An Introduction to JavaScript ES6 Proxies

An Introduction to JavaScript ES6 Proxies

Proxy is one of the most overlooked concepts introduced in ES6 version of JavaScript, but ES6 proxies bound to come in handy at some point in your future.

Proxy is one of the most overlooked concepts introduced in the ES6 version of JavaScript.

Admittedly, it isn’t particularly useful on a day-to-day basis, but it is bound to come in handy at some point in your future.

The basics

The Proxy object is used to define a custom behavior for fundamental operations such as property lookup, assignment, and function invocation.

The most basic example of a proxy would be:

const obj = {
 a: 1,
 b: 2,
};

const proxiedObj = new Proxy(obj, {
 get: (target, propertyName) => {
   // get the value from the "original" object
   const value = target[propertyName];

   if (!value && value !== 0) {
     console.warn('Trying to get non-existing property!');

     return 0;
   }

   // return the incremented value
   return value + 1;
 },
 set: (target, key, value) => {
   // decrement each value before saving
   target[key] = value - 1;

   // return true to indicate successful operation
   return true;
 },
});

proxiedObj.a = 5;

console.log(proxiedObj.a); // -> incremented obj.a (5)
console.log(obj.a); // -> 4

console.log(proxiedObj.c); // -> 0, logs the warning (the c property doesn't exist)

We have intercepted the default behavior of both get and set operations by defining the handlers with their respective names in the object provided to the proxy constructor. Now each get operation will return the incremented value of the property, while set will decrement the value before saving it in the target object.

What’s important to remember with proxies is that once a proxy is created, it should be the only way to interact with the object.

Different kinds of traps

There are many traps (handlers that intercept the object’s default behavior) aside from get and set, but we won’t be using any of them in this article. With that being said, if you are interested in reading more about them, here’s the documentation.

Having fun

Now that we know how proxies work, let’s have some fun with them.

Observing object’s state

As it has been stated before it is very easy to intercept operations with proxies. To observe an object’s state is to be notified every time there’s an assignment operation.

const observe = (object, callback) => {
 return new Proxy(object, {
   set(target, propKey, value) {
     const oldValue = target[propKey];
   
     target[propKey] = value;

     callback({
       property: propKey,
       newValue: value,
       oldValue,
     });

     return true;
   }
 });
};

const a = observe({ b: 1 }, arg => {
 console.log(arg);
});

a.b = 5; // -> logs from the provided callback: {property: "b", oldValue: 1, newValue: 5}

And that’s all we have to do — invoke the provided callback every time the set handler is fired.

As an argument to the callback, we provide an object with three properties: the name of the changed property, the old value, and the new value.

Prior to executing the callback, we assign the new value in the target object so the assignment actually takes place. We have to return true to indicate that the operation has been successful; otherwise, it would throw a TypeError.

Here’s a live example.

Validating properties on set

If you think about it, proxies are a good place to implement validation — they are not tightly coupled with the data itself. Let’s implement a simple validation proxy.

As in the previous example, we have to intercept the set operation. We would like to end up with the following way of declaring data validation:

const personWithValidation = withValidation(person, {
 firstName: [validators.string.isString(), validators.string.longerThan(3)],
 lastName: [validators.string.isString(), validators.string.longerThan(7)],
 age: [validators.number.isNumber(), validators.number.greaterThan(0)]
});

In order to achieve this, we define the withValidation function like so:

const withValidation = (object, schema) => {
 return new Proxy(object, {
   set: (target, key, value) => {
     const validators = schema[key];

     if (!validators || !validators.length) {
       target[key] = value;

       return true;
     }

     const shouldSet = validators.every(validator => validator(value));

     if (!shouldSet) {
       // or get some custom error
       return false;
     }

     target[key] = value;
     return true;
   }
 });
};

First we check whether or not there are validators in the provided schema for the property that is currently being assigned — if there aren’t, there is nothing to validate and we simply assign the value.

If there are indeed validators defined for the property, we assert that all of them return true before assigning. Should one of the validators return false, the whole set operation returns false, causing the proxy to throw an error.

The last thing to do is to create the validators object.

const validators = {
 number: {
   greaterThan: expectedValue => {
     return value => {
       return value > expectedValue;
     };
   },
   isNumber: () => {
     return value => {
       return Number(value) === value;
     };
   }
 },
 string: {
   longerThan: expectedLength => {
     return value => {
       return value.length > expectedLength;
     };
   },
   isString: () => {
     return value => {
       return String(value) === value;
     };
   }
 }
};

The validators object contains validation functions grouped by the type they should validate. Each validator on invocation takes the necessary arguments, like validators.number.greaterThan(0), and returns a function. The validation happens in the returned function.

We could extend the validation with all kinds of amazing features, such as virtual fields or throwing errors from inside the validator to indicate what went wrong, but that would make the code less readable and is outside the scope of this article.

Here’s a live example.

Making code lazy

For the final — and hopefully most interesting — example, let’s create a proxy that makes all the operations lazy.

Here’s a very simple class called Calculator, which contains a few basic arithmetic operations.

class Calculator {
 add(a, b) {
   return a + b;
 }

 subtract(a, b) {
   return a - b;
 }

 multiply(a, b) {
   return a * b;
 }

 divide(a, b) {
   return a / b;
 }
}

Now normally, if we ran the following line:

new Calculator().add(1, 5) // -> 6

The result would be 6.

The code is executed on the spot. What we would like is to have the code wait for the signal to be run, like a run method. This way the operation will be postponed until it is needed — or not executed at all if there is never a need.

So the following code, instead of 6, would return the instance of the Calculator class itself:

lazyCalculator.add(1, 5) // -> Calculator {}

Which would give us another nice feature: method chaining.

lazyCalculator.add(1, 5).divide(10, 10).run() // -> 1

The problem with that approach is that in divide, we have no clue of what the result of add is, which makes it kind of useless. Since we control the arguments, we can easily provide a way to make the result available through a previously defined variable — $, for example.

lazyCalculator.add(5, 10).subtract($, 5).multiply($, 10).run(); // -> 100

$ here is just a constant Symbol. During execution, we dynamically replace it with the result returned from the previous method.

const $ = Symbol('RESULT_ARGUMENT');

Now that we have a fair understanding of what do we want to implement, let’s get right to it.

Let’s create a function called lazify. The function creates a proxy that intercepts the get operation.

function lazify(instance) {
 const operations = [];

 const proxy = new Proxy(instance, {
   get(target, propKey) {
     const propertyOrMethod = target[propKey];

     if (!propertyOrMethod) {
       throw new Error('No property found.');
     }

     // is not a function
     if (typeof propertyOrMethod !== 'function') {
       return target[propKey];
     }

     return (...args) => {
       operations.push(internalResult => {
         return propertyOrMethod.apply(
           target,
           [...args].map(arg => (arg === $ ? internalResult : arg))
         );
       });

       return proxy;
     };
   }
 });

 return proxy;
}

Inside the get trap, we check whether or not the requested property exists; if it doesn’t, we throw an error. If the property is not a function, we return it without doing anything.

Proxies don’t have a way of intercepting method calls. Instead, they are treating them as two operations: the get operation and a function invocation. Our get handler has to act accordingly.

Now that we are sure the property is a function, we return our own function, which acts as a wrapper. When the wrapper function is executed, it adds yet another new function to the operations array. The wrapper function has to return the proxy to make it possible to chain methods.

Inside the function provided to the operations array, we execute the method with the arguments provided to the wrapper. The function is going to be called with the result argument, allowing us to replace all the $ with the result returned from the previous method.

This way we delay the execution until requested.

Now that we have built the underlying mechanism to store the operations, we need to add a way to run the functions — the .run() method.

This is fairly easy to do. All we have to do is check whether the requested property name equals run. If it does, we return a wrapper function (since run acts as a method). Inside the wrapper, we execute all the functions from the operations array.

The final code looks like this:

const executeOperations = (operations, args) => {
 return operations.reduce((args, method) => {
   return [method(...args)];
 }, args);
};

const $ = Symbol('RESULT_ARGUMENT');

function lazify(instance) {
 const operations = [];

 const proxy = new Proxy(instance, {
   get(target, propKey) {
     const propertyOrMethod = target[propKey];

     if (propKey === 'run') {
       return (...args) => {
         return executeOperations(operations, args)[0];
       };
     }

     if (!propertyOrMethod) {
       throw new Error('No property found.');
     }

     // is not a function
     if (typeof propertyOrMethod !== 'function') {
       return target[propKey];
     }

     return (...args) => {
       operations.push(internalResult => {
         return propertyOrMethod.apply(
           target,
           [...args].map(arg => (arg === $ ? internalResult : arg))
         );
       });

       return proxy;
     };
   }
 });

 return proxy;
}

The executeOperations function takes an array of functions and executes them one by one, passing the result of the previous one to the invocation of the next one.

And now for the final example:

const lazyCalculator = lazify(new Calculator());

const a = lazyCalculator
 .add(5, 10)
 .subtract($, 5)
 .multiply($, 10);

console.log(a.run()); // -> 100

If you are interested in adding more functionality I have added a few more features to the lazify function — asynchronous execution, custom method names, and a possibility to add custom functions through the .chain() method. Both versions of the lazify function are available in the live example.

Summary

Now that you have seen proxies in action, I hope that you could find a good use for them in your own codebase.

Proxies have many more interesting uses than those covered here, such as implementing negative indices and catching all the nonexistent properties in an object. Be careful, though: proxies are a bad choice when performance is an important factor.

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JavaScript developers should you be using Web Workers?

JavaScript developers should you be using Web Workers?

Do you think JavaScript developers should be making more use of Web Workers to shift execution off of the main thread?

Originally published by David Gilbertson at https://medium.com

So, Web Workers. Those wonderful little critters that allow us to execute JavaScript off the main thread.

Also known as “no, you’re thinking of Service Workers”.

Photo by Caleb Jones on Unsplash

Before I get into the meat of the article, please sit for a lesson in how computers work:

Understood? Good.

For the red/green colourblind, let me explain. While a CPU is doing one thing, it can’t be doing another thing, which means you can’t sort a big array while a user scrolls the screen.

This is bad, if you have a big array and users with fingers.

Enter, Web Workers. These split open the atomic concept of a ‘CPU’ and allow us to think in terms of threads. We can use one thread to handle user-facing work like touch events and rendering the UI, and different threads to carry out all other work.

Check that out, the main thread is green the whole way through, ready to receive and respond to the gentle caress of a user.

You’re excited (I can tell), if we only have UI code on the main thread and all other code can go in a worker, things are going to be amazing (said the way Oprah would say it).

But cool your jets for just a moment, because websites are mostly about the UI — it’s why we have screens. And a lot of a user’s interactions with your site will be tapping on the screen, waiting for a response, reading, tapping, looking, reading, and so on.

So we can’t just say “here’s some JS that takes 20ms to run, chuck it on a thread”, we must think about where that execution time exists in the user’s world of tap, read, look, read, tap…

I like to boil this down to one specific question:

Is the user waiting anyway?

Imagine we have created some sort of git-repository-hosting website that shows all sorts of things about a repository. We have a cool feature called ‘issues’. A user can even click an ‘issues’ tab in our website to see a list of all issues relating to the repository. Groundbreaking!

When our users click this issues tab, the site is going to fetch the issue data, process it in some way — perhaps sort, or format dates, or work out which icon to show — then render the UI.

Inside the user’s computer, that’ll look exactly like this.

Look at that processing stage, locking up the main thread even though it has nothing to do with the UI! That’s terrible, in theory.

But think about what the human is actually doing at this point. They’re waiting for the common trio of network/process/render; just sittin’ around with less to do than the Bolivian Navy.

Because we care about our users, we show a loading indicator to let them know we’ve received their request and are working on it — putting the human in a ‘waiting’ state. Let’s add that to the diagram.

Now that we have a human in the picture, we can mix in a Web Worker and think about the impact it will have on their life:

Hmmm.

First thing to note is that we’re not doing anything in parallel. We need the data from the network before we process it, and we need to process the data before we can render the UI. The elapsed time doesn’t change.

(BTW, the time involved in moving data to a Web Worker and back is negligible: 1ms per 100 KB is a decent rule of thumb.)

So we can move work off the main thread and have a page that is responsive during that time, but to what end? If our user is sitting there looking at a spinner for 600ms, have we enriched their experience by having a responsive screen for the middle third?

No.

I’ve fudged these diagrams a little bit to make them the gorgeous specimens of graphic design that they are, but they’re not really to scale.

When responding to a user request, you’ll find that the network and DOM-manipulating part of any given task take much, much longer than the pure-JS data processing part.

I saw an article recently making the case that updating a Redux store was a good candidate for Web Workers because it’s not UI work (and non-UI work doesn’t belong on the main thread).

Chucking the data processing over to a worker thread sounds sensible, but the idea struck me as a little, umm, academic.

First, let’s split instances of ‘updating a store’ into two categories:

  1. Updating a store in response to a user interaction, then updating the UI in response to the data change
  2. Not that first one

If the first scenario, a user taps a button on the screen — perhaps to change the sort order of a list. The store updates, and this results in a re-rendering of the DOM (since that’s the point of a store).

Let me just delete one thing from the previous diagram:

In my experience, it is rare that the store-updating step goes beyond a few dozen milliseconds, and is generally followed by ten times that in DOM updating, layout, and paint. If I’ve got a site that’s taking longer than this, I’d be asking questions about why I have so much data in the browser and so much DOM, rather than on which thread I should do my processing.

So the question we’re faced with is the same one from above: the user tapped something on the screen, we’re going to work on that request for hopefully less than a second, why would we want to make the screen responsive during that time?

OK what about the second scenario, where a store update isn’t in response to a user interaction? Performing an auto-save, for example — there’s nothing more annoying than an app becoming unresponsive doing something you didn’t ask it to do.

Actually there’s heaps of things more annoying than that. Teens, for example.

Anyhoo, if you’re doing an auto-save and taking 100ms to process data client-side before sending it off to a server, then you should absolutely use a Web Worker.

In fact, any ‘background’ task that the user hasn’t asked for, or isn’t waiting for, is a good candidate for moving to a Web Worker.

The matter of value

Complexity is expensive, and implementing Web Workers ain’t cheap.

If you’re using a bundler — and you are — you’ll have a lot of reading to do, and probably npm packages to install. If you’ve got a create-react-app app, prepare to eject (and put aside two days twice a year to update 30 different packages when the next version of Babel/Redux/React/ESLint comes out).

Also, if you want to share anything fancier than plain data between a worker and the main thread you’ve got some more reading to do (comlink is your friend).

What I’m getting at is this: if the benefit is real, but minimal, then you’ve gotta ask if there’s something else you could spend a day or two on with a greater benefit to your users.

This thinking is true of everything, of course, but I’ve found that Web Workers have a particularly poor benefit-to-effort ratio.

Hey David, why you hate Web Workers so bad?

Good question.

This is a doweling jig:

I own a doweling jig. I love my doweling jig. If I need to drill a hole into the end of a piece of wood and ensure that it’s perfectly perpendicular to the surface, I use my doweling jig.

But I don’t use it to eat breakfast. For that I use a spoon.

Four years ago I was working on some fancy animations. They looked slick on a fast device, but janky on a slow one. So I wrote fireball-js, which executes a rudimentary performance benchmark on the user’s device and returns a score, allowing me to run my animations only on devices that would render them smoothly.

Where’s the best spot to run some CPU intensive code that the user didn’t request? On a different thread, of course. A Web Worker was the correct tool for the job.

Fast forward to 2019 and you’ll find me writing a routing algorithm for a mapping application. This requires parsing a big fat GeoJSON map into a collection of nodes and edges, to be used when a user asks for directions. The processing isn’t in response to a user request and the user isn’t waiting on it. And so, a Web Worker is the correct tool for the job.

It was only when doing this that it dawned on me: in the intervening quartet of years, I have seen exactly zero other instances where Web Workers would have improved the user experience.

Contrast this with a recent resurgence in Web Worker wonderment, and combine that contrast with the fact that I couldn’t think of anything else to write about, then concatenate that combined contrast with my contrarian character and you’ve got yourself a blog post telling you that maybe Web Workers are a teeny-tiny bit overhyped.

Thanks for reading

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Further reading

An Introduction to Web Workers

JavaScript Web Workers: A Beginner’s Guide

Using Web Workers to Real-time Processing

How to use Web Workers in Angular app

Using Web Workers with Angular CLI