Cycle.js a reactive framework

I had the chance to spend quite few evenings with Cycle.js preparing my presentation for JSDay 2016 and I have to admit that I had quite a lot of fun so I decided to share my experience in this post.

I’d suggest first to take a look to my previous introduction to reactive programming just to cover the basics if you are not familiar with this paradigm.

Cycle.js is an incredible light framework that allow you to work in a reactive fashion way. As mentioned on all my talks regarding this topic, the initial entry level is a little bit higher than other frameworks if you are not familiar with Reactive concepts like hot and cold observables for instance and Functional concepts like pure functions.
Cycle puts the functions as first class citizen for the entire framework, having a previous knowledge of reactive and functional paradigms definitely it helps to speed up working with this framework.
Let’s start to see how it works from an eagle eye perspective:

Screen Shot 2016-05-22 at 11.37.17

This image above represent the main concept behind Cycle where we have a loop between the a main method, that receives as input a read effects (sources), and the “external world” that receives some write effects as output (sinks).
The side effects generated by the main function will be handled by the “external world” inside drivers that will communicate with the external world.

Cycle in practice

 

Cycle.js allows you to work with an interesting architecture created ad hoc for reactive programming called MVI (Model View Intent), I wrote an extensive article on this topic and I suggest to read it because the architecture is really interesting leveraging new concepts like the communication between objects via observables.

mvi

There is an interesting read in the Cycle website that explains how MVI works in the official website.

For the JSDay I prepared a simple example in MVI with Cycle just to show how simple is working with this architecture and with Cycle framework.
The example is a real time monitor for London Underground trains showing the position of each train and the expected arrival to their destination.

Screen Shot 2016-05-11 at 11.52.07

You can find the project on my github account

The application is mainly composed by 4 main areas:

  • Main.js is the entry point of our application where I’m instantiating Cycle run loop and I’m adding the hot reloading module for Cycle.js
  • App.js where there is the business logic of the application written in MVI (mvi-refactor branch)
  • Networking.js where I’m handling the HTTP request and response made via HTTPDriver
  • Template.js that represents the renderer object made with hyperscript (default virtual-dom library present in Cycle)

The App.js is where the business logic of the application sits with the division of competences between Model – View – Intent.
I warmly suggest to have a read to my article on MVI as mentioned before in order to understand how MVI works.

export default function app(_drivers){
   const response$ = networking.processResponse(_drivers.HTTP);
   const actions = intent(_drivers.DOM);
   const state$ = model(response$, actions);
   const vtree$ = view(state$);
   const trainsRequest$ = networking.getRequestURL(actions.line$, DEFAULT_LINE);

   return {
      DOM: vtree$,
      HTTP: trainsRequest$
   };
}

the interesting part here is how I’ve divided the interaction between different actors present in the app inside the main method.
All the constants that ends with $ symbols are observables (this is a simple convention to immediately recognise which variable is an observable and which is not).
The app method has a unique argument (_drivers) and it returns an object containing 2 observables that will be handled by the outside world via drivers (check Main.js to see where I’ve instantiated the DOM and HTTP drivers).

Then I’ve created the networking object that is handling the interaction between an end point and the application.
response$ is the observable where I’m going to store the service response and trainsRequest$ is where I’m defining the request using the tube line chosen by the user in query string (check Networking.js for that).

Last but not least I’m creating the MVI structure where the only point of communication between these pure functions is an observable or a collection of observables.
That would help me to testing easily the application, encapsulating properly the behaviours of each part and having a unidirectional flow of information that are flowing inside the application or component.

I’d like to bring your attention now to how the view is handled in Cycle.js, the view is generating a virtual tree of elements that will be rendered by a third party library like Hyperscript or React.
It’s not a case that Cycle is using a render library that implements the virtual-dom concept because, as we describe at the beginning, Cycle works with loops so having a diff algorithm that update the DOM only when needed it’s a great boost performance wise for the entire application and it removes some complexity to handle on the developers side.

export default function getBody(results){

   let selectedLine = results[0].length > 0 ? 'Selected line: ' + results[0] : "";
 
   return div(".container", [
      h1("#title", ["Reactive Live London Tube trains status"]),
      select("#lines", [
         option({ value: 'piccadilly' }, ["Piccadilly line"]),
         option({ value: 'northern' }, ["Northern line"]),
         option({ value: 'bakerloo' }, ["Bakerloo line"]),
         option({ value: 'central' }, ["Central line"]),
         option({ value: 'district' }, ["District line"]),
         option({ value: 'circle' }, ["Circle line"]),
         option({ value: 'victoria' }, ["Victora line"]),
     ]),
     h3("#selectedLine", [selectedLine]), 
     renderTrainsData(results[1])
   ]);
}

Just to give you an idea, I brought the entry function that generates the application view, after defined few static elements like the dropdown and few title elements, I’m going to call another function that is returning the results to display in the main view.
In renderTrainsData function I’m returning the elements splitting the different domain objects across 3 other functions:

function getTrainData(data){
   return li(".train", [
      div(".train-data", [
        p(".stationName .col", [span("station: "), data.stationName]),
        p(".platform", [span("platform: "), data.platformName]),
        p(".current-location", [span("current location: "), data.currentLocation]),
        p(".arrival-time: ", [span("expected arrival time: "), moment(new Date(data.expectedArrival)).format("HH:MM - Do MMM YYYY")])
      ]
   )])
}

function getDestinationStation(data){
   return div(`.destination-station .${data.lineId}`, [
       h2(data.destination),
       ul(".destination-trains-available", data.trains.map(item => getTrainData(item)))
   ]);
}

function renderTrainsData(data){
   return div(".all-stations", data.map(item => getDestinationStation(item)));
}

As you can see is very easy to understand and the code becomes very readable for anyone, in particular when we are writing meaningful function names.
I’ve created also some simple CSS IDs and classes defined as first parameter of each HTML element just for the curiosity to see a basic integration between hyperscript and CSS.

Wrap Up

Cycle.js is showing a new approach to the Javascript community with a lot of good ideas and a growing community that is following and improving the framework.
I can’t say that would be the most used framework for the next year considering how much React+Redux and Angular 2 are succeeding in the front end scene, but I believe that with Cycle you can still create great applications often with less and well structured code compared to other frameworks.
I’ll definitely continue to go ahead with it and possibly to contribute as much as I can to this project and Rx.js as well, because I strongly believe in the future of reactive programming paradigm and the people behind it.

 

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Hot and Cold observables

One important thing to understand when you are working with Reactive Programming is the difference between hot and cold observables.
Let’s start with the definition of both types:

Cold Observables

Cold observables start running upon subscription: the observable sequence only starts pushing values to the observers when subscribe is called.

Values are also not shared among subscribers.

Hot Observables

When an observer subscribes to a hot observable sequence, it will get all values in the stream that are emitted after it subscribes.

The hot observable sequence is shared among all subscribers, and each subscriber is pushed the next value in the sequence.

Let’s see now how these 2 different observables are used across a sample application.

Using the same application I started to describe in my previous blog post, we can spot in the main class some code that is commented.
The first part represent how a cold observable works, so if you try to have the following code inside App.js you can immediately understand what’s going on when an observer subscribes to a cold observable:

let engine = new BallsCallSystem(); 
let t1 = new Ticket("t1", engine.ballStream); 

setTimeout(()=>{
    let t2 = new Ticket("t2", engine.ballStream);
}, 5000);

engine.startGame();

Our game engine instead has the following code in order to share the balls called across the tickets:

let stream = Rx.Observable
    .interval(INTERVAL)
    .map((value) => {return numbersToCall[value]})
    .take(TOTAL_CALLS);
 
this.published = stream.publish();

As you can see when we start the game there is only 1 ticket bought by the user, then after 5 seconds the user bought a new ticket and in theory we should check if in that ticket all the numbers previously called are present or not.

coldObservables
But with cold observables when an observer subscribe, it won’t be able to receive the previous data but just the data since when it subscribed, completely broken the main purpose of our bingo game… we definitely need something different in order to work with it, potentially something that won’t completely change our game logic but that could be useful to fix the issue…

That’s where the hot observables come in!
The cool part of hot observables is that you can define how much data you want to buffer inside the memory, sometimes you need to store all of them (like in the bingo game) sometimes you need only the last 4-5 occurrences, but as you will see changing from a cold to an hot observables it’s a matter of 1 line of code!

Inside the same git repo, you can find a class called BallsCallSystemReplay, this class implement an hot observable, let’s see how much the code changed inside our game engine:

this.stream = Rx.Observable
   .interval(INTERVAL)
   .map((value) => {return numbersToCall[value]})
   .take(TOTAL_CALLS)
   .shareReplay();

Basically we removed the publish method after creating the stream (that was useful if you want to control when the observable starts to stream data) and we added shareReplay that is a method that transform a cold observable to an hot one sharing all the data pass trough the stream every time a new observer subscribe to it.

So now if we change the code in App.js in this way:

let engine = new BallsCallSystemReplay();
let t1 = new Ticket("t1", engine.ballStream);
 
setTimeout(function() {
    let t2 = new Ticket("t2", engine.ballStream);
}, 5000);

Now you can see that when the second ticket is bought after the game started, we’re going anyway to check all the values called by the engine without doing a massive refactor of our game logic! Below you can see when the second ticket subscribe to the hot observable, the first thing is going to receive are all the previous values called by the engine and then is receiving the data with a certain interval following the logic of the game.

hotObservables

Reactive Programming with RxJS

In the past 6 months I spent quite few time trying to understand Reactive Programming and how it could help me on my daily job.
So I’d like to share in this post a quick example made with RxJS just to show you how Reactive Programming could help when you are handling asynchronous data streams.

If you are not familiar at all with these concepts I’d suggest to watch first my presentation on Communicating Sequential Process and Reactive Programming with RxJS (free registration) or check the slides below.

For this example I thought to create a basic bingo system that I think is a good asynchronous application example that fits perfectly with the Reactive Programming culture.
I won’t introduce in this blog post concepts like hot and cold observables, iterator pattern or observer pattern mainly because all these theoretical information are present in the webinar and the slides previously mentioned. 

You can clone the project repository directly from my git account.

Let’s start talking a little bit about the engine, basically a bingo system is composed by an engine where the numbers are called every few seconds and shared with the users in order to validate in which ticket bought by the user the number called is present.
For this purpose working with observables will facilitate the communication and the information flow between the engine and the ticket objects.
In BallsCallSystem class, after setting up the object creating few constant that we’re going to use inside the core engine, we’re going to implement the core functionality of the engine:

let stream = Rx.Observable
              .interval(INTERVAL)
              .map((value) => {return numbersToCall[value]})
              .take(TOTAL_CALLS);

These few lines of code are expressing the following intents:

  1. we create an observable (Rx.Observable)
  2. that every few milliseconds (interval method)
  3. iterate trough the interval values (incremental value from 0 to N) and return a value retrieved from the array numbersToCall (function described inside the map method)
  4. and after a certain amount of iteration we need to close the observable because the game is ended (take method) so all the observer will stop to execute their code

If we compare with an imperative programming implementation made with CSP (communicating sequential processes) I’ll end up having something similar to this one:

this.int = setInterval(this.sendData.bind(this), 3000);
[....]
sendData(){
   var val = this.numbersToCall[this.counter];
   console.log("ball called", val);
 
   csp.putAsync(this.channel, val);
   this.counter++;
 
   if(this.counter > this.numbersToCall.length){
      clearInterval(this.int);
      this.channel.close();
      console.log("GAME OVER");
   }
 }

As you can see I needed to express each single action I wanted to do in order to obtain the core functionality of my bingo system.
These 2 implementations are both solving exactly the same problem but as you can see the reactive implementation is way less verbose and easy to read than the imperative one where I’ve control of anything is happening inside the algorithm but at the same time I don’t really have a specific reason to do it.

Moving ahead with the reactive example, when we create an observable that streams data we always need an observer to retrieve these data.
So now let’s jump to Ticket class and see how we can validate against a ticket the numbers called by the engine

First of all we pass the observable via injection to a Ticket object:

let t2 = new Ticket("t2", engine.ballStream);

Then, inside the Ticket class we subscribe to the observable and we handle the different cases inside the stream (when we receive data, when an error occurs and when the stream will be terminated):

obs.subscribe(this.onData.bind(this), this.onError.bind(this), this.onComplete.bind(this));
onData(value){
    console.log("number called", value, this.tid);
    if(this.nums.indexOf(value) >= 0){
       this.totalNumsCalled.push(value);
       console.log(value + " is present in ticket " + this.tid);
    } 
 }
 
 onError(err){
    console.log("stream error:", err);
 }
 
 onComplete(){
    console.log("total numbers called in " + this.tid + ": " + this.totalNumsCalled.length);
    console.log(this.totalNumsCalled);
 }

Also here you can notice the simplicity of an implementation, for instance if we are working with React it will be very easy to handle the state of an hypothetical Ticket component and create a resilient and well structured view where each stream state is handled correctly.

An interesting benefit provided by reactive programming is for sure the simplicity and the modularity at the same time how our implementations are working.
I would really recommend to spend sometime watching the webinar in order to get the first approach to Reactive Programming and to understand better the purpose of the example described briefly above.