Angular: The Full Gamut Edition

Charlie Greenman
April 27, 2021
6 min read


Combine latest allows us to combine multiple observables into one, and have the subscribe emit when either of them are called. A common enterprise example, is let's say, that we have a form. The form gives us a search bar, but we would like to have our search bar, search against a drop down as well.

export class AppComponent implements OnInit, OnDestroy {
  private destroyed$ = new Subject<void>();

  get searchText() {
    return this.form.get('searchText');

  get searchFor() {
    return this.form.get('searchFor');

  form: FormGroup;

  constructor(formBuilder: FormBuilder) {
    this.form ={
      searchText: null,
      searchFor: null,

  ngOnInit() {
    const searchText$ = this.searchText.valueChanges;
    const searchFor$ = this.searchFor.valueChanges;

    // combineLatest emits when any of the source observables
    // emits (provided that they have all emitted once to
    // begin with). that's why the console.logs start appearing
    // after values are selected for both form controls
    combineLatest(searchText$, searchFor$)
      .subscribe(([searchText, searchFor]) => {
        console.log('searchText', searchText);
        console.log('searchFor', searchFor);

        // make a call to an API whenever either observable
        // emits
        // this.apiService.loadData(searchText, searchFor)

  ngOnDestroy() {


One very useful use of concat within an enterprise setting, is that if you have all of the data you need available. However, you would like to make sure that they emit in proper order of each other. Using the following:

import { concat } from 'rxjs/operators';

concat(printLog1, printLog2, printLog3); 
// printLog1 emits, then printLog2, and then printLog3

In a realistic scenario, this will come up in a situation such as we would like to

export class AppComponent {
  searchStream$ = new BehaviorSubject('');

  constructor(private productsService: ProductsService) {}

  obs$ = this.searchStream$.pipe(
    switchMap((query) => 
        of({ type: 'start'}),
        this.productsService.getByFilter(query).pipe(map(value => ({ type: 'finish', value })))


Merge allows us to \"merge\" multiple observables into one singular observable. A great re-occuring real world example, is to group multiple events into single observable. For instance, if we are trying to create a music player:

const start$ = fromEvent(this.startButton.nativeElement, 'click').pipe(mapTo(true));
const pause$ = fromEvent(this.pauseButton.nativeElement, 'click').pipe(mapTo(false));
const reset$ = fromEvent(this.resetButton.nativeElement, 'click').pipe(mapTo(null));

this.playerButtons$ = merge(start$, pause$, reset$, stateChange$).pipe(
  switchMap(val => {
    if(val === null) // reset 
    else if(val) // start
    else // stop

By merging all of our events within a single observable, it tidies up our code base, and allows us to deal with all of our events in a singular fashion.


There is a really old tweet by Andre Saltz, that is no longer available for some reason. Regardless, the tweet goes something along these lines:

startWith, as the name implies, is a way to tell your observable to start with a paticular value. With the advent of behaviorSubject which allows you to supply the initial value, or the alternative scenario of data being retrieved from the backend, with the use of Angular's async pipe, wherein the initial value is superfluous.

However, there is one scenario wherein the startWith pipe does get used alot within an Angular setting. That is in conjuction with combineLatest. However, even in this scenario, I would like to argue that behaviorSubject get's used more. [^1]


withLatestFrom will combine two observables with each other. However, only when the value changes for the primary observable, will the subscribe be triggered. If the secondary observable value changes, the subscribe will not be triggered.

Let's use a common example that will occur within the enterprise architecture set up by Razroo. Let's say that you are using ngrx/store, and that you would like to determine whether, or not a blog post exists already within our store. If the blog post already exists within our store, then do make another HTTP request, as we have the data we need already.

  filter([post] => !post),
  mergeMap([a] => s.getPost(

We are looking to see if current post already exists within our blog store. If it does, then we do not make the request. If it does not, then we go ahead and make the request once again.


const yin   = Rx.Observable.of('peanut butter', 'wine','rainbows');
const yang  = Rx.Observable.of('jelly', 'cheese', 'unicorns');

const combo =, yang);

combo.subscribe( arr => console.log(arr));
// peanut butter, jelly
// wine, cheese
// rainbows, unicorns  

Expontential Backoff

zip can be particularly useful using something called exponential backoff. Exponential backoff is a technique wherein you retry an API after failure. However, instead of retrying let's say every 5 seconds, instead we increase the values exponentially after each consecutive failure, with a maximum amount of retries. This can potentially be really complex, but zip makes something like this alot easier:

import { pipe, range, timer, zip } from 'rxjs';
import { ajax } from 'rxjs/ajax';
import { retryWhen, map, mergeMap } from 'rxjs/operators';

function backoff(maxTries, ms) {
 return pipe(
   retryWhen(attempts => zip(range(1, maxTries), attempts)
       map(([i]) => i * i),
       mergeMap(i =>  timer(i * ms))

  .pipe(backoff(3, 250))
  .subscribe(data => handleData(data));

function handleData(data) {
  // ...

The above code is a bit like ninja code, so let's go ahead and unpack everything that is being done here.

  1. First we pass maximum amount of tires, and multiplier to increase exponentially.

  2. In our rxjs pipe, we first use retryWhen. This is an rxjs operator that takes in an observable, and then retries that for x amounts of time.

  3. within our retryWhen we pass a zip, so that we create x x amount of observable streams equal to the amount of maxTries

  4. We then pass the retryWhen index, and increase that exponentially.

  5. We then use the new value, and pipe that over to our timer, which is passed as the new retryWhen amount.

[^1]: To see why not to use startWith and go with behaviorSubject, check the addendum

Subscribe to the Razroo Angular Newsletter!

Razroo takes pride in it's Angular newsletter, and we really pour heart and soul into it. Pass along your e-mail to recieve it in the mail. Our commitment, is to keep you up to date with the latest in Angular, so you don't have to.

More articles similar to this


Razroo is committed towards contributing to open source. Take the pledge towards open source by tweeting, #itaketherazroopledge to @_Razroo on twitter. One of our associates will get back to you and set you up with an open source project to work on.