Rxjs provides a paradigm for dealing with asynchronous operations in a way that resembles synchronous code. It uses Observables to represent asynchronous data streams over time that can be composed using operators. This allows handling of events, asynchronous code, and other reactive sources in a declarative way. Key points are: - Observables represent asynchronous data streams that can be subscribed to. - Operators allow manipulating and transforming streams through methods like map, filter, switchMap. - Schedulers allow controlling virtual time for testing asynchronous behavior. - Promises represent single values while Observables represent continuous streams, making Observables more powerful for reactive programming. - Cascading asynchronous calls can be modeled elegantly using switch

1. Rxjs
everything is a stream
Christoffer Noring
Google Developer Expert
@chris_noring

2. Why Rxjs?
We want to deal with async in a “synchronous looking way”
We want something better than promises
We want one paradigm for async to rule them all

3. nce upon a time in async land
There were callbacks
Callbacks turned into callback hell

4. Promises to the rescue
service
.getData()
.then(getMoreData)
.then(getEvenMore)
.then(andSomeMore)
Looks great right?

5. But promises were flawed
No cancellation
eal with other async concepts like mouse positions, clicks, use
No rich composition
And brexit happened
Cumbersome to retry
Only returns one value

6. Help us Observables
You’re my only hope

7. What is an observable
Observable is just a function
that takes an observer and returns a function
Observer: an object with next, error, complete methods
Rx.Observable.create((observer) => {
observer.next(1);
observer.error(‘error’);
observer.complete();
})
1 2 3 4 5 6 7
stream of value over time

8. Promise
vs Array
vs Observable
list
.map( x = > x.prop )
.filter( x => x > 2 )
.take( 2 )
Array
list
.map( x = > x.prop )
.filter( x => x > 2 )
.take( 2 )
.subscribe(
x => console.log(x),
err => console.log(err) )
Observable
Promise
service.get()
.then( x => console.log(x) )
.catch( err => console.log(err) ) but can also
- Cancelled
- Retried
Array like,
handles async

9. So pretty much linq with
async

10. Rx.Observable.create(
fnValue,,
fnError,,
fnCompleted
)
Observable signature

11. var stream = Rx.Observable.create((observer) =>{
})})
Emits
stream
.subscribe(
(data) => { console.log( data ); }
)
1
next()
observer.next(1);
2
next()
observer.next(2);
3
next()
observer.next(3);

12. var stream = Rx.Observable.create((observer) =>{
})
stream
.subscribe(
(data) => { console.log( data ); }
(err) => { console.log(err); }
)
Emits 1
next()
observer.next(1);
error message
error()
observer.error(‘something went wrong’)

13. var stream = Rx.Observable.create((observer) =>{
})})
stream
.subscribe(
(data) => { console.log( data ); }
(err) => { console.log(err) },
() => { console.log(‘completed’) }
)
Emits 1
next()
observer.next(1);
complete()
observer.complete();

14. Cancelling
.unsubscribe()

15. var homemadeStream = Rx.Observable.create((observer) => {
var i=0;
});
var subscription2 = homemadeStream.subscribe((val) => {
console.log('Homemade val',val);
});
setTimeout(() => {
console.log('Cancelling homemadeStream');
subscription2.unsubscribe();
}, 1500); Calling dispose
Produce values
till someone calls unsubscribe
var handle = setInterval(() => {
observer.next( i++ );
}, 500);
Define whats to happen
on unsubscribe
return function(){
console.log('Disposing timeout');
clearTimeout( handle );
}

16. You will always create
an observable from something

17. Rx.Observable.fromArray([ 1,2,3,4 ])
Rx.Observable.fromEvent(element, ‘event’);
Rx.Observable.fromArray(eventEmitter, ‘data’, function(){})
Rx.Observable.fromNodeCallback(fs.createFile)
Rx.Observable.fromCallback(obj.callback)
Rx.Observable.fromPromise(promise)
Rx.Observable.fromIterable(function *() { yield 20 })
Rx.Observable.range(1,3)
Rx.Observable.interval(miliseconds)

18. Wrap an observable
next()
error()
complete()

19. var stream = Rx.Observable.create((observer) => {
var request = new XMLHttpRequest();
request.open( ‘GET’, ‘url’ );
request.onload =() =>{
if(request.status === 200) {
} else {
}
}
request.onerror = () => { }
request.send();
})
stream.subscribe(
)
observer.next( request.response );
(result) => { console.log( result ); }
Get our data
observer.complete();
() => { console.log(‘completed’); }
No more data, close stream
observer.error( new Error( request.statusText ) )
(err) => { console.log(err) },
observer.error( new Error(‘unknown error’) );
Error
Error

20. Hot vs Cold Observable

21. Cold Observable
recorded tv show
Hot observable
Live streaming
eg World Cup Final

22. Observables are cold by default,
unless you make them hot
var stream = Rx.Observable.interval(1000);
stream.subscribe(
(val) => { console.log('Subscriber 1', val);}
);
stream.subscribe(
(val) => { console.log('Subscriber 2', val); }
);
var stream = Rx.Observable
.interval(1000)
.publish();
stream.subscribe((val) => {
console.log('Subscriber 1', val);
});
setTimeout(function() {
stream.connect();
}, 2000);
setTimeout(() => {
stream.subscribe((val) => {
console.log('Value', val);
});
}, 4000);
Subscriber 2 Values 0 1 2 3 4
Subscriber 1 Values 0 1 2 3 4
0 1 2 3 4 5 6
3 4 5 6

23. You can create an observable
from almost any async concept
Operators however gives it
its power
Remember:
But:

24. Operators
makes your code look like linq

25. 120+ operators Rxjs 4
60+ Rxjs 5
Combination
Conditional
Multicasting
Filtering
Transformation
Utility
Categories
in production

26. Marble diagram
how does that operator work

27. Operator
Most operators are covered at rxmarbles.com
Stream 1 2 3
Other stream 4 5
Resulting stream 1 2 3 4 5

28. Operator example
var stream = Rx.Observable.of(1,2,3,4,5);
stream
stream.subscribe((data) => { console.log(‘data’); })
Operators :
map()
filter()
3
Emits
6
.map((val) => {
return val + 1;
})
changes the value
.filter((val) => {
return val % 3 === 0;
})
filters out values

29. Do
var stream = Rx.Observable.of(1,2,3,4,5);
var subscription = stream
.filter(function(val){
return val % 2 === 0;
});
subscription.subscribe(function(val){
console.log('Val',val);
})
Echos every value
without changing it,
used for logging
.do((val) => {
console.log('Current val', val);
})
Current val 1
Current val 2
Current val 3
Current val 4
Current val 5
Subscribe:
2
4

30. debounce
var debounceTime = Rx.Observable
.fromEvent(button,'click')
debounceTime.subscribe( function(){
console.log('mouse pressed');
})
waits x ms and
returns latest emitted
Ignores all generated
mouse click events
for 2 seconds.debounce(2000);
Clicking save button
2secclick click click click click
save()

31. switchMap
Switch map,
complete something based on a condition
breakCondition = Rx.Observable.fromEvent(document,'click');
breakCondition.switchMap((val) => {
return Rx.Observable.interval(3000).mapTo(‘Do this');
})
breakCondition.subscribe((val) => {
console.log('Switch map', val);
})
Intended action is completed/restarted
by ‘breakCondition’
etc..
Do this
Do this
Do this
Do this
Do this
click
click

32. source.subscribe((data) => {
console.log( data );
})
flatMap
let source = Rx.DOM.getJSON( 'data2.json' )
return Rx.Observable.fromArray( data ).map((row) => {
return row.props.name;
});
return observable
.flatMap((data) => {
} );
We get an array response that we want to emit row by row
We use flatMap instead of map because :
We want to flatten our list to one stream

33. flatMap explained
when you create a list of observables flatMap flattens that list s
Great when changing from one type of stream to another
Without it you would have to listen to every single substream, w
eve
nt
eve
nt
eve
nt
eve
nt
ajax ajax ajax ajax
json json json json
flatMap
map

34. Problem : Autocomplete
Listen for keyboard presses
Filter so we only do server trip after x number of
chars are entered
Do ajax call based on filtered input
Cash responses,
don’t do unnecessary calls to http server

35. The procedural approach

36. let input = $(‘#input’);
input.bind(‘keyup’,() = >{
let val = input.val()
if(val.length >= 3 ) {
if( isCached( val ) ) { buildList( getFromCache(val) ); return; }
doAjax( val ).then( (response) => {
buildList( response.json() )
storeInCache( val, response.json() )
});
}
})
fetch if x characters long
return if cached
do ajax
Ok solution but NOT so fluent
We need 3 methods to deal with cache

37. The observable approach

38. Stream modeling
key key key key key key
FILTER
AJAX CALL
jso
n
jso
n
MAP
key key key key key key key
respons
e
respons
e

39. flatmapExample = Rx.Observable.fromEvent(input,'keyup')
flatmapExample.subscribe(
(result) =>{ console.log('Flatmap', result); buildList( result ) }
)
more fluent
Transform event to char.map((ev) => {
return ev.target.value;
})
Wait until we have 3 chars
.filter(function(text){
return text.length >=3;
})
Only perform search if this ‘search’ is unique.distinctUntilChanged()
Excellent to use when
coming from
one stream to another
.switchMap((val) => {
return Rx.DOM.getJSON( 'data3.json' );
})

40. Error handling
when streams fail

41. error
completion
.catch() completion
completion
no values
completion
values, WIN!
.catch()
merge
.catch()
merge

42. onErrorResumeNext
completion
values, WIN
error
completion
no values

43. retry
let stream = Rx.Observable.interval(1000)
.take(6);
.map((n) => {
if(n === 2) {
throw 'ex';
}
return n;
})
Produce error
.retry(2)
Number of tries
before hitting error callback
stream.subscribe(
(data) => console.log(data)
(error) => console.log(error)
1
Emits
3
Makes x attempts before error cb is called

44. retryWhen
delay between attempts
let stream = Rx.Observable.interval(1000)
.take(6);
delay, 200 ms.retryWhen((errors) => {
return errors.delay(200);
})
.map((n) => {
if(n === 2) {
throw 'ex';
}
return n;
})
produce an error when
= 2
stream.subscribe(
(data) => console.log(data)
(error) => console.log(error) for those shaky connections

45. What did we learn so far?
We can cancel with .unsubsribe()
We can retry easily
A stream generates a continuous stream of values
Operators manipulate either the values or the stream/s
We can “patch” an erronous stream with a .catch()
or
Ignore a failing stream altogether
with onErrorResumeNext

46. Schedulers
bending time

47. What about schedulers and
testing?
Because scheduler has its own virtual clock
Anything scheduled on that scheduler
will adhere to time denoted on the clock
I.e we can bend time for ex unit testing

48. Schedulers
testingvar testScheduler =
new Rx.TestScheduler();
var stream =
Rx.Observable
.interval(1000, testScheduler)
.take(5)
.map((val) => {
return val + 1
})
.filter((i) => {
return i % 2 === 0
});
var result;
stream.subscribe((val) => result = val );
console.log('testing function’);
testScheduler.advanceBy(1000);
testScheduler.advanceBy(1000);
console.log('Should equal', result === 4);
increment operator
testScheduler.advanceBy(1000);
testScheduler.advanceBy(1000);
testScheduler.advanceBy(1000);
assert
console.log('Should equal', result === 2);

49. Comparing promises
to Rxjs

50. .then vs .subscribe
getData()
.then(
)
getData().subscribe(
)
I will keep on streaming values
(data) => console.log(data),
(data) => console.log(data),
(err) => console.log(err) (err) => console.log(err)

51. user
order
orderItem
Fetch user
Then fetch order
Lastly fetch order item

52. Cascading calls
Response:
//getUser
stream
.subscribe((orderItem) => {
console.log('OrderItem',orderItem.id);
})
{ id: 11, userId : 1 }.then(getOrderByUser)
.switchMap((user) => {
//getOrder
return Rx.Observable.of({ id : 11, userId : user.id }).delay(3000)
})
{ id: 123, orderId : 11 }.then(getOrderItemByOrder)
.switchMap((order) => {
//getOrderItem
return Rx.Observable.of({ id: 114, orderId: order.id })
})
{ id: 1 }getUser()
var stream = Rx.Observable.of({ id : 1 });
So we can see the
first user observable
being dropped when
user 2 is emitted

53. Short word on switchMap
is to ensure we throw away the other calls when a new user is em
We don’t want
getUser
getOrderByUser
getOrderItemByOrder
to complete if a new user is emitted
1 2 3
2 4 5
Not continued
Replaces above
stream

54. user
orders messages
Fetch user
Fetch in parallell

55. Cascading call
wait for the first
.subscribe(
(data) => {
console.log( 'orders', data[0] );
console.log( 'messages', data[0] );
}
)
var stream = Rx.Observable.of([{ id : 1 }, { id : 2 }]);
getUser()
We wait for user
function getOrdersAndMessages(user){
return Promise.all([
getOrdersByUser( user.id ),
getMessagesByUser( user.id )
])
}
.then(getOrdersAndMessages)
stream.switchMap((user) => {
return Rx.Observable.forkJoin(
Rx.Observable.of([ { id: 1, userId : user.id } ]).delay(500), // orders
Rx.Observable.of([ { id: 100, userId : user.id } ]).delay(1500) //messages
)
})
Calls to orders and message
can happen in parallel
Orders,Messages
arrive at the same time

56. Last summary
We can use schedulers to easily test our code
Cascading calls can easily be setup
switchMap over flatMap when doing ajax calls
because we need it to abandon the stream if
the first condition change

57. Rxjs
An elegant weapon for a
more civilized age
Remember..

58. Thank you