Recently I gave a talk about pointfree style programming at the JS Poland Conference. I decided to turn some of the ideas I mentioned during the talk into a blog post!

What is pointfree style?

It’s easiest to explain pointfree style by showing a small example. Let’s say we have this array of objects representing mountains:

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const mountains = [

{ name : 'Mount Everest' , height : 8848 },

{ name : 'Mont Blanc' , height : 4808 },

{ name : 'Kazbek' , height : 5033 },

];



As you know, you can use array methods such as map or reduce to run some calculations on this array.

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const names = mountains.map( mountain => mountain.name);

const totalHeight = mountains

.map( mountain => mountain.height)

.reduce( ( result, height ) => result + height, 0 );



Both of these methods are higher-order functions - they accept a function as an parameter. In both cases we create an anonymous function using arrow function syntax and pass it as an argument. Now let’s make those two lines more pointfree.

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mountains.map(prop( 'name' ));

mountains.map(prop( 'height' )).reduce(add, 0 );



What happened here? I replaced arrow functions with small, self-explaining functions such as prop and add . These functions come from a library called ramda, but you could easily write them yourself. As you can imagine, prop('name') returns a function that reads name property from given object and add simply adds two numbers.

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prop( 'name' )({ name : 'Kazbek' });

add( 1 , 3 ));



Pointfree style can be summarized as the following rule: never mention the data. In our example, data refers to parameters of anonymous functions. Instead of using anonymous functions, we use small, very generic functions. We build applications by composing these functions. This forces us to focus on data tranformations instead of on the data itself.

BTW, point in pointfree doesn’t refer to . that is part of method call syntax. It comes from category theory, where points are elements of sets. Pointfree in this context means that you focus on transformations (morphisms) between set elements (points) instead of on the points themselves.

Partial application

There are two very important concepts that make pointfree style possible. The first one is called partial application. I’ve already used partial application in this article. It happened when I called prop('name') . Logically, prop takes two arguments: a property name and an object:

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prop( 'name' , { name : 'Kazbek' });



However, we used it as if it was a single argument function: prop('name') . By doing this, we’ve partially applied prop . The result is a function that will wait for the second argument and only evaluate once it receives it.

But wait, if I only provided one argument to two argument function, it will still evaluate - undefined will be passed as the second argument, right? Well, it’s true unless the function is curried. Currying is the process of taking a multi-argument function and transforming it into a single argument function.

Here is a simplified, multi-argument version of prop - it can’t be partially applied:

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const prop = ( propName, object ) => object[propName];



And here is a curried version:

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const prop = ( propName ) => (object) => object[propName];



Do you see the difference? The second version is indeed a single argument function which returns another single argument function. You don’t need to curry your functions manually - you can use curry function from ramda instead.

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const prop = curry( ( propName, object ) => object[propName]);



Function composition

Another concept essential for pointfree style is function composition. I wrote a separate article about, so please take a look if you are not familiar with the concept.

Application in RxJS

Ok, I promised you some RxJS code 😉 Let’s start with a simple example. Upon clicking the breedsFetchEl button we want to fetch some data from Dog API and present it in breedsListEl div. Easy peasy.

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const click$ = fromEvent(breedsFetchEl, 'click' );

const breeds$ = click$.pipe(

switchMap( () =>

ajax.getJSON( 'https://dog.ceo/api/breeds/list/all' )),

map( result => Object .keys(result.message).join( ', ' ))

);

breeds$.subscribe( breeds => breedsListEl.innerText = breeds);



Let’s convert it to pointfree style. We will focus on the anonymous function inside map . Let’s try to figure our what’s going on there:

First, message property is read from result .

property is read from . Next, its value is passed to Object.keys function.

function. Finally, we call join on the value returned by that call.

We don’t like method calls in functional programming - they are not composable. Let’s first replace the third step with a function call. We will use join from ramda .

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map( result => join( ', ' , Object .keys(result.message)))



Property access also comes from the OOP word, so let’s change it to a function call. This time, let’s use prop from ramda .

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map( result => join( ', ' , Object .keys(prop( 'message' , result))))



Now this looks familiar. We have three nested function calls. We call the first one and pass the result to the second one. The result of the second one is passed as an argument of the third one. This is exactly what function composition is. Let’s use pipe to replace the anonymous function with a function composed from these three functions.

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map(

pipe(

prop( 'message' ),

Object .keys,

join( ', ' )

)

)



But wait, prop and join are two argument functions and now we partially apply them! How is this possible? The answer to this is that ramda functions are really clever. They are curried by default. However, they do also work as expected when called with multiple arguments.

More advanced example

Let’s now take a look at a slightly more complex scenario. We have a text field ( dogNameInputEl ) and we want to show dog images (inside dogImageEl ) based on breed names entered into this field. We want the image to update as you type, but we don’t want to overload the server with request. Hence, we will only send the request if breed name’s length exceeds 2 and we will debounce calls.

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const nameInput$ = fromEvent(dogNameInputEl, 'input' );



const image$ = nameInput$.pipe(

map( () => dogNameInputEl.value),

filter( name => name.length >= 3 ),

debounceTime( 500 ),

mergeMap( name =>

ajax.getJSON( `https://dog.ceo/api/breed/ ${name} /images/random` )),

map( result => result.message)

);



image$.subscribe(

imageUrl => dogImageEl.setAttribute( 'src' , imageUrl));



Cool, let’s deal with this example line by line. The first operator maps input events to actual values typed into the text field.

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map( () => dogNameInputEl.value)



We need a function that ignores its input and always returns dogNameInputEl . Then we could pass its result to prop('value') . It turns out that there is such function in ramda . It’s called… always !

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map(pipe(always(dogNameInputEl), prop( 'value' ))



Next line filters input values so that we only process those that are longer then 2. It boils down to function composition again. First, we calculate string length. You guessed right, there is a function called length in ramda that we can use. Second, we compare the result with 3. ramda has a function called gte . However, if we used it like this gte(3) the we would get a function that returns true if 3 is greater then or equal to its argument. Therefore, we need to swap gte ‘s arguments. flip is a function which does exactly that!

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filter(pipe(length, (flip(gte))( 3 )))



There is no anonymous function in debounce , so we can skip it. Next, mergeMap transforms breed name to a response object retrieved from the server. Again, we can use function composition. First, we transform the name into an URL. Next, we pass the URL to ajax.getJSON . Transforming the name into an URL is achieved using template strings. We could compose this using ramda ‘s functions but the result would not be readable at all. In such case, it’s better to create a helper function and simply use it inside pipe . It’s not super pointfree, but code readability is more important (another approach would be to use order based string formatting library, such as sprintf-js ).

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const getImageUrl =

(name) => `https://dog.ceo/api/breed/ ${name} /images/random` ;



mergeMap(pipe(getImageUrl, ajax.getJSON))



Finally, the last line simple extracts message property from the result. I’m pretty sure you already know how to do that 😉 The end result will look like this:

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const image$ = nameInput$.pipe(

map(pipe(always(dogNameInputEl), prop( 'value' ))),

filter(pipe(length, (flip(gte))( 3 ))),

debounceTime( 500 ),

mergeMap(pipe(getImageUrl, ajax.getJSON)),

prop( 'message' )

);



Summary

What do you think about pointfree style? In my opinion, it’s a great programming practice, but one that has to be applied with caution. In general, it makes your code more concise and eliminates the boilerplate of anonymous functions. More importantly, it forces you to think about your program as a composition of small, generic building blocks (functions). Pointfree style lets you experience the full power of functional programming!

However, pointfree shouldn’t be applied at all cost. In some cases, it might make the overall readability of code much worse. What’s more, if you’re working in a team, you have to keep in mind that such style of writing code might be unfamiliar to others.

Don’t hesitate to share your opinion about pointfree style in comments section!

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