insights it gives us. We have to dig a little deeper for the implicit meaning in a lot of these values, but once we’ve worked out what we’re looking for, we open up a whole new world of knowledge.

Before we get too deep into things, there are a few of things we need to be aware of when using Parker:

This article was written in context of Parker version 0.0.10 . If any major changes are released, I will endeavour to update this article accordingly. Parker reports mean values. It would be quite nice to know that ‘most of your selectors have class-level specificity’, rather than ‘the average specificity across all of your selectors is roughly that of a class’. A subtle but significant distinction. Unfortunately Parker currently reports specificity incorrectly. Katie and I are in active discussions about how best to tackle this, but for now it’s technically incorrect. In real terms—unless you have hellishly nested selectors using more than 10 classes—it shouldn’t impact you too much, but it’s certainly something to be aware of.

With these points in mind, please remember: Parker is not failsafe; it is not infallible and nor does it claim to be. Parker is best used as a rough guide; a finger in the air. Parker’s job is just to present you with the numbers; it’s down to you to know what those numbers represent, and what they mean for your CSS.

That’s what this article is for.

Total Rules, Selectors, Identifiers, Declarations

All of these metrics are very self explanatory, and don’t need any special mention. However, using two of these metrics we can actually polyfill a very useful one that isn’t present (Katie and I are discussing its addition).

If we divide Total Declarations by Total Rules, we are left with the mean number of declarations per ruleset:

Total Declarations ÷ Total Rules = Declarations Per Ruleset

Given our data set, we’re left with:

522 ÷ 260 = 2.007692308

We have an average of 2 declarations per ruleset.

What this tells us is how large each of our rulesets are: rulesets with lots of declarations are probably quite monolithic, and could/should probably be broken down into smaller composable responsibilities.

Take this example of an overly loaded ruleset:

.btn-login { display: inline-block; padding: 2em; background-color: green; color: white; }

There are a number of problems present here. Firstly, the name btn-login describes a very specific use case, making it very difficult to reuse. Secondly, this is a pretty monolithic ruleset—it handles everything about this button, mixing up structural and cosmetic responsibilities. Instead, we could break this out into:

.btn { display: inline-block; } .btn--large { padding: 2em; } .btn--positive { background-color: green; color: white; }

Three smaller and more composable rulesets, each with a smaller number of declarations. CSS like this likely adheres to the Single Responsibility Principle, meaning we have very well defined and encapsulated rulesets that can be combined and composed in a very modular fashion.

This is how the Declarations Per Ruleset metric comes in handy.

Selectors Per Rule

Selectors Per Rule: 1.4038461538461537

Selectors Per Rule is pretty simple. The following CSS has one selector per rule:

.c-btn { display: inline-block; padding: 12px; } .c-btn--small { padding: 6px; } .c-btn--large { padding: 24px; }

This CSS has two selectors per rule:

h1, .u-h1 { font-size: 3rem; } h2, .u-h2 { font-size: 2rem; } h3, .u-h3 { font-size: 1.5rem; }

Straightforward enough, but what does this actually tell us?

Well, we want a number as close to one as possible. Lots of selectors per rule suggests that we’re applying the exact same declarations (styles) to a number of different selectors. Perhaps we could create a single catch-all selector to handle all eventualities, making our CSS smaller, and abstracting patterns out into more reusable selectors. Let’s look at an example of some poorly written CSS that has lots of selectors per rule:

input[type="text"] input[type="email"], input[type="password"], textarea { border: 1px solid #ccc; background-color: #fff; color: #333; padding: 4px; }

As we add more input types to this site, that list of selectors continues to grow. A much simpler and shorter solution would be to tie all of this information up into a single reusable class, for example:

.c-input-text { border: 1px solid #ccc; background-color: #fff; color: #333; padding: 4px; }

So no matter if the input handles email addresses, regular text, passwords, or an input type yet to be invented, we don’t need to maintain a very implementation-specific list of selectors.

We often end up with lots of selectors per rule for two key reasons:

Fear of using classes in our markup: The surprisingly still-persistent fear and avoidance of judicious use of classes in our HTML often leads to developers creating (and subsequently maintaining) unwieldy lists of selectors that are all chained to the exact same declarations. By adopting a more class-based architecture, we can begin to recycle these rules in a much more terse and practical way. Using Sass’ @extend : Sass’ @extend functionality has long been considered an anti-pattern for a number of reasons (please see Extending silent classes in Sass , When to use @extend ; when to use a mixin , Mixins Better for Performance ). @extend transplants selectors from one part of your project to all converge on another. This has plenty of its own problems—detailed in the linked articles—but it ultimately gives us a long, unwieldy list of selectors chained to the same declarations; it increases our Selectors Per Rule.

In the extreme, it’s not uncommon to see @extend being abused by developers striving to never repeat the same declaration twice, leading to CSS that looks like this:

Damn! I wouldn't like to be the one who maintains this 125 lines CSS selector! pic.twitter.com/0jAEb2h8VF — Gaël Métais (@gaelmetais) 7 February 2015

A confusing mess of unrelated selectors all grouped together via coincidence as opposed to reason. This fragments style information across your project, creates unusual relationships and dependencies, removes encapsulation, and makes using DevTools far more difficult:

Identifiers Per Selector

Identifiers Per Selector: 1.6821917808219178

Identifiers per selector is not to be confused with IDs. Identifiers per selector is a measure of parts per selector. For example, take the following CSS:

.c-btn { /* 1 identifier */ } .c-btn:hover { /* 2 identifiers */ } .c-widget--large .widget__title { /* 2 identifiers */ } header nav ul li a { /* 5 identifiers */ }

Nesting, qualifying, and pseudo selectors all increase the Identifiers Per Selector metric, and we should strive to keep this number as small as possible. Identifiers Per Selector is effectively our Cyclomatic Complexity.

Having a high number of identifiers per selector brings a few problems:

Increased specificity: The more selectors we have in our compound selector, the higher the specificity will be. Specificity is best kept as low as possible.

The more selectors we have in our compound selector, the higher the specificity will be. Specificity is best kept as low as possible. Decreased portability: It’s harder to move styles around the view when they’re tightly bound to a specific DOM structure.

It’s harder to move styles around the view when they’re tightly bound to a specific DOM structure. Increased fragility: The more parts in a compound selector, the more chances there are of something going wrong.

The more parts in a compound selector, the more chances there are of something going wrong. Increased filesize: A minor issue, but any bytes added to your selectors cannot be reclaimed by a minifier—they’re dead weight.

For further reading about the problems with long selectors, please refer to my article Keep your CSS selectors short .

We want to see an Identifiers Per Selector value between 1 and 2 (remember, this being a mean value means we can end up with decimals). We can’t have smaller than 1 by definition. Anything over 2 means that, on average, every selector in the codebase is the equivalent to everything being nested or qualified at least once.

Our selectors should be as short as possible, but as long as necessary, and Parker helps us measure this.

Specificity Per Selector

Specificity Per Selector: 9.293150684931506

As mentioned, specificity is reported slightly incorrectly by Parker, but things should still work okay for the most part.

In CSS, every type of selector has an inherent specificity value:

Universal selector: 0/ignored

0/ignored Element selectors: 1

1 Class selectors, attribute selectors, pseudo selectors: 10

10 IDs: 100

When we look at a complex/compound selector, we add together all like selectors (i.e. all IDs, all classes, all elements) and present the overall specificity as three separate integers. For example:

#header #nav li a {}

…has a specificity of 200, 0, 2 because we have two IDs at 100 each, zero classes at 10 each, and two elements at 1 each. Unfortunately, Parker reports this as 202 as a result of adding the three integers together.

.c-btn:hover {}

…has a specificity of 0, 20, 0 because we have zero IDs at 100 each, two class-like selectors at 10 each, and zero element selectors at 1 each.

input[type="text"] {}

…has a specificity of 0, 10, 1 because we have zero IDs at 100 each, one pseudo class at 10 each, and one element at 1 each. Unfortunately, Parker reports this as 11 as a result of adding the three integers together.

Because we are (or should be) working to a class-based architecture, we want to see a number as close to 10 (the specificity of a single class) as possible. Remember, however, that Parker reports mean values, so if you have lots of element selectors or (heaven forbid) ID selectors, your reported value may be skewed as a result.

Because it’s inevitable that we’ll have some nested selectors, and will certainly have pseudo selectors attached to some of our classes, I would typically deem a Specificity Per Selector value of anything up to 20 as being ‘safe’. Anything over 20 means that, on average, every selector in the codebase is the equivalent to two classes worth of specificity.

If your value is over 20, you’ll want to remove any/all IDs you have in the project, and look to reduce all unnecessary nesting and qualifying to get your selectors as flat as possible.

Total ID Selectors

Total Id Selectors: 0

This number should be exactly zero, as there is absolutely no good reason whatsoever to use IDs in CSS. They are infinitely more specific than classes, and instantly impossible to reuse: both of these traits are diametrically opposed to the pursuit of modular and reusable CSS.

Further reading: When using IDs can be a pain in the class… , Hacks for dealing with specificity .

Total Unique Colors

Total Unique Colors: 25

This metric is pretty subjective, and will depend a lot on your project. If you’re working on a large site with lots of themes and sub-themes, expect to see a relatively large number. If you’re working on a smaller site with a limited obvious colour scheme, be suspicious of larger numbers.

Given the small size of the demo project we’re using for this article, a value of 25 surprises me a little. I should create a design task to look through the project and begin to audit and rationalise my use of colours.

Live update: I actually did just go and explore where all the numerous unique colours were coming from, and I tracked it down to my colour-coded scoring component: the existence of these colours is, thankfully, both intentional and justifiable.

Total Important Keywords

Total Important Keywords: 60

!important isn’t as evil as we like to make out, so if you reported number is not zero, you don’t necessarily need to panic. Just ensure that any instances of !important are only found against your utility classes.

To understand how and when we should use !important , please see my recent article The Importance of !important : Forcing Immutability in CSS .

To get a quick look at where !important is being used in your project, try running this inside of your CSS directory:

$ git grep --break -C 2 "\!important"

This will show you all instances of !important with two lines of context ( -C 2 ) either side of the result. Hopefully the two lines of context allow you to see the selectors that the !important lives inside; if not, just try increasing the number.

Practical Usage

Let me close with some little tips and tricks for getting some real and immediate practical value out of Parker…

The Worst Offender

Initially we’ll want to run Parker over all of our entire compiled project, and get a report for every single line of CSS we have. Not only does this give us a handy project-wide overview of things, it tells us what our worst offender is: it’s our Top Selector Specificity Selector.

This is the current worst selector in our project, so this is the first/next thing we need to fix. Once we’ve refactored that down and removed it, we run Parker again. Now we’ll get a new worst offender, and we refactor that, and so on. This gives us tiny, bitesize chunks of refactoring work where we only ever have to focus on our worst bit of CSS, rather than being over faced with a project’s worth of fixes.

Anomalous Data

Calculating the mean values means that any anomalous data points will skew our results. The problem with means is that if I have one hand in the fire and one hand in the freezer, on average I’m a comfortable temperature. Means are only useful when you’re comparing similar data points, so any outliers will affect the results. This means that running Parker across an entire codebase might not always give us an entirely representative report (if we have a legacy project that has lots of nesting, or IDs, those selectors will pull our mean values a little higher).

To combat this, I often pull out discrete features of the CSS project and run Parker over those in isolation. For example, copy/paste your button styles out of your compiled Stylesheet and into its own buttons.css file, and run Parker over that. This means we can study the quality of our CSS in smaller chunks which has a few key benefits:

We get much better results. As discussed above, we’re comparing like data points, so get more representative metrics. It isolates any potential refactoring work. If Parker suggests we need to rework or refactor anything, at least we’re only dealing with discrete features at a time, and not having to start refactoring our entire project. We can descope certain bits of our CSS. There’s little use having Parker report back on our reset or Normalize.css, so we can exclude any setup or library code.

Parker is a really useful, valuable tool that presents us with some seemingly obvious and simple data. As soon as we understand what these numbers represent, and the principles behind them, we can quickly begin to assess and improve the quality of our CSS.

I’d really recommend running Parker over your existing project(s) right now, and then begin to make it a part of your regular development workflow.

☕️ Did this help? Buy me a coffee!