So, I'm currently learning to think Reactively thanks to RxJS. Now, I'm currently reading an RxJS book (Reactive Programming with RxJS) and I've read about AsyncSubject and how it only caches the last value received. What I'd like to know is, what happens if I want to update the server and have this observable update? Since onComplete has been called, do I need to create a brand new observer? Is there another pattern I should follow?
My overall requirement is that I'd like to have a means to cleanly pass data to and from the server and keep my observable (model) fresh at all times.
Thanks,
Lee
As you suspected, you cannot change the value of an AsyncSubject after onCompleted has been called. The typical way of dealing with a simple "call the server as required, cache the value between calls" scenario is to use flatMapLatest to map your trigger observable to an AsyncSubject representing your server call. For example, if you wanted to refresh some data every 30 seconds, you might do something like this:
const subscription = Rx.Observable
.interval(30000)
.flatMapLatest(() => serverCall())
.subscribe(x => doStuffWithResult(x));
In your case I would consider using Websockets, since you want your observable (model) fresh at all times
Something like
var source = Rx.Observable.create(function (observer) {
websocket.onmessage = function( msg ) {
observer.onNext( msg );
}
websocket.onerror = function( error ) {
observer.onError( error );
}
websocket.onclose = function ( msg ) {
observer.onComplete( msg );
}
});
Otherwise you can use an interval
const subscription = Rx.Observable
.interval(1000)
.flatMapLatest(() => Rx.Observable.fromPromise(fetch( ... ).then( response => response.json() ).retry(5))
.subscribe( response => response );
You can always use the retry operator to not give up immediately if there is an error.
Related
I have the following observable: messages$: Observable<Message[] | undefined>. Message has 2 fields: id and content, both of which are string.
What I would like to do is to modify messages$ so that a function foo(string) is invoked on the content of each Message.
It doesn't seem difficult at face value but I'm new to observables and unfortunately I got stuck.
I guess solution is simple:
messages$: Observable<Message[] | undefined> = yourSource
.pipe(
map(messages => {
messages.forEach(value => {
value.content = foo(value.content);
});
return messages;
}
)
What you are asking is how can you change your Observable to an observable with sideeffect. You probably don't ever want that (except for simple cases like logging stuff).
Instead what you want to do is subscribe to that Observable and then do your logic in the subscription. That way you're also guaranteed that your logic is only run once (or the number you want) instead of being reliant on something else subscribing to the observable.
messages$.subscribe(({ content }) => { foo(content); });
Be careful of subscription that is not unsubscribed.
Check out this question for a solution to that generic problem:
RXJS - Angular - unsubscribe from Subjects
If i misunderstood your question, and what you really want is an observable that transforms the data, and your foo method is pure (does not modify the inputs or other external data), the solution is different:
const modifiedMessages$ = messages$.pipe(map(({ content }) => foo(content));
I have an observable (onAuthStateChanged) from the Firebase client that:
emits null immediately if the user is not signed in, and
emits null and then a user object a few moments later if the user is signed in.
const observable = new Observable((obs) => {
return app.auth().onAuthStateChanged(
obs.next,
obs.error,
obs.complete
)
})
What I want is to:
ignore any emitted null values for the first 1000ms of the app lifecycle (null coming after 1000ms is accepted)
always emit user object regardless of what time it comes
if no user object comes in the first 1000ms, then emit null at the 1000ms mark
Here is what I've done (and it seems to work). However, I'm reluctant to use this code as it doesn't seem that concise:
const o1 = observable.pipe(skipUntil(timer(1000)))
const o2 = observable.pipe(
takeUntil(o1),
filter((user) => user !== null)
)
const o3 = timer(1000).pipe(takeUntil(o2), mapTo(null))
merge(o1, o2, o3).subscribe({
next: setUser,
error: console.log,
complete: () => console.log("error: obs completed, this shouldn't happen"),
})
Is there a way to do this without merge? I tried going through the docs but I'm quite lost.
Thanks for your help!
You could use concat instead of merge. Think of it as using the first source until it completes, then use the second source.
const nonNullUser = firebaseUser.pipe(
filter(user => user !== null),
takeUntil(timer(1000))
);
const user = concat(nonNullUser, firebaseUser);
user.subscribe(...);
I just realized that this solution will not explicitly perform step #3 "emit null at the 1000ms mark". I was thinking subscribing to firebaseUser would emit the latest value. But, I'm not sure if that's true for your scenario.
If not, we could easily achieve this by adding shareReplay like this:
const firebaseUser = observable.pipe(shareReplay(1));
While I liked the answer from #BizzyBob I was genuinely intrigued by these requirements that I wanted to see what other options were available. Here's what I produced:
const auth$ = observable.pipe(
startWith(null)
)
const null$ = timer(1000).pipe(
switchMap(_=>auth$)
)
const valid$ = auth$.pipe(
filter(user=>!!user)
)
const user$ = race(null$, valid$);
We have our source auth$ observable which gets your Firebase data. However, startWith() will immediately emit null before any values coming from Firebase.
I declared two observables for null and non-null cases, null$ and valid$.
The null$ observable will subscribe to auth$ after 1000ms. When this happens it immediately emits null thanks to the startWith() operator.
The valid$ observable subscribes to auth$ immediately but only emits valid user data thanks to filter(). It won't emit startWith(null) because it is caught by the filter.
Last, we declare user$ by using the race() operator. This operator accepts a list of observables as its parameters. The first observable to emit a value wins and is the resulting subscription.
So in our race, valid$ has 1000ms to emit a valid user. If it doesn't, race() will subscribe to null$ resulting in the immediate null, and all future values coming from Firebase.
I have an angular application that makes a request to an Http service and calls a switchMap on another Http service. For some reason the request in the switchMap only runs the first time the parent call is called. Otherwise the parent request fires and the switchMap one doesn't, here is the code:
this._receivableService.newTenantDebitCredit(tenantCredit)
.take(1)
.switchMap(result =>
// Refresh the lease receivables before giving result
this._receivableService.getAll({
refresh: true,
where: { leaseId: this.leaseId }
}).take(1).map(() => result)
)
.subscribe(
...
)
How can I make the getAll request in the switch map run every time the newTenantDebitCredit method is called above it?
Edit: Here is the entirety of the function that is called on click. when i click the button the first time for a given unit both methods are executed. If I try a Unit that has already had that method called (without a refresh) only the first method is executed. I realize a lot of this may not be clear it's a rather large project at this point.
public submitTenantCredit() {
this.isLoading = true;
let tenantCredit: NewTenantDebitCreditData;
let receivableDefinitions: ReceivableDefinition[] = [];
// construct receivable defintions for NewTenantDebitData model
receivableDefinitions = this._constructReceivableDefinitions();
// construct data we will be POSTing to server.
tenantCredit = new NewTenantDebitCreditData({
siteId: this._apiConfig.siteId,
leaseId: this.leaseId,
isCredit: true,
receivables: receivableDefinitions,
reason: this.actionReason
});
// make service call and handle response
this._receivableService.newTenantDebitCredit(tenantCredit)
.take(1)
.switchMap(result =>
// Refresh the lease receivables before giving result
this._receivableService.getAll({
refresh: true,
where: { leaseId: this.leaseId }
}).take(1).map(() => result)
)
.take(1)
.subscribe(
(receivables) => {
this.closeReasonModal();
let refreshLeaseId = this.leaseId;
this.leaseId = refreshLeaseId;
this.isLoading = false;
this.refreshBool = !this.refreshBool;
this._debitCreditService.refreshUnitInfo();
this._notifications.success(`The tenant credit for ${this.customerName} - Unit ${this.unitNumber} was submitted successfully`);
},
(error) => {
console.error(error);
this.isLoading = false;
}
)
}
If it helps newTenantDebitCredit() is a HTTP POST request and getAll() is a GET request.
You used take operator. When your service observable will emit then take operator will execute first and take will chain only first emit from observable. Subsequent emit will not taken by your code.
If you want to take all emits from observable then remove take from your code.
Hope it will help.
Testing the Rx code in isolation, here's a mockup. The console logs happen each time, so I think the Rx you're using is ok.
The best guess at a likely culprit is this.refreshBool = !this.refreshBool, but we'd need to see the internals of newTenantDebitCredit and getAll to be definitive.
// Some mocking
const _receivableService = {
newTenantDebitCredit: (tc) => {
console.log('inside newTenantDebitCredit')
return Rx.Observable.of({prop1:'someValue'})
},
getAll: (options) => {
console.log('inside getAll')
return Rx.Observable.of({prop2:'anotherValue'})
}
}
const tenantCredit = {}
// Test
_receivableService.newTenantDebitCredit(tenantCredit)
.take(1)
.switchMap(result => {
console.log('result', result)
return _receivableService.getAll({
refresh: true,
where: { leaseId: this.leaseId }
})
.take(1)
.map(() => result)
})
.take(1)
.subscribe(
(receivables) => {
console.log('receivables', receivables)
//this.refreshBool = !this.refreshBool;
},
(error) => {
console.error(error);
}
)
<script src="https://cdnjs.cloudflare.com/ajax/libs/rxjs/5.5.6/Rx.js"></script>
First of all, this has nothing to do with the switchMap operator.
Normaly removing the take(1) would cause this behaviour. In this case it wouldn't because it itsn't a so called hot observable.
The problem is that you are using a http.post. This is a cold observable which means it will only return a value once. That is also the reason why you don't need to unsubscribe. It will NEVER fire twice. Possible sollutions might be:
Using web sockets to get realtime data.
Creating a timer which will periodically fetch the data.
Simply get the data again whenever you need it.
The way you are asking the question
How can I make the getAll request in the switch map run every time the newTenantDebitCredit method is called above it?
actually sounds to me as if you are calling only newTenantDebitCredit from somewhere in your code, expecting the second request to happen; so I think this might be a misunderstanding of how observable chains work. Let's make an example:
const source$ = Observable.of(42);
source$
.map(value => 2 * value)
.subscribe(console.log);
source$
.subscribe(console.log);
What would you expect this to log? If your answer is "It would log 84 twice", then that is wrong: it logs 84 and 42.
Conceptually, your situation is the same. The second request only happens when the observable returned by newTenantDebitCredit() emits; it will not happen anytime some caller calls newTenantDebitCredit. This is because observable chains do not mutate an observable in-place, they only ever return a new observable.
If you want the second request to happen, you have to actually change the definition of the newTenantDebitCredit method to return an observable set up to perform the second request; alternatively, set up a chained observable that you subscribe to instead of calling newTenantDebitCredit.
Not really an answer but I did solve my problem. It will almost certainly be of no use to anyone BUT it was an issue in the receivableService it was not properly cheeking the boolean: refresh and was pulling values from cache after the first time.
I'm trying to create an observable flow that fulfills the following requirements:
Loads data from storage at subscribe time
If the data has not yet expired, return an observable of the stored value
If the data has expired, return an HTTP request observable that uses the refresh token to get a new value and store it
If this code is reached again before the request has completed, return the same request observable
If this code is reached after the previous request completed or with a different refresh token, start a new request
I'm aware that there are many different answers on how to perform step (3), but as I'm trying to perform these steps together I am looking for guidance on whether the solution I've come up with is the most succinct it can be (which I doubt!).
Here's a sample demonstrating my current approach:
var cachedRequestToken;
var cachedRequest;
function getOrUpdateValue() {
return loadFromStorage()
.flatMap(data => {
// data doesn't exist, shortcut out
if (!data || !data.refreshtoken)
return Rx.Observable.empty();
// data still valid, return the existing value
if (data.expires > new Date().getTime())
return Rx.Observable.return(data.value);
// if the refresh token is different or the previous request is
// complete, start a new request, otherwise return the cached request
if (!cachedRequest || cachedRequestToken !== data.refreshtoken) {
cachedRequestToken = data.refreshtoken;
var pretendHttpBody = {
value: Math.random(),
refreshToken: Math.random(),
expires: new Date().getTime() + (10 * 60 * 1000) // set by server, expires in ten minutes
};
cachedRequest = Rx.Observable.create(ob => {
// this would really be a http request that exchanges
// the one use refreshtoken for new data, then saves it
// to storage for later use before passing on the value
window.setTimeout(() => { // emulate slow response
saveToStorage(pretendHttpBody);
ob.next(pretendHttpBody.value);
ob.completed();
cachedRequest = null; // clear the request now we're complete
}, 2500);
});
}
return cachedRequest;
});
}
function loadFromStorage() {
return Rx.Observable.create(ob => {
var storedData = { // loading from storage goes here
value: 15, // wrapped in observable to delay loading until subscribed
refreshtoken: 63, // other process may have updated this between requests
expires: new Date().getTime() - (60 * 1000) // pretend to have already expired
};
ob.next(storedData);
ob.completed();
})
}
function saveToStorage(data) {
// save goes here
}
// first request
getOrUpdateValue().subscribe(function(v) { console.log('sub1: ' + v); });
// second request, can occur before or after first request finishes
window.setTimeout(
() => getOrUpdateValue().subscribe(function(v) { console.log('sub2: ' + v); }),
1500);
First, have a look at a working jsbin example.
The solution is a tad different then your initial code, and I'd like to explain why. The need to keep returning to your local storage, save it, save flags (cache and token) didn't not fit for me with reactive, functional approach. The heart of the solution I gave is:
var data$ = new Rx.BehaviorSubject(storageMock);
var request$ = new Rx.Subject();
request$.flatMapFirst(loadFromServer).share().startWith(storageMock).subscribe(data$);
data$.subscribe(saveToStorage);
function getOrUpdateValue() {
return data$.take(1)
.filter(data => (data && data.refreshtoken))
.switchMap(data => (data.expires > new Date().getTime()
? data$.take(1)
: (console.log('expired ...'), request$.onNext(true) ,data$.skip(1).take(1))));
}
The key is that data$ holds your latest data and is always up to date, it is easily accessible by doing a data$.take(1). The take(1) is important to make sure your subscription gets a single values and terminates (because you attempt to work in a procedural, as opposed to functional, manner). Without the take(1) your subscription would stay active and you would have multiple handlers out there, that is you'll handle future updates as well in a code that was meant only for the current update.
In addition, I hold a request$ subject which is your way to start fetching new data from the server. The function works like so:
The filter ensures that if your data is empty or has no token, nothing passes through, similar to the return Rx.Observable.empty() you had.
If the data is up to date, it returns data$.take(1) which is a single element sequence you can subscribe to.
If not, it needs a refresh. To do so, it triggers request$.onNext(true) and returns data$.skip(1).take(1). The skip(1) is to avoid the current, out dated value.
For brevity I used (console.log('expired ...'), request$.onNext(true) ,data$.skip(1).take(1))). This might look a bit cryptic. It uses the js comma separated syntax which is common in minifiers/uglifiers. It executes all statements and returns the result of the last statement. If you want a more readable code, you could rewrite it like so:
.switchMap(data => {
if(data.expires > new Date().getTime()){
return data$.take(1);
} else {
console.log('expired ...');
request$.onNext(true);
return data$.skip(1).take(1);
}
});
The last part is the usage of flatMapFirst. This ensures that once a request is in progress, all following requests are dropped. You can see it works in the console printout. The 'load from server' is printed several times, yet the actual sequence is invoked only once and you get a single 'loading from server done' printout. This is a more reactive oriented solution to your original refreshtoken flag checking.
Though I didn't need the saved data, it is saved because you mentioned that you might want to read it on future sessions.
A few tips on rxjs:
Instead of using the setTimeout, which can cause many problems, you can simply do Rx.Observable.timer(time_out_value).subscribe(...).
Creating an observable is cumbersome (you even had to call next(...) and complete()). You have a much cleaner way to do this using Rx.Subject. Note that you have specifications of this class, the BehaviorSubject and ReplaySubject. These classes are worth knowing and can help a lot.
One last note. This was quite a challange :-) I'm not familiar with your server side code and design considerations yet the need to suppress calls felt uncomfortable to me. Unless there is a very good reason related to your backend, my natural approach would be to use flatMap and let the last request 'win', i.e. drop previous un terminated calls and set the value.
The code is rxjs 4 based (so it can run in jsbin), if you're using angular2 (hence rxjs 5), you'll need to adapt it. Have a look at the migration guide.
================ answers to Steve's other questions (in comments below) =======
There is one article I can recommend. It's title says it all :-)
As for the procedural vs. functional approach, I'd add another variable to the service:
let token$ = data$.pluck('refreshtoken');
and then consume it when needed.
My general approach is to first map my data flows and relations and then like a good "keyboard plumber" (like we all are), build the piping. My top level draft for a service would be (skipping the angular2 formalities and provider for brevity):
class UserService {
data$: <as above>;
token$: data$.pluck('refreshtoken');
private request$: <as above>;
refresh(){
request.onNext(true);
}
}
You might need to do some checking so the pluck does not fail.
Then, each component that needs the data or the token can access it directly.
Now lets suppose you have a service that needs to act on a change to the data or the token:
class SomeService {
constructor(private userSvc: UserService){
this.userSvc.token$.subscribe(() => this.doMyUpdates());
}
}
If your need to synthesize data, meaning, use the data/token and some local data:
Rx.Observable.combineLatest(this.userSvc.data$, this.myRelevantData$)
.subscribe(([data, myData] => this.doMyUpdates(data.someField, myData.someField));
Again, the philosophy is that you build the data flow and pipes, wire them up and then all you have to do is trigger stuff.
The 'mini pattern' I've come up with is to pass to a service once my trigger sequence and register to the result. Lets take for example autocomplete:
class ACService {
fetch(text: string): Observable<Array<string>> {
return http.get(text).map(response => response.json().data;
}
}
Then you have to call it every time your text changes and assign the result to your component:
<div class="suggestions" *ngFor="let suggestion; of suggestions | async;">
<div>{{suggestion}}</div>
</div>
and in your component:
onTextChange(text) {
this.suggestions = acSVC.fetch(text);
}
but this could be done like this as well:
class ACService {
createFetcher(textStream: Observable<string>): Observable<Array<string>> {
return textStream.flatMap(text => http.get(text))
.map(response => response.json().data;
}
}
And then in your component:
textStream: Subject<string> = new Subject<string>();
suggestions: Observable<string>;
constructor(private acSVC: ACService){
this.suggestions = acSVC.createFetcher(textStream);
}
onTextChange(text) {
this.textStream.next(text);
}
template code stays the same.
It seems like a small thing here, but once the app grows bigger, and the data flow complicated, this works much better. You have a sequence that holds you data and you can use it around the component wherever you need it, you can even further transform it. For example, lets say you need to know the number of suggestions, in the first method, once you get the result, you need to further query it to get it, thus:
onTextChange(text) {
this.suggestions = acSVC.fetch(text);
this.suggestionsCount = suggestions.pluck('length'); // in a sequence
// or
this.suggestions.subscribe(suggestions => this.suggestionsCount = suggestions.length); // in a numeric variable.
}
Now in the second method, you just define:
constructor(private acSVC: ACService){
this.suggestions = acSVC.createFetcher(textStream);
this.suggestionsCount = this.suggestions.pluck('length');
}
Hope this helps :-)
While writing, I tried to reflect about the path I took to getting to use reactive like this. Needless to say that on going experimentation, numerous jsbins and strange failures are big part of it. Another thing that I think helped shape my approach (though I'm not currently using it) is learning redux and reading/trying a bit of ngrx (angular's redux port). The philosophy and the approach does not let you even think procedural so you have to tune in to functional, data, relations and flows based mindset.
Within my Flux architected React application I am retrieving data from a store, and would like to create an action to request that information if it does not exist. However I am running into an error where the dispatcher is already dispatching.
My desired code is something like:
getAll: function(options) {
options = options || {};
var key = JSON.stringify(options);
var ratings = _data.ratings[key];
if (!ratings) {
RatingActions.fetchAll(options);
}
return ratings || [];
}
However intermittently fails when the dispatcher is already dispatching an action, with the message Invariant Violation: Dispatch.dispatch(...): Cannot dispatch in the middle of a dispatch.. I am often making requests in response to a change in application state (eg date range). My component where I make the request, in response to a change event from the AppStore has the following:
getStateFromStores: function() {
var dateOptions = {
startDate: AppStore.getStartISOString(),
endDate: AppStore.getEndISOString()
};
return {
ratings: RatingStore.getAll(dateOptions),
};
},
I am aware that event chaining is a Flux antipattern, but I am unsure what architecture is better for retrieving data when it does not yet exist. Currently I am using this terrible hack:
getAll: function(options) {
options = options || {};
var key = JSON.stringify(options);
var ratings = _data.ratings[key];
if (!ratings) {
setTimeout(function() {
if (!RatingActions.dispatcher.isDispatching()) {
RatingActions.fetchAll(options);
}
}, 0);
}
return ratings || [];
},
What would be a better architecture, that avoids event chaining or the dispatcher error? Is this really event chaining? I just want to change the data based on the parameters the application has set.
Thanks!
You can use Flux waitFor() function instead of a setTimeout
For example you have 2 stores registered to the same dispatcher and have one store waitFor the other store to process the action first then the one waiting can update after and dispatch the change event. See Flux docs example
My particular error was occurring because my stores emitted their change event during the action dispatch, while it was still cycling through the listeners. This meant any listeners (ie components) that then triggered an action due to a data change in the store would interrupt the dispatch. I fixed it by emitting the change event after the dispatch had completed.
So this:
this.emit(CHANGE_EVENT);
Became
var self = this;
setTimeout(function() { // Run after dispatcher has finished
self.emit(CHANGE_EVENT);
}, 0);
Still a little hacky (will probably rewrite so doesn't require a setTimeout). Open to solutions that address the architectural problem, rather than this implementation detail.
The reason you get a dispatch in the middle of a previous dispatch, is that your store dispatches an action (invokes an action creator) synchronously in the handler for another action. The dispatcher is technically dispatching until all its registered callbacks have been executed. So, if you dispatch a new action from either of the registered callbacks, you'll get that error.
However, if you do some async work, e.g. make an ajax request, you can still dispatch an action in the ajax callbacks, or the async callback generally. This works, because as soon as the async function has been invoked, it per definition immediately continues the execution of the function and puts the callback on the event queue.
As pointed out by Amida and in the comments of that answer, it's a matter of choice whether to make ajax requests from the store in response to an action, or whether to do it in the store. The key is that a store should only mutate its state in response to an action, not in an ajax/async callback.
In your particular case, this would be exemplified by something like this for your store's registered callback, if you prefer to make the ajax calls from the store:
onGetAll: function(options) {
// ...do some work
request(ajaxOptions) // example for some promise-based ajax lib
.then(function(data) {
getAllSuccessAction(data); // run after dispatch
})
.error(function(data) {
getAllFailedAction(data); // run after dispatch
});
// this will be immediately run during getAllAction dispatch
return this.state[options];
},
onGetAllSuccess: function(data) {
// update state or something and then trigger change event, or whatever
},
onGetAllFailed: function(data) {
// handle failure somehow
}
Or you can just put the ajax call in your action creator and dispatch the "success/failed" actions from there.
you can user the "defer" option in the dispatcher.
In your case it would be like:
RatingActions.fetchAll.defer(options);
In my case, I fetch data through the actions/actions creators. The store is only a dump place that receives the payload of an action.
This means that I would "fetchall" in an action and then pass the result to the store which will do whatever with it and then emit a change event.
Some people consider using stores like me, others think like you.
Some people at Facebook uses "my" approach:
https://github.com/facebook/flux/blob/19a24975462234ddc583ad740354e115c20b881d/examples/flux-chat/js/utils/ChatWebAPIUtils.js#L51
I think it would probably avoid the dispatch problem treating your stores like this, but I may be wrong.
An interesting discussion is this one: https://groups.google.com/forum/#!topic/reactjs/jBPHH4Q-8Sc
where Jing Chen (Facebook engineer) explains what she thinks about how to use stores.