I am having a little trouble understanding how to utilize an asynchronous request. Suppose I have two web services that I want to invoke that return results. After both return results I want to do some operation.
Here is a very simple mach up of what I am trying to do:
AWebService myWebService = new AWebService();
int firstNumber = myWebService.firstMethod();
int secondNumber = myWebService.secondMethod();
Console.WriteLn(firstNumber + secondNumber);
How do I invoke them asynchronously, and wait for them both to respond prior to continuing my code? I'd imagine you'd write something like this (which is some pseduo-code);
AWebService myWebService = new AWebService();
int firstNumber = myWebService.firstMethodAsync();
int secondNumber = myWebService.secondMethodAsync();
someWaitCommand;
Console.WriteLn(firstNumber + secondNumber);
However, the Async methods return null, and I need to set the callback method on a Asynchronous method by method basis. What if I need to call the same web method multiple times but do different things with each request?
As a side note, I am using c# 2.0, and do not have access to the Begin####/End#### methods which seem to be the focus of this topic often.
Related
I have watched Explore structured concurrency in Swift video and other relevant videos / articles / books I was able to find (swift by Sundell, hacking with swift, Ray Renderlich), but all examples there are very trivial - async functions usually only have 1 async call in them. How should this work in real life code?
For example:
...
task = Task {
var longRunningWorker: LongRunningWorker? = nil
do {
var fileURL = state.fileURL
if state.needsCompression {
longRunningWorker = LongRunningWorker(inputURL: fileURL)
fileURL = try await longRunningWorker!.doAsyncWork()
}
let urls = try await ApiService.i.fetchUploadUrls()
if let image = state.image, let imageData = image.jpegData(compressionQuality: 0.8) {
guard let imageUrl = urls.signedImageUrl else {
fatalError("Cover art supplied but art upload URL is nil")
}
try await ApiService.i.uploadData(url: imageUrl, data: imageData)
}
let fileData = try Data(contentsOf: state.fileUrl)
try await ApiService.i.uploadData(url: urls.signedFileUrl, data: fileData)
try await ApiService.i.doAnotherAsyncNetworkCall()
} catch {
longRunningWorker?.deleteFilesIfNecessary()
throw error
}
}
...
Then at some point I will call task.cancel().
Whose responsible for cancelling what? Examples I've seen so far would use try Task.checkCancellation(), but for this code that line should appear every few lines - is that how it should be done?
If API service uses URLSession the calls will be cancelled on iOS 15, but we don't use async variant of URLSession code so we have to cancel the calls manually. Also this applies to all the long running worker code.
I am also thinking that I could add this check within each of async functions, but then basically all async functions would have the same boilerplate code which again seems wrong and I haven't seen that done in any of the videos.
EDIT:
I have removed callback calls as those are irrelevant to the question.
There are two basic patterns for the implementation of our own cancelation logic:
Use withTaskCancellationHandler(operation:onCancel:) to wrap your cancelable asynchronous process.
This is useful when calling a cancelable legacy API and wrapping it in a Task. This way, canceling a task can proactively stop the asynchronous process in your legacy API, rather than waiting until you reach a manual isCancelled or checkCancellation call. This pattern works well with iOS 13/14 URLSession API, or any asynchronous API that offers a cancelation method.
Periodically check isCancelled or try checkCancellation.
This is useful in scenarios where you are performing some manual, computationally intensive process with a loop.
Many discussions about handling cooperative cancelation tend to dwell on these methods, but when dealing with legacy cancelable API, the aforementioned withTaskCancellationHandler is generally the better solution.
So, I would personally focus on implementing cooperative cancelation in your methods that wrap some legacy asynchronous process. And generally the cancelation logic will percolate up, frequently not requiring additional checking further up in the call chain, often handled by whatever error handling logic you might already have.
Examples I've seen so far would use try Task.checkCancellation(), but for this code that line should appear every few lines - is that how it should be done?
Basically yes. Cancellation is a totally voluntary venture. The runtime doesn't know what cancellation means for your particular task, so it just leaves it up to you. You look at Task.isCancelled, or, if your intention is to throw just in case the task is cancelled, you can call Task.checkCancellation.
Note that if, within your task, you are calling (with try) any async material that throws when cancelled, you do not need to any cancellation work with regard to that material, because when it throws due to cancellation, you will throw due to cancellation automatically.
Having said all that, I have to add, as a footnote, that your code is extremely strange. Callbacks and async/await are opposites; the idea that you would do a do/catch and call a callback within a Task is extremely weird and I would advise against it. You are basically negating all the advantages of a Task by doing that, as well as making untrue the thing I just said about the throw trickling up and out of your task.
I'm using SingleLiveEvent to communicate my ViewModel and my Activity. Something like that (pseudocode):
class MyActivity: BaseActivity{
fun onCreate(){
//Init viewmodel and so on
viewModel.commands.observe(this, { command ->
logger.debug("Command received","------>>>>>>>"+command.javaClass.simpleName)
processCommand(command)
})
}
}
And my ViewModel is something like:
class MyViewModel(application: Application) : BaseAndroidViewModel(application) {
val command: SingleLiveEvent<CustomCommands> = SingleLiveEvent()
init{
loadOneThing()
command.postValue(CustomCommands.MessageCommand("one thing loaded"))
loadAnotherThing()
command.postValue(CustomCommands.MessageCommand("another thing loaded"))
}
}
The problem that I'm having, is that the Activity is receiving only the last command, and that is per design. SingleLiveEvent is a Child class from LiveData, and the documentation says the following for the method postValue:
* If you called this method multiple times before a main thread executed a posted task, only
* the last value would be dispatched.
Interestingly, if I set a breakpoint on the line that posts the commands, the emulator/device/main thread has time enough to process the first command, and the second command is sent too. But when executing the app without breakpoints, if the tasks that the viewmodel does between commands are done very fast (no rest requests or things like that, but some calculations), the main thread does not have time enough to finish the first command, and the second command is ignored.
But I really need the View to receive all events/commands that the ViewModel sends.
I suppose the SingleLiveEvent is not the right tool for that use case, nor is LiveData, because of the problem of already consumed events being resent when the device is rotated and so on.
Somebody knows a better approach to do this?
Thanks in advance!
I have faced same problem today. I'm also using SingleLiveEvent for commands/event. I have solved this problem using
commands.value = event instead of commands.postValue(event). Then I wonder why it behaving like that. I found this article. In the article,
But for postValue, the value will be updated twice and the number of times the observers will receive the notification depends on the execution of the main thread. For example, if the postValue is called 4 times before the execution of the main thread, then the observer will receive the notification only once and that too with the latest updated data because the notification to be sent is scheduled to be executed on the main thread. So, if you are calling the postValue method a number of times before the execution of the main thread, then the value that is passed lastly i.e. the latest value will be dispatched to the main thread and rest of the values will be discarded.
I hope it help someone that faced same problem.
have you tried using EventObserver?
/**
* Used as a wrapper for data that is exposed via a LiveData that represents an event.
*/
open class Event<out T>(private val content: T) {
#Suppress("MemberVisibilityCanBePrivate")
var hasBeenHandled = false
private set // Allow external read but not write
/**
* Returns the content and prevents its use again.
*/
fun getContentIfNotHandled(): T? {
return if (hasBeenHandled) {
null
} else {
hasBeenHandled = true
content
}
}
/**
* Returns the content, even if it's already been handled.
*/
fun peekContent(): T = content
}
/**
* An [Observer] for [Event]s, simplifying the pattern of checking if the [Event]'s content has
* already been handled.
*
* [onEventUnhandledContent] is *only* called if the [Event]'s contents has not been handled.
*/
class EventObserver<T>(private val onEventUnhandledContent: (T) -> Unit) : Observer<Event<T>> {
override fun onChanged(event: Event<T>?) {
event?.getContentIfNotHandled()?.let {
onEventUnhandledContent(it)
}
}
}
Use it with live data
val someEvent: MutableLiveData<Event<Unit>>= MutableLiveData()
when you need to some event
fun someEventOccured(){
someEvent.value = Event(Unit)
}
Fragment file, observe the Event
viewModel.someEvent.observe(this, EventObserver {
//somecode
})
I tried to show a progress in angulardart, and thought that a Future would be good for this. But then i realized that a Future must be recursive to show a progress, since the Future returns immediately and the lengthy operation is executed afterwards.
If i create a Future that calls itself until the end condition is met it works with the progressbar. But i think this could not be a very good practice sind these calls will raise the memory on the stack with every recursion. Just consider a loop going through 1 billion datasets that could run a few hours and every loop calls a new Future within the current Future.
Is there a better way to create a loop that needs a certain amount of time to do work on every element (including calling a website that must be done asynchronous and evaluating the return value)? During the loop the user should see a progress that shows him "x/1000000 done".
I think it must be done with a Future since the UI needs to reload after initiating the loop, but a recursive Future seems like a bad idea to me.
You need the future to return back to you right away on the web because it is a single threaded platform. If an async action didn't return until it was complete then you would hang the browser and it wouldn't be a great experience to the user.
Instead you have a couple of options:
Dart has the ability to make the future look like it is synchronous with the await keyword. So you can do something like:
void performAction() async {
showProgress = true;
await expensiveRpc();
showProgress = false;
}
This would require the progress to be intermediate, as you aren't actually updating the progress bar as it goes along. That said if you don't really get progress events from your RPC this is probably the better solution.
Now if your RPC or action gives you some kind of feedback as it goes you can do something a bit nicer with a stream.
void performAction() {
showProgress = true;
expensiveRpc().listen((progress) {
if (progress.done) {
showProgress = false;
} else {
percentComplete = progress.value;
});
}
Really it depends more on the RPC or service you are interacting with on how you can update the progress nicely more than the progress itself.
Meanwhile i recognized that a Future-method returns immediately without executing anything in the method-body. So the solution is pretty easy:
Just declare the rpc with a Future, do whatever you need to do in the method and when calling it, use then(...) to do what you need to do after collecting the data.
int progress = 0;
int progressMax = 100;
bool progressCanceled = false;
Future rpc(var data)
async{
for(progress=0; progress<progressMax, progress++)
{
// do whatever you need to do with data
if(progressCanceled)
return;
}
}
rpc(data).then(
{
if(progressCanceled)
return;
// do whatever is needed after having received that data
});
rpc is executed and the calling process can continue while rpc does what rpc has to do. The main program can handle button clicks to set progressCanceled to true and the rpc-method will ask for the state and stop processing if it is set.
I am fetching data (news articles) in JSON format from a web service. The fetched data needs to be converted to an Article object and that object should be stored or updated in the database. I am using Alamofire for sending requests to the server and Core Data for database management.
My approach to this was to create a DataFetcher class for fetching JSON data and converting it to Article object:
class DataFetcher {
var delegate:DataFetcherDelegate?
func fetchArticlesFromUrl(url:String, andCategory category:ArticleCategory) {
//convert json to article
//send articles to delegate
getJsonFromUrl(url) { (json:JSON?,error:NSError?) in
if error != nil {
print("An error occured while fetching json : \(error)")
}
if json != nil {
let articles = self.getArticleFromJson(json!,andCategory: category)
self.delegate?.receivedNewArticles(articles, fromCategory: category)
}
}
}
After I fetch the data I send it to DataImporter class to store it in database:
func receivedNewArticles(articles: [Article], fromCategory category:ArticleCategory) {
//update the database with new articles
//send articles to delegate
delegate?.receivedUpdatedArticles(articles, fromCategory:category)
}
The DataImporter class sends the articles to its delegate that is in my case the ViewController. This pattern was good when I had only one API call to make (that is fetchArticles), but now I need to make another call to the API for fetching categories. This call needs to be executed before the fetchArticles call in the ViewController.
This is the viewDidLoad method of my viewController:
override func viewDidLoad() {
super.viewDidLoad()
self.dataFetcher = DataFetcher()
let dataImporter = DataImporter()
dataImporter.delegate = self
self.dataFetcher?.delegate = dataImporter
self.loadCategories()
self.loadArticles()
}
My questions are:
What is the best way to ensure that one the call to the API gets executed before the other one?
Is the pattern that I implemented good since I need to make different method for different API calls?
What is the best way to ensure that one the call to the API gets executed before the other one?
If you want to ensure that two or more asynchronous functions execute sequentially, you should first remember this:
If you implement a function which calls an asynchronous function, the calling function becomes asynchronous as well.
An asynchronous function should have a means to signal the caller that it has finished.
If you look at the network function getJsonFromUrl - which is an asynchronous function - it has a completion handler parameter which is one approach to signal the caller that the underlying task (a network request) has finished.
Now, fetchArticlesFromUrl calls the asynchronous function getJsonFromUrl and thus becomes asynchronous as well. However, in your current implementation it has no means to signal the caller that its underlying task (getJsonFromUrl) has finished. So, you first need to fix this, for example, through adding an appropriate completion handler and ensuring that the completion handler will eventually be called from within the body.
The same is true for your function loadArticles and loadCategories. I assume, these are asynchronous and require a means to signal the caller that the underlying task has finished - for example, by adding a completion handler parameter.
Once you have a number of asynchronous functions, you can chain them - that is, they will be called sequentially:
Given, two asynchronous functions:
func loadCategories(completion: (AnyObject?, ErrorType?) -> ())
func loadArticles(completion: (AnyObject?, ErrorType?) -> ())
Call them as shown below:
loadCategories { (categories, error) in
if let categories = categories {
// do something with categories:
...
// Now, call loadArticles:
loadArticles { (articles, error) in
if let articles = articles {
// do something with the articles
...
} else {
// handle error:
...
}
}
} else {
// handler error
...
}
}
Is the pattern that I implemented good since I need to make different method for different API calls?
IMHO, you should not merge two functions into one where one performs the network request and the other processes the returned data. Just let them separated. The reason is, you might want to explicitly specify the "execution context" - that is, the dispatch queue, where you want the code to be executed. Usually, Core Data, CPU bound functions and network functions should not or cannot share the same dispatch queue - possibly also due to concurrency constraints. Due to this, you may want to have control over where your code executes through a parameter which specifies a dispatch queue.
If processing data may take perceivable time (e.g. > 100ms) don't hesitate and execute it asynchronously on a dedicated queue (not the main queue). Chain several asynchronous functions as shown above.
So, your code may consist of four asynchronous functions, network request 1, process data 1, network request 2, process data 2. Possibly, you need another function specifically for storing the data into Core Data.
Other hints:
Unless there's a parameter which can be set by the caller and which explicitly specifies the "execution context" (e.g. a dispatch queue) where the completion handler should be called on, it is preferred to submit the call of the completion handler on a concurrent global dispatch queue. This performs faster and avoids dead locks. This is in contrast to Alamofire that usually calls the completion handlers on the main thread per default and is prone to dead locks and also performs suboptimal. If you can configure the queue where the completion handler will be executed, please do this.
Prefere to execute functions and code on a dispatch queue which is not associated to the main thread - e.g. not the main queue. In your code, it seems, the bulk of processing the data will be executed on the main thread. Just ensure that UIKit methods will execute on the main thread.
I've seen 2 flavors of working with asyncronous operations in mvc controllers.
First:
public void GetNewsAsync()
{
AsyncManager.OutstandingOperations.Increment();
using (ManualResetEvent mre = new ManualResetEvent(false))
{
//Perform the actual operation in a worker thread
ThreadPool.QueueUserWorkItem((object _mre) =>
{
//do some work in GetFeed that takes a long time
var feed = GetFeed();
AsyncManager.Parameters["Feed"] = feed;
AsyncManager.OutstandingOperations.Decrement();
mre.Set();
}, mre);
//Wait for the worker thread to finish
mre.WaitOne(TimeSpan.FromSeconds(SomeNumberOfSecondsToWait));
}
}
Second:
public void GetNewsAsync()
{
AsyncManager.OutstandingOperations.Increment();
//Perform the actual operation in a worker thread
ThreadPool.QueueUserWorkItem((object x) =>
{
//do some work in GetFeed that takes a long time
var feed = GetFeed();
AsyncManager.Parameters["Feed"] = feed;
AsyncManager.OutstandingOperations.Decrement();
}, null);
}
The first blocks GetNewsAsync for SomeNumberOfSecondsToWait, the second does not. Both perform the work inside a of a worker thread and the results passed to GetNewsCompleted.
So my question is, which is the correct way to handle an Ajax call to GetNews; Wait, or don't wait?
I don't know where did you see the first example but that's a total anti-pattern that completely defeats the purpose of an asynchronous controller. The whole point of an asynchronous operation is to execute asynchronously and free the main thread as fast as possible.
This being said if GetFeed is a blocking call (which is what its name supposes it is) you get strictly 0 benefit from an asyncrhonous controller so the second example is also wrong for me. You could use a standard synchronous controller action in this case. With the second example you draw a thread from the pool and instead of blocking inside the main thread you block inside the other thread so the net effect is almost the same (in reality it's worse) if you had used a standard synchronous controller action.
So both those examples will bring more overhead than any benefit.
Where asynchronous controllers are useful is when you have some I/O intensive API such as a database or web service call where you could take advantage of IO Completion Ports. The following article provides a good example of this scenario. The newsService used there is providing real asynchronous methods and there is no blocking during the I/O network call. No worker thread being jeopardized.
I would also recommend you reading the following article. Even if it is for classic WebForms it still contains some very useful information.