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Exploring template literal types in TypeScript

This post will explore my train of thought following a question about how I would type an existing function. This code was not used in any production app, but it was a good exercise in working with TypeScript while trying to solve this particular problem.

We will go a bit deeper by using (recursive) conditional types, template literal types, index accessed types, and a suite of other helper types. Previous knowledge of TypeScript is required in order to be able to follow along. Knowing about these types beforehand will also help, but I’ll try to provide links and examples for further reading.

So grab your favorite hot beverage and get ready for a post that goes towards the ‘heavy to read’ end of the spectrum. Experimenting with the code as we go along is encouraged, for example in the TypeScript playground. There is also a link with the solution at the end.

The problem

Let’s assume we have an existing code base, with a general function that reads data from an API. We can pass it the property names that we want to read for that specific object type, and the URL. Might look something like this:

fetchData(properties, url) {...}

Assuming we have a Car object:

type Car = {
    id: number;
    name: string;
    price: number;

We can use our function to fetch a list of available cars, and what properties we need for each:

fetchData('id, name', '/api/cars');

We are specifying that we want the list of cars, but only the id and name properties on them. In our simple example, this is somehow irrelevant. But if you are working with complex objects or large volume of data, this can save a lot of bandwidth and improve the speed of our applications. If we have a large list of complex objects, including just a few properties (vs. all) would make a big difference.

Another possible use case is if you have different clients (web, mobile) that use the same APIs, but they display different data. So this might be useful to fetch what’s needed in each case. There are different ways to implement this on the backend, depending on what technology you are using.

Going back to our function, we can think about this as being used inside an existing code base. Our task at hand would be to create a proper typed version of fetchData, so that it will be easier to use and make our code better.

Return type

This should be straight forward. We want to get a specific type back, so we make the function generic, and specify ourselves what the return type is:

function fetchData<T>(properties: string, url: string): T {...}

Then we can use it as:

const cars = fetchData<Car>('id', '/api/cars')

Now TypeScript will make sure our cars variable has the proper type. It’s a bit tricky that we have to explicitly write this, but there is no easy way out of it. We cannot easily map the type to a string, so this is what we have to settle with. All the popular data fetching libraries have an implementation similar to this.

If we want to make sure developers working in this codebase use the correct type, we could encapsulate this at the API layer in one way or another. For example creating a fetchCars function:

function fetchCars(properties: string) {
  return fetchData<Car>(properties, '/api/cars');

This takes care of the basics, now let’s see about that properties type.

One property

It would be nice to be able to specify only existing properties of a Car when we call this! In that way, we’re sure our function is typed.

First thing I would think of is keyof. This will allow us to get all the keys of a specified type. So if we have something like:

type CarKeys = keyof Car;

It will expand into:

type CarKeys = 'id' | 'name' | 'price';

This happens because those are all the properties that we defined on our Car type above. Any time we add or remove one from the Car type, the keyof derived type will be updated. You can see the official docs for more.

So we update our function to fetch data with this knowledge:

function fetchData<T>(properties: keyof T, url: string): T

This works, we can make calls and get back data with what property we want:

// ✅
fetchData('id', '/api/cars/');

But we can specify only one property at a time, which is not exactly what we want 😅:

// ❌
// Argument of type '"name, id"' is not assignable to parameter of type...
fetchData('id, name', '/api/cars/');

But before we are going to look at how to implement support for multiple properties, we need to get ourselves conformable with some (new) TypeScript features.

Template literal and recursive conditional types

A possible solution to our problem is the use of template literal types and recursive conditional types, introduced in TypeScript 4.1. You can see the release notes for full details, but I’ll try to show some examples so we can better understand them.

Template literal types

Using similar concepts from template literals, we create a type using substitutions:

type Programming = "programming";
type Statement = `love ${Programming}`; // 'love programming'

This is pretty straight forward, but we can explore one additional trick:

type Programming = "programming";
type Reading = "reading";
type Statement = `love ${Programming | Reading}`;

What happens if we use a union operator with a template literal type? It will create all the possible combinations! So this will get expanded to:

type Statement = "love programming" | "love reading";

We can use something a bit more complex as an example to better grasp it. Lets compose some CSS properties:

type CssProperty = "margin" | "padding";
type PropertySide = "top" | "right" | "bottom" | "left";

type Prop = `${CssProperty}-${PropertySide}`;

Which will get expanded to all possible combinations:

type Prop = "margin-top" | "margin-right" | "margin-bottom" | "margin-left" |
            "padding-top" |"padding-right" | "padding-bottom" | "padding-left";

Conditional types

Since TypeScript 2.8 we have conditional types at our disposal. Let’s explore them a bit.

A simple example of this would be (re)creating the NonNullable type. This will remove null or undefined from types:

type NonNullable<T> = T extends null | undefined ? never : T;

As the name implies, you can think of conditional types like an if statement. If the condition is true, resolve to the first type, if not, the second one. If the expression is not that familiar, you can have a quick look at the conditional operator.

In the example above, we check to see if the generic type matches null or undefined and:

  • if true -> we return never
  • if false -> we return the generic type itself

In TypeScript, never is a built-in type representing values that are never observed. In our case, it removes undefined or null:

// string
type OnlyString = NonNullable<string | null>;

// number
type OnlyNumber = NonNullable<number | null | undefined>;

Recursive conditional types

We had conditional types but, up until TypeScript 4.1, we could not recursively reference the type itself. Let’s try to extract the primitive types from an array, also handling the case when we have deeply nested arrays:

type ExtractType<T> = T extends Array<infer U> ? ExtractType<U> : T;

As before, we check to see if the generic type matches something like an Array and:

  • if true -> we return the same ExtractType, but as a type argument we use the type of the Array itself
  • if false -> we return the generic type itself

In order to figure out what the type of the arrays is, we used the infer keyword. It’s like saying take whatever type you find there, and place it in this U variable, so that I can use it later on.

And we can test it out:

// 'string'
let one: ExtractType<[string]>;

// 'string' | 'number'
let two: ExtractType<[string, [number]]>;

// 'string' | 'number' | 'boolean'
let three: ExtractType<[string, [number, [boolean]]]>;

These examples are pretty similar to those from the release notes. Added them here for more context or in case you did not open the links :)

And now we know everything we need to continue.

Multiple properties

Back to our problem. We have the Car type, we used the keyof on it, which works, but only with one property at a time, and we would like to expand this to work for all/any combination of them.

Let’s start the other way around. One solution would be something like this:

type KeysOf<T, Key extends keyof T = keyof T> = Key extends string
    ? `${Key}, ${KeysOf<Omit<T, Key>>}` | Key
    : never;

Lets go through it step by step. We created a generic type with two arguments: the type of the object we want to use and an union with property names of that type. By default, this will be a union of all the property names, like we’ve seen before. In most cases we’ll use the generic type by passing in only the first argument, as most of the time we want to go through all of the properties, which is what the default, keyof T, value does.

Then, we use a conditional type to see if the second generic argument, the Key, looks like a string. This will happen most of the time, for all the properties of our type. When there are no more properties, it will be an empty set, so no string, and we return never. This is our way to make sure we don’t get into infinite recursive calls.

Now, if we still have properties to process, we construct our template literal type: ${Key},${KeysOf<Omit<T, Key>>}. We want the properties to be separated by a comma, so we add it there. Then we use the same type to create a recursive call.

The trick here is to use the Omit helper type. Each time we process a property name, we call the same type recursively, but without the processed property. In this way we handle all the properties one by one, until we call the type with an empty set. In that case, the Key will no longer be a string, so we will return never and stop the recursive call.

type CarWithoutName = Omit<Car, 'name'>;

It is equivalent to the initial Car type, but without a name:

type Car = {
    id: number;
    price: number;

The last thing to add here is a union with the Key itself. This will generate a union with all the possible combinations.

Then we can update our function with our new type:

function fetchData<T>(properties: KeysOf<T>, url: string): T

And this will work pretty well. We can specify any combination of properties that we might want to read:

fetchData('name, price');
fetchData('price, name');
fetchData('id, name, price');
// and so on

If you want to check this, you can use this yourself (or see the TypeScript playground link at the end):

type CarProps = KeysOf<Car>;

It will get transformed into:

type CarProps = "id" | "name" | "price" | "name, price" | "price, name" |
                "id, name" | "id, price" | "id, name, price" | "id, price,name" |
                "price, id" | "name, id" | "name, id, price" | "name, price,id" |
                "price, id, name" | "price, name, id";

There are some ways to solve this without using the second generic argument, but I found this way of doing it more straight forward and we get some extra benefits. Notice that we’ve passed only one generic argument so far, but we can also pass the second to explicitly use only specific keys:

KeysOf<Car, "id">
KeysOf<Car, "id" | "name">

Or just maybe this way of solving it might have been the easiest for me 😅.

Complex (nested) objects

We can further improve on our type. So far we had a simple car, with properties that have primitive values. But in real life, we might have some more complex types. Maybe the car also has an engine:

type Engine = {
  power: number;
  id: string;

type Car = {
  id: number;
  name: string;
  price: number;
  engine: Engine;

And, in case of the engine property, we could do the same thing, specify only what properties we want to read from it. Something like this:

fetchData('name, engine(power)', '/api/cars');

This will mean that we want a list of all the cars, with only the name and engine properties, and on the engine we only need the power property.

In this part we’ll make use of the Record utility type. This helps us check if a type looks like an object, or it is a primitive type. Using Record we create an object-like type, where the first argument will represent all the properties and the second one the type of those properties. So using something like Record<string, any> will create an object that has as properties any string and those can have any value.

As an alternative, we could have used our own Primitive type, or another way to create an object-like type.

Knowing this, we can build on our previous version to include an additional check:

type KeysOf<T, Key extends keyof T = keyof T> = Key extends string
    ? T[Key] extends Record<string, any>
        ? `${Key}(${KeysOf<T[Key]>})`
        : `${Key}, ${KeysOf<Omit<T, Key>>}` | Key
    : never;

We have added even another level to our type. After we check that the Key is a string, we need to see if the type of that property is a Primitive or not. To get that type, we use the T[Key] expression, which is an index accessed type. Then we do a similar thing, depending on the condition:

  • if it looks like an object, we add round brackets and we do a recursive reference to KeysOf, passing in the just extracted index accessed type
  • if it’s not an object, we have the previous code, nothing different here

And this solves the problem of a bit more complex types, as we can see if we check it out:

type CarProps = KeysOf<Car>;

It will get transformed into an even more complex thing:

type CarProps = "id" | "name" | "price" | "engine(id)" | "engine(power)" |
                "engine(id,power)" | "engine(power,id)" | "price,engine(id)" |
                "price,engine(power)" | "price,engine(id,power)" |
                ... 68 more ... | "price,name,id,engine(power,id)";

Yes, 68 more options, it indeed has all the possible combinations and we can use any of them to call our function.


This was an interesting experiment, and it allowed me to play around with template literals and recursive conditional types. They are quite powerful and can provide useful types for our code. This post is a first in a series of “learning in public” style of articles. More will follow :)

If you want to experiment live with this type, you can use this TypeScript playground.

Let me know if you would use something like this in production, or what other interesting ways of solving this problem you have.