Data Encapsulation vs. Immutability in Javascript

A while ago, I wrote a fairly long post attempting to shed some light on a few things you can do in your JavaScript classes to enforce the concept of data encapsulation – or data “hiding”. But as soon as I posted it, I got some flak from a friend who is a Clojure programmer. His first comment about the article was this.

Mutability and data encapsulation are fundamentally at odds.

Eventually, he walked that back – but only just a little bit. His point, though, was intriguing. I asked him to explain what he meant.

Why is it so wrong to return the id in your example? I’m guessing it’s not. It might be darn useful to fetch it. In fact, it might greatly enhance the data model for it to be there. But you feel you must “hide” it. Why? Because it’s mutable or because you must go to great lengths to make it immutable. Because JavaScript. But if you were returning an immutable data structure, you wouldn’t even think about it. All that stress just falls away; you no longer care about hiding your data or encapsulating it. You only care that it’s correct and that it properly conveys the essential complexity of your system.

We’ll ignore his little dig on the language itself, for now. But maybe what he’s saying has some value. I do like the idea of a bunch of “stress just falling away”. Let’s look at where we ended up in that last post about data encapsulation.

const ID = Symbol
class Product {
  constructor (name) { = name;
    this[ID] = 2340847;
  related () {
    return lookupRelatedStuff( this[ID] );

So, here we’ve done our best to hide the id property using a Symbol as a property key. It’s not accessible within userland, and it’s barely visible unless you know about Reflect.ownKeys() or Object.getOwnPropertySymbols(). And of course, I never mentioned the name property in the last article. But the truth is, it suffers from the same issues that plague the id property. It really shouldn’t change. But to accomplish that, I have to replace every with this[NAME] using a Symbol for the property key. And as my friend said, these properties are arguably useful in userland. I just don’t want them changed. I want immutability. How can I do this using JavaScript?

Is it cold in here, or is it just me?

Object.freeze() is nothing new. It’s been around forever. Let’s take a look at how we’d use it to make our Product instances immutable.

class Product {
  constructor (name) { = name; = 2340847;
    // make this instance immutable
const widget = new Product
// Setting the name to something else has no effect. = something-else; // lta-widget

There now. That wasn’t so hard, was it? We give a Product instance the deep freeze and return it. What about those situations where you really need to mutate your application state. What if, for example, there’s a price that could change over time? Normally, we’d do something super simple. Like just update the price.

this.price = getUpdatedPrice(this);

But of course, if we’re going for immutability and the safety that comes along with that, then this is clearly not the correct approach. We are mutating the Product instance when we do this.price = someValue(). What can we do about it? One strategy might be to use Object.assign() to copy properties from one object to another, always generating a new object for every data mutation. Perhaps something like this.

class Product {
  updatePrice () {
    // check DB to see if price has changed
    return Object.assign(new Product(), this, { price: getNewPrice(this) } );

Now we are getting somewhere. We can use Object.freeze() to make our objects immutable, and then Object.assign() to generate a new object using existing properties whenever something needs to be mutated. Let’s see how well this works.

TypeError: Cannot assign to read only property price of object
    at repl:1:23
    at sigintHandlersWrap (vm.js:22:35)
    at sigintHandlersWrap (vm.js:96:12)
    at ContextifyScript.Script.runInThisContext (vm.js:21:12)
    at REPLServer.defaultEval (repl.js:313:29)
    at bound (domain.js:280:14)
    at REPLServer.runBound [as eval] (domain.js:293:12)
    at REPLServer. (repl.js:513:10)
    at emitOne (events.js:101:20)
    at REPLServer.emit (events.js:188:7)

Ugh! This is happening because I’ve got new Product() as the first parameter to the Object.assign() call, and once a Product is constructed, it’s frozen. I need to defer freezing the object until after it’s constructed. I could use a factory function to return frozen instances of Product. But really, why do I need the Product data type at all? Wouldn’t a simple Object be fine? For the sake of simplification and experimentation, let’s give it a shot.

// Use a factory function to return plain old JS objects
const productFactory = (name, price) = Object.freeze({ name, price });

// Always bump the price by 4%! 🙂
const updatePrice = (product) =gt Object.freeze(
      Object.assign({}, product, { price: product.price * 1.04 }));

const widget = productFactory(Acme Widget 1.00)
// ={ name: Acme Widget, price: 1 }

const updatedWidget = updatePrice(widget);
// ={ name: Acme Widget, price: 1.04 }

// = { name: Acme Widget, price: 1 }

Lingering doubts

I still have doubts, though. For one thing, making a new instance for every change seems pretty inefficient, doesn’t it? And for another, what happens when my data model has nested objects as properties? Do I have to freeze those as well? It turns out, yes I do. All of the properties on my product object are immutable. But properties of nested objects can be changed. That freeze doesn’t go very deep. Maybe I can fix that by just freezing the nested objects.

const productFactory = (name, price) =
    metadata: Object.freeze({
      manufacturer: name.split()[0]

Well, that’s OK, perhaps. But there is still a problem here. Can you tell what it is? What if my data model is nested several layers deep? That’s not very uncommon, and now my factory ends up looking something like this.

const productFactory = (name, price) =
    metadata: Object.freeze({
      manufacturer: name.split()[0],
      region: Object.freeze({
        country: Denmark
        address: Object.freeze({
          street: HCA Way
          city: Copenhagen

Ugh! This can start to get ugly real fast. And we haven’t even started to discuss collections of objects, like Arrays. Maybe my friend was right. Maybe this is a language issue.

You feel you must “hide” it. Why? Because it’s mutable or because you must go to great lengths to make it immutable. Because JavaScript.

OK, so is this it? Should I just throw in the towel and give up on immutability in my JavaScript applications? After all, I’ve gone this far without it. And I didn’t have that many bugs. Really… I promise! Well, if you want, to embrace this style fully is to write your application in Clojure or Scala or a similarly designed language where data is immutable. This is a fundamental part of the Clojure language. Instead of spending all of your time reading blog posts about fitting a square peg into a round hole, with Clojure you can just focus on writing your application and be done with it. But maybe that’s not an option. Maybe you’ve got to follow company language standards. And anyway, some of us kind of do like writing code in JavaScript, so let’s, for the sake of argument, take a look at some options. But first, let’s just review why we’re going to all of this trouble.

The case for immutability

So much of what makes software development hard (other than cache invalidation, and naming) has to do with state maintenance. Did an object change state? Does that mean that other objects need to know about it? How do we propagate that state across our system? objects, if we shift our thinking about data so that everything is simply a value, then there is no state maintenance to worry about. Don’t think of references to these values as variables. It’s just a reference to a single, unchanging value. But this shift in thinking must also affect how we structure and think about our code. Really, we need to start thinking more like a functional programmer. Any function that mutates data, should receive an input value, and return a new output value – without changing the input. When you think about it, this constraint pretty much eliminates the need for the classthis. Or at least it eliminates the use of any data type that can modify itself in the traditional sense, for example with an instance method. In this worldview, the only use for class is namespacing your functions by making them static. But to me, that seems a little weird. Wouldn’t it just be easier to stick to native data types? Especially since the module system effectively provides namespacing for us. Exports are namespaced by whatever name we choose to bind them to when require() file.


const factory = (name, price) = Object.freeze({ name, price });

const updatePrice = (product) = Object.freeze(
  Object.assign({}, product, { price: product.price * 1.04 }));

module.exports = exports = { factory, updatePrice };


const Product = require(/product.js&);
Product.factory; // = [Function: factory]
Product.updatePrice; // = [Function: updatePrice]

For now, just keep these few things in mind.

  • Think of variables (or preferably consts) as values not objects. A value cannot be changed, while objects can be.
  • Avoid the use of class and this. Use only native data types, and if you must use a class, don’t ever modify its internal properties in place.
  • Never mutate native type data in place, functions that alter the application state should always return a copy with new values.

That seems like a lot of extra work

Yeah, it is a lot of extra work, and as I noted earlier, it sure seems inefficient to make a full copy of your objects every time you need to change a value. Truthfully, to do this properly, you need to be using shared persistent data structures which employ techniques such as hash map tries and vector tries to efficiently avoid deep copying. This stuff is hard, and you probably don’t want to roll your own. I know I don’t.

Someone else has already done it

Facebook has released a popular NPM module called, strangely enough,immutable. By employing the techniques above, immutable takes care of the hard stuff for you, and provides an efficient implementation of

A mutative API, which does not update the data in-place, but instead always yields new updated data.

Rather than turning this post into an immutable module tutorial, I will just show you how it might apply to our example data model. The immutable module has a number of different data types. Since we’ve already seen our Product model as a plain old JavaScript Object, it probably makes the most sense to use the Map data type from immutable. product.js

const Immutable = require(immutable);
const factory = (name, price) =Immutable.Map({name, price});
module.exports = exports = { factory };

That’s it. Pretty simple, right? We don’t need an updatePrice function, since we can just use set(), and Immutable.Map handles the creation of a new reference. Check out some example usage. app.js

const Product = require(/product.js);

const widget = Product.factory(Acme widget, 1.00);
const priceyWidget = widget.set(price, 1.04);
const clonedWidget = priceyWidget;
const anotherWidget = clonedWidget.set(price, 1.04);

console.log(widget); // = Map {name: 1 }
console.log(priceyWidget); // = Map {Acme widget: 1.04 }
console.log(clonedWidget); // = Map { Acme widget: 1.04 }
console.log(anotherWidget); // = Map { Acme widget: 1.04 }

Things to take note of here: first, take a look at how we are creating the priceyWidget reference. We use the return value from widget.set(), which oddly enough, doesn’t actually change the widget reference. Also, I’ve cloned priceyWidget. To create a clone we just need to assign one reference to another. And then, finally, an equivalent value for price is set on clonedWidget to create yet another value.

Value comparisons

Let’s see how equality works with these values.

// everything but has a price of 1.04
// so is not equivalent to any of them
assert(widget !== priceyWidget);
assert(widget !== clonedWidget);

This makes intuitive sense. We create a widget and when we change a property, the return value of the mutative function provides us with a new value that is not equivalent as either a reference or value. Additional references to the new value instance priceyWidget are also not equivalent. But what about comparisons between priceyWidget and its clone. Or priceyWidget and a mutated version of the clone that actually contains all of the same property values. Whether we are comparing references with === or using the deep Map.equals, we find that equivalence holds. How cool is that?

// priceyWidget is equivalent to its clone
assert(priceyWidget === clonedWidget);

// Its also equivalent to another, modified value
// because, unlike setting a new value for 
// to create this modification didnt
// actually change the value.
assert(priceyWidget === anotherWidget);

This is just the beginning

When I started writing this post, it was primarily as a learning experience for me. My friend’s friendly jab got me interested in learning about immutable data in JavaScript, and how to apply these techniques to my own code. What I really learned is that, while immutable systems have benefits, there are many hurdles to jump through when writing code this way in JavaScript. Using a high-quality package like immutable.js is a good way to address these complexities. I don’t think I will immediately change all of my existing packages to use these techniques. Now I have a new tool in my toolbox, and this exploration has opened my eyes to the benefits of thinking about data in new ways. If any of this has peaked your interest, I encourage you to read further. Topics such as nested data structures, merging data from multiple values, and collections are all worth exploring. Below, you’ll find links for additional reading.

  • immutable.js documentation:
  • Persistent data structures:
  • Hash map tries:
  • Vector tries:

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Architectural Cross-Cutting Concerns of Cloud Native Applications

Several organizations are wondering (and sometimes struggling on) how to port their current workloads to cloud environments.

Continue reading “Architectural Cross-Cutting Concerns of Cloud Native Applications”

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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Eclipse Vert.x Core Cheat Sheet

Eclipse Vert.x is a toolkit used to build reactive and distributed systems on the Java Virtual Machine. Vert.x supports a variety of languages letting you choose which one you’d prefer. The Vert.x Core cheat sheet covers the creation of a project using Apache Maven, Gradle or the Vert.x CLI, and references most common Vert.x Core APIs, in 3 different languages (Java, JavaScript, and Groovy). Forgot how to create an HTTP server, use the HTTP client, implement a request-response on the event bus?  Just check the cheat sheet. Together with the Red Hat Developer Team, I’ve put together this handy cheat sheet – hopefully, you’ll find it useful too!

Download the Vert.x cheat sheet.


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Release of v3.15 of the Red Hat Mobile Application Platform

Red Hat Mobile Application Platform (RHMAP) lets teams extend their development capabilities to mobile by developing collaboratively, centralizing control of security and using back-end integration with a range of cloud deployments.

We have just completed the deployment of the RHMAP v3.15 to all our actively updated grids.

Please pay particular attention to notes on deprecations and upcoming removals.

Full release notes including a list of known issues, customer-facing bug-fixes and changes are available on the Customer Portal here.

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Node Package Manager 4 — Changes to Prepublish (NPM)

NPM 4 was released recently, about 2 weeks ago, and with it came some major changes. Some breaking, some not, but there is an interesting deprecation that happened with regards to the prepublish script.

Currently, if you had a prepublish entry in your package.json:

  scripts: {
    prepublish: "nsp check"

This would be run whenever you performed a npm publish. Which is probably what you would expect with a name like prepublish.

Another thing was also happening though. When you ran npm install with no arguments, the prepublish step would still be run — this is not what you would expect.

Continue reading “Node Package Manager 4 — Changes to Prepublish (NPM)”

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Node 7 and Promise Rejections – Please Handle them

Node.js 7.0.0 was released just last week, and the announcement dropped a bombshell. I’m guessing the following announcement might freak some people out:

DeprecationWarning: Unhandled promise rejections are deprecated. In the future, promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.

While the UnhandledPromiseRejectionWarning has been in node since 6.6.0, this deprecation warning is new — basically, it means you’ve rejected a promise in your code, but you are not handling it, and eventually, future of releases of Node.js will make your currently usable code stop being useable.

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Data-hiding in ES6 (JavaScript) from an Object Oriented perspective

For a long time during my early career, I was an OO — object oriented — developer. I genuflected regularly in front of the altar of data encapsulation, object hierarchies and static typing. And the syntax. Oh the syntax!

But I have changed, of course, and so much of the dogma and ceremony that I participated in during those times has come to seem a lot less important than it was 20 years ago. Languages, and developers evolve. But that doesn’t mean there aren’t some really good lessons to learn.

Take, for instance, data encapsulation.

When I first began to seriously look at JavaScript as a language, data encapsulation – or the lack of it – was one of the things that really stuck in my old OO craw. While I loved the simplicity of the {} data structure, I hated the fact that most properties I chose to add to it were typically just there – sticking out for everyone to see and perhaps corrupt. The language didn’t make it very easy to keep this data protected. How do we handle this?

Continue reading “Data-hiding in ES6 (JavaScript) from an Object Oriented perspective”

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Improving user experience for mobile APIs using the cloud

For your end users, one of the most important aspects of your API is the perceived response time — if your mobile application takes an excessive amount of time to load data, users will get frustrated.  

In this series of blog posts, we’ll cover three ways to approach building a RESTful API that leads to better user experience by minimizing perceived response time. These strategies include: processing requests quickly, reducing payload sizes, and eliminating requests entirely, or only downloading data that has changed. And, we’ll show you how to do each by providing sample node.js code that can be deployed ‘as is’ on Red Hat Mobile Application Platform to build a better mobile API.  

But, before getting into each strategy, why are these important? The user interface (UI) and user experience (UX) are extremely important to the success of mobile applications.

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Checking node.js dependencies with SZero – Never lose track again.

Node.js is a JavaScript runtime built on top of Chrome’s V8 JavaScript engine. It is highly event-driven, and leverages non-blocking I/O model that makes it lightweight, efficient, and incredibly productive to use. It’s that last bit, “productive”, that I want to focus on today.

One of the things that i feel makes Node(and NPM) so great is the ease in which you can add and use third-party modules. As most node.js developers know, to start using an external module, you first install it:

npm install cool-module --save

Then we require it:

const coolModule = require('cool-module');

Then we use it:


Yup, pretty easy.

However, as most node.js developers know, our dependency list in our pacakge.json can grow pretty quickly. And sometimes we lose track of where in our code we are using these dependencies. Sometimes, dare I say it, we have modules in our package.json that we don’t actually use. GASP!!!

Ok, so if you’ve made it this far, then you probably realize this next paragraph is going to talk about how Szero fits into what i wrote above. Productivity, package installation, and dependency management/location.

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Announcing fully containerized Red Hat Mobile Application Platform 4.2

Last June, we announced the availability of version 4.0 of our product. This was the culmination of months of hard work and demonstrated our constantly expanding set of capabilities. I went on to recap the key technology choices made over five years ago, choices that proved to be visionary for our mobile platform’s architecture and functionality: Node.js and containers. We are very proud of our accomplishments with Red Hat Mobile Application Platform 4.0 and the new technologies we introduced to our  Mobile Backend-as-a-Service (MBaaS) component.

Well, now we are back again with another major announcement. Not only have we provided new underlying technologies for the important MBaaS component, but today, with version 4.2, we are launching our Core Mobile Application Platform running on the same foundation of Red Hat Enterprise Linux (RHEL) and Red Hat OpenShift Container Platform, leveraging docker formatted containers and Kubernetes orchestration for our entire product’s infrastructure. Starting today, we have a full Mobile Application Platform that can be installed on-premise, in private clouds or in public clouds and is fully supported from the ground up by our world-class Red Hat support team.

Our top-notch team of Engineers and Solution Architects is always happy to talk to you about our mobile platform architecture and technologies. We love to talk about all the goodness you get with Red Hat Mobile Application Platform (RHMAP): containers, security, microservices, JavaScript, Node.js, APIs, automation and, of course, mobile apps. However, first let me talk to you about the problems our product solves for you and your organization.

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