My 3 Why TypeScript

The other day I gave a short talk at our local JavaScriptMD meetup: “3 ways to improve your JavaScript with TypeScript,” and I thought writing a summary of it may be a nice way to enliven my blogging.



I’ve programmed in JavaScript for quite some time now. I think I’ve discovered it in early 2000s and played with it because I was curious what is this new Web thing, and what can I do with it.

I was mostly playing with it outside of the job, but never lost a chance to bring it in to add some magic to the company’s website. Then in 2005 I got a full-time and full-stack JavaScript job: on the front-end we had YUI/EXT and in the back-end we had JScript (classic ASP), and since then, even I was also doing things across the stack, I felt mostly like a JavaScript and Web front-end person.

In the last few years I even started a couple of side-projects that I wrote in JS, again both front-end and back-end, where now I had Node. These projects made me think deeper about my JavaScript skills and stack because I was the only one tech person on each of them, and I could pick the best things and ways to build them. (I was not ready to bring in anyone else yet, because I didn’t want to share the risk.)

As of half a year ago, my attitude was that I can do most of the things that frameworks and module loaders do, but just with less overhead in the development process: I was (and still am) quite ascetic when picking my stack.

There was one thing that I began to feel: while JavaScript gave me all the flexibility in the world to build things how I saw fit, it was also leaving me to my own devices when codebases grew beyond of a few files, and I was feeling more and more tensed to change the code to reflect my new understanding of the business logic that I was modeling.

Unit tests helped, and while I was writing a ton of them, I began to worry about them: they are JavaScript code too, aren’t they? At some point I began to feel bogged down by my own, dear, beautiful code…


About a half a year ago I came at Mixbook to help out with a new front-end project. The stack was TypeScript + React, but I decided I’d give it a try because Mixbook culturally wowed me the few times we’ve met in person with Aryk (CTO and cofounder) and a couple other people online.

A month ago, after going to our local JavaScriptMD meetup I was ripe to give a talk on why I found TypeScript so useful to me as a Native JavaScripter®.

In a few bullet-points and a picture

  • A superset of ES.Next + transpiler + type checker: While the first two are valuable too, the latter is what I found to be the biggest thing. It’s that diligent and tireless assistant that helps you when your code grows beyond what you have ever expected.
  • Open Source®
  • Is written in TS: I’m mentioning this not because it sounds geeky, but because I see this as an added bit of guarantee: if its creators use it themselves, they will keep it practical.
  • inference → optional types: Another one of the biggest points about TypeScript, and which make it stand out of the static typing languages (more on this later).
  • ~adjustable level of strictness: A few knobs to adjust the level of how much it’ll let you shoot yourself in the foot.
TypeScript ES6 ES5

Thanks to @basarat for the visual concept.

The 3 ways, in detail

  • read
  • write
  • change


Having types let you see at a glance what a function expects and returns. What is equally important is that they tell the type checker what we intended to say, and because of this it will be able to guide your code so that it does the right things to the input and returns what we expect.

Here is an example from the entry point function of our project:

export function main(container: Element,
                     projectJson: ProjectJson,
                     configJson: ConfigOptionsJson,
                     externalCallbacks: ExternalCallbacks): ApplicationManager {

What is ProjectJson? ConfigOptionsJson? That’s easy to tell because we have them described in real, concrete code:

export interface ProjectJson {
  id?: number;
  creator?: UserJson;
  name?: string;
  pages?: PageJson[];
  photos?: PhotoJson[];
  template?: ProjectTemplateJson;
  intended_product?: ProductJson;

This will help the type checker help us keep the whole thing straight, and will also help the developers see what exactly is that argument.

Because we spend a lot more time reading our code than writing, you can’t overestimate the value of clarity that these definitions give to your team.


Let’s say we want to models a basket for an e-commerce website. I’d begin with something like this:

interface Basket {
  items: Item[],
  lastUpdate: Date | number,

and then I’d say:

interface Item {
  id: number | string,
  name: string,
  quantity: number,
  price: number,

These definitions make the ideas in my head concrete, and not only to me but also to the type checker — the useful assistant that will work alongside with us to keep the code straight with our intentions specified in these declarations. Now when I write the code that works with these data structures, the type checker will guide me towards meeting those intentions.

const basket: Basket = {
  items: [{
    id: 1,
    name: "Pixel",
    quantity: 2,
    price: 2000

function totalAmount(basket: Basket) {
  return basket.items.reduce((memo, item) => {
    return memo + item.quantity * item.price;
  }, 0);

// Here the type checker will tell be able to us immediately that:
// “Property 'length' does not exist on type 'number'.”

console.log("Total amount: " + totalAmount(basket).length);

Writing the code to work with these data structures is where TypeScript’s ability to infer types shines: The code can still be concise, we didn’t need to specify the type of every little thing in the code:

  • because we specified that totalAmount’s argument is of type Basket the type checker inferred that it’s OK to access its items property;
  • because we defined that basket.items is an array of Item objects, it inferred that it’s OK to call reduce on it;
  • because we defined that basket.items is an array of Item it inferred that the reducer function’s second argument has type Item — we didn’t need to tell it again;
  • because the second argument of reduce is 0, it inferred that the reducer function’s first argument is number, and from that, it inferred that the result of the reduce call, and so the function’s return type will be number too.
  • because the type checker knows all of that, it will beep us if somehow try to multiply item.price with a string on a late Friday night…

This is both smart, and very helpful.


I find that the ability to change is the most important part of any project. No mater how much we think upfront about what we think our code should be, at some point we’ll need to change it. And at that point, the type checker will point every place in the code that it knows it’ll be affected by changing this function here. It will not let us doubt about wether we found all the places where it’s used those hundreds of files in our project.

The superpower

No matter how smart an IDE can be, it can’t keep up with what the compiler knows about he code, and this is why TypeScript can do all the things above. It comes with a tool that has access to the same data and language services that the compiler does: the tsserver that can be used by IDEs and text editors to find things about the project source code.

Because it uses the same core functionality as the compiler, it can unambiguously tell things like:

  • What type is this symbol?
  • Where is this symbol declared?
  • Where is this symbol used?
  • What are the IntelliSense options for this thing here?
  • What other places in the project would I have to change if I rename this symbol?

This is exactly what makes it possible to have fearless project-wide refactorings with TypeScript.


Every little piece of data that moves through our code has a specific type. Wether we specify it explicitly or not, we are aware of it when we write or change that function. If we explicitly define that type, the type checker can help us keep the code in harmony with the data.

I find this somewhat similar to unit tests: We always want to test every piece of code. The question is only wether we’ll do it manually or will automate it.