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SemaphoreSlim problems with async tasks

I've been attempting to use SemaphoreSlim to limit the amount of concurrent tasks I have running at any one time but it seems to have no effect, likely down to my implementation which is why I'm here. My SemaphoreSlim code is like so:
First it's called by
await Task.Run(() => mc.StartAsync());
Calling this method
public async Task StartAsync()
{
using (SemaphoreSlim concurrencySemaphore = new SemaphoreSlim(5))
{
foreach (var task in ThreadHandler.ThreadList)
{
await concurrencySemaphore.WaitAsync();
try
{
await Task.Run(() => task.Operation.Start());
}
finally
{
concurrencySemaphore.Release();
}
}
}
}
This in turn is starting a task from a list which looks like this, this is in a custom model with the task stored and created previously
public Task Operation { get; set; }
var t = new Task(async () =>
{
await Task.Run(() => Method(input, sps));
});
Remembering my code doesn't work as I'd expect, is this the correct way to start something like this? I don't expect 3 tasks launching from a single point is a good idea. The main reason It's like this is because I'm executing an Action<> and couldn't figure out a way to await it alone. Do these tasks count towards the SemaphoreSlim limit?
After various tests I can confirm that my SemaphoreSlim code is just continuously executing the tasks, I added a large task delay into the list of tasks to see if I could stop it from executing which worked but new tasks were still launched... what am I missing?
My goal is to have a limit on the number of tasks concurrently running, if that wasn't clear. Thank you for any assistance!
EDIT: I think I've realised I'm only awaiting the starting of the task, not the completion.

I think I've realised I'm only awaiting the starting of the task, not the completion.
Indeed, that is the core of the problem.
You shouldn't use the Task constructor, ever, at all, for anything. Just pretend it doesn't exist. It will always lead you down an awkward path.
If you have an action you want to perform at a later time, you should use a delegate: Action or Func<T> for synchronous work, and Func<Task> or Func<Task<T>> for asynchronous work. E.g., if Method is synchronous, then you would have:
public Action Operation { get; set; }
...
Operation = () => Method(input, sps);
Then you can invoke it using Task.Run as such:
public async Task ProcessAsync()
{
using (SemaphoreSlim concurrencySemaphore = new SemaphoreSlim(5))
{
var tasks = ThreadHandler.ThreadList.Select(async task =>
{
await concurrencySemaphore.WaitAsync();
try
{
await Task.Run(() => task.Operation());
}
finally
{
concurrencySemaphore.Release();
}
}).ToList();
await Task.WhenAll(tasks);
}
}
The above code will work fine if Operation is Action (synchronous) or Func<Task> (asynchronous).
However, if it is Action (i.e., synchronous), then what you're really doing is parallel processing, not asynchronous concurrency, and there's built-in types that can help with that:
public void Process()
{
// Only valid if Operation is Action, not Func<Task>!
Parallel.ForEach(
ThreadHandler.ThreadList,
new ParallelOptions { MaxDegreeOfParallelism = 5 },
task => task.Operation());
}

Forcing certain code to always run on the same thread

We have an old 3rd party system (let's call it Junksoft® 95) that we interface with via PowerShell (it exposes a COM object) and I'm in the process of wrapping it in a REST API (ASP.NET Framework 4.8 and WebAPI 2). I use the System.Management.Automation nuget package to create a PowerShell in which I instantiate Junksoft's COM API as a dynamic object that I then use:
//I'm omitting some exception handling and maintenance code for brevity
powerShell = System.Management.Automation.PowerShell.Create();
powerShell.AddScript("Add-Type -Path C:\Path\To\Junksoft\Scripting.dll");
powerShell.AddScript("New-Object Com.Junksoft.Scripting.ScriptingObject");
dynamic junksoftAPI = powerShell.Invoke()[0];
//Now we issue commands to junksoftAPI like this:
junksoftAPI.Login(user,pass);
int age = junksoftAPI.GetAgeByCustomerId(custId);
List<string> names = junksoftAPI.GetNames();
This works fine when I run all of this on the same thread (e.g. in a console application). However, for some reason this usually doesn't work when I put junksoftAPI into a System.Web.Caching.Cache and use it from different controllers in my web app. I say ususally because this actually works when ASP.NET happens to give the incoming call to the thread that junksoftAPI was created on. If it doesn't, Junksoft 95 gives me an error.
Is there any way for me to make sure that all interactions with junksoftAPI happen on the same thread?
Note that I don't want to turn the whole web application into a single-threaded application! The logic in the controllers and elswhere should happen like normal on different threads. It should only be the Junksoft interactions that happen on the Junksoft-specific thread, something like this:
[HttpGet]
public IHttpActionResult GetAge(...)
{
//finding customer ID in database...
...
int custAge = await Task.Run(() => {
//this should happen on the Junksoft-specific thread and not the next available thread
var cache = new System.Web.Caching.Cache();
var junksoftAPI = cache.Get(...); //This has previously been added to cache on the Junksoft-specific thread
return junksoftAPI.GetAgeByCustomerId(custId);
});
//prepare a response using custAge...
}

You can create your own singleton worker thread to achieve this. Here is the code which you can plug it into your web application.
public class JunkSoftRunner
{
private static JunkSoftRunner _instance;
//singleton pattern to restrict all the actions to be executed on a single thread only.
public static JunkSoftRunner Instance => _instance ?? (_instance = new JunkSoftRunner());
private readonly SemaphoreSlim _semaphore;
private readonly AutoResetEvent _newTaskRunSignal;
private TaskCompletionSource<object> _taskCompletionSource;
private Func<object> _func;
private JunkSoftRunner()
{
_semaphore = new SemaphoreSlim(1, 1);
_newTaskRunSignal = new AutoResetEvent(false);
var contextThread = new Thread(ThreadLooper)
{
Priority = ThreadPriority.Highest
};
contextThread.Start();
}
private void ThreadLooper()
{
while (true)
{
//wait till the next task signal is received.
_newTaskRunSignal.WaitOne();
//next task execution signal is received.
try
{
//try execute the task and get the result
var result = _func.Invoke();
//task executed successfully, set the result
_taskCompletionSource.SetResult(result);
}
catch (Exception ex)
{
//task execution threw an exception, set the exception and continue with the looper
_taskCompletionSource.SetException(ex);
}
}
}
public async Task<TResult> Run<TResult>(Func<TResult> func, CancellationToken cancellationToken = default(CancellationToken))
{
//allows only one thread to run at a time.
await _semaphore.WaitAsync(cancellationToken);
//thread has acquired the semaphore and entered
try
{
//create new task completion source to wait for func to get executed on the context thread
_taskCompletionSource = new TaskCompletionSource<object>();
//set the function to be executed by the context thread
_func = () => func();
//signal the waiting context thread that it is time to execute the task
_newTaskRunSignal.Set();
//wait and return the result till the task execution is finished on the context/looper thread.
return (TResult)await _taskCompletionSource.Task;
}
finally
{
//release the semaphore to allow other threads to acquire it.
_semaphore.Release();
}
}
}
Console Main Method for testing:
public class Program
{
//testing the junk soft runner
public static void Main()
{
//get the singleton instance
var softRunner = JunkSoftRunner.Instance;
//simulate web request on different threads
for (var i = 0; i < 10; i++)
{
var taskIndex = i;
//launch a web request on a new thread.
Task.Run(async () =>
{
Console.WriteLine($"Task{taskIndex} (ThreadID:'{Thread.CurrentThread.ManagedThreadId})' Launched");
return await softRunner.Run(() =>
{
Console.WriteLine($"->Task{taskIndex} Completed On '{Thread.CurrentThread.ManagedThreadId}' thread.");
return taskIndex;
});
});
}
}
}
Output:
Notice that, though the function was launched from the different threads, some portion of code got always executed always on the same context thread with ID: '5'.
But beware that, though all the web requests are executed on independent threads, they will eventually wait for some tasks to get executed on the singleton worker thread. This will eventually create a bottle neck in your web application. This is anyway your design limitation.

Here is how you could issue commands to the Junksoft API from a dedicated STA thread, using a BlockingCollection class:
public class JunksoftSTA : IDisposable
{
private readonly BlockingCollection<Action<Lazy<dynamic>>> _pump;
private readonly Thread _thread;
public JunksoftSTA()
{
_pump = new BlockingCollection<Action<Lazy<dynamic>>>();
_thread = new Thread(() =>
{
var lazyApi = new Lazy<dynamic>(() =>
{
var powerShell = System.Management.Automation.PowerShell.Create();
powerShell.AddScript("Add-Type -Path C:\Path\To\Junksoft.dll");
powerShell.AddScript("New-Object Com.Junksoft.ScriptingObject");
dynamic junksoftAPI = powerShell.Invoke()[0];
return junksoftAPI;
});
foreach (var action in _pump.GetConsumingEnumerable())
{
action(lazyApi);
}
});
_thread.SetApartmentState(ApartmentState.STA);
_thread.IsBackground = true;
_thread.Start();
}
public Task<T> CallAsync<T>(Func<dynamic, T> function)
{
var tcs = new TaskCompletionSource<T>(
TaskCreationOptions.RunContinuationsAsynchronously);
_pump.Add(lazyApi =>
{
try
{
var result = function(lazyApi.Value);
tcs.SetResult(result);
}
catch (Exception ex)
{
tcs.SetException(ex);
}
});
return tcs.Task;
}
public Task CallAsync(Action<dynamic> action)
{
return CallAsync<object>(api => { action(api); return null; });
}
public void Dispose() => _pump.CompleteAdding();
public void Join() => _thread.Join();
}
The purpose of using the Lazy class is for surfacing a possible exception during the construction of the dynamic object, by propagating it to the callers.
...exceptions are cached. That is, if the factory method throws an exception the first time a thread tries to access the Value property of the Lazy<T> object, the same exception is thrown on every subsequent attempt.
Usage example:
// A static field stored somewhere
public static readonly JunksoftSTA JunksoftStatic = new JunksoftSTA();
await JunksoftStatic.CallAsync(api => { api.Login("x", "y"); });
int age = await JunksoftStatic.CallAsync(api => api.GetAgeByCustomerId(custId));
In case you find that a single STA thread is not enough to serve all the requests in a timely manner, you could add more STA threads, all of them running the same code (private readonly Thread[] _threads; etc). The BlockingCollection class is thread-safe and can be consumed concurrently by any number of threads.

If you did not say that was a 3rd party tool, I would have asumed it is a GUI class. For practical reasons, it is a very bad idea to have multiple threads write to them. .NET enforces a strict "only the creating thread shall write" rule, from 2.0 onward.
WebServers in general and ASP.Net in particular use a pretty big thread pool. We are talking 10's to 100's of Threads per Core. That means it is really hard to nail any request down to a specific Thread. You might as well not try.
Again, looking at the GUI classes might be your best bet. You could basically make a single thread with the sole purpose of immitating a GUI's Event Queue. The Main/UI Thread of your average Windows Forms application, is responsible for creating every GUI class instance. It is kept alive by polling/processing the event queue. It ends onlyx when it receies a cancel command, via teh Event Queue. Dispatching just puts orders into that Queue, so we can avoid Cross-Threading issues.

Queuing asynchronous task in C#

I have few methods that report some data to Data base. We want to invoke all calls to Data service asynchronously. These calls to data service are all over and so we want to make sure that these DS calls are executed one after another in order at any given time. Initially, i was using async await on each of these methods and each of the calls were executed asynchronously but we found out if they are out of sequence then there are room for errors.
So, i thought we should queue all these asynchronous tasks and send them in a separate thread but i want to know what options we have? I came across 'SemaphoreSlim' . Will this be appropriate in my use case?
Or what other options will suit my use case? Please, guide me.
So, what i have in my code currently
public static SemaphoreSlim mutex = new SemaphoreSlim(1);
//first DS call
public async Task SendModuleDataToDSAsync(Module parameters)
{
var tasks1 = new List<Task>();
var tasks2 = new List<Task>();
//await mutex.WaitAsync(); **//is this correct way to use SemaphoreSlim ?**
foreach (var setting in Module.param)
{
Task job1 = SaveModule(setting);
tasks1.Add(job1);
Task job2= SaveModule(GetAdvancedData(setting));
tasks2.Add(job2);
}
await Task.WhenAll(tasks1);
await Task.WhenAll(tasks2);
//mutex.Release(); // **is this correct?**
}
private async Task SaveModule(Module setting)
{
await Task.Run(() =>
{
// Invokes Calls to DS
...
});
}
//somewhere down the main thread, invoking second call to DS
//Second DS Call
private async Task SendInstrumentSettingsToDS(<param1>, <param2>)
{
//await mutex.WaitAsync();// **is this correct?**
await Task.Run(() =>
{
//TrackInstrumentInfoToDS
//mutex.Release();// **is this correct?**
});
if(param2)
{
await Task.Run(() =>
{
//TrackParam2InstrumentInfoToDS
});
}
}

Initially, i was using async await on each of these methods and each of the calls were executed asynchronously but we found out if they are out of sequence then there are room for errors.
So, i thought we should queue all these asynchronous tasks and send them in a separate thread but i want to know what options we have? I came across 'SemaphoreSlim' .
SemaphoreSlim does restrict asynchronous code to running one at a time, and is a valid form of mutual exclusion. However, since "out of sequence" calls can cause errors, then SemaphoreSlim is not an appropriate solution since it does not guarantee FIFO.
In a more general sense, no synchronization primitive guarantees FIFO because that can cause problems due to side effects like lock convoys. On the other hand, it is natural for data structures to be strictly FIFO.
So, you'll need to use your own FIFO queue, rather than having an implicit execution queue. Channels is a nice, performant, async-compatible queue, but since you're on an older version of C#/.NET, BlockingCollection<T> would work:
public sealed class ExecutionQueue
{
private readonly BlockingCollection<Func<Task>> _queue = new BlockingCollection<Func<Task>>();
public ExecutionQueue() => Completion = Task.Run(() => ProcessQueueAsync());
public Task Completion { get; }
public void Complete() => _queue.CompleteAdding();
private async Task ProcessQueueAsync()
{
foreach (var value in _queue.GetConsumingEnumerable())
await value();
}
}
The only tricky part with this setup is how to queue work. From the perspective of the code queueing the work, they want to know when the lambda is executed, not when the lambda is queued. From the perspective of the queue method (which I'm calling Run), the method needs to complete its returned task only after the lambda is executed. So, you can write the queue method something like this:
public Task Run(Func<Task> lambda)
{
var tcs = new TaskCompletionSource<object>();
_queue.Add(async () =>
{
// Execute the lambda and propagate the results to the Task returned from Run
try
{
await lambda();
tcs.TrySetResult(null);
}
catch (OperationCanceledException ex)
{
tcs.TrySetCanceled(ex.CancellationToken);
}
catch (Exception ex)
{
tcs.TrySetException(ex);
}
});
return tcs.Task;
}
This queueing method isn't as perfect as it could be. If a task completes with more than one exception (this is normal for parallel code), only the first one is retained (this is normal for async code). There's also an edge case around OperationCanceledException handling. But this code is good enough for most cases.
Now you can use it like this:
public static ExecutionQueue _queue = new ExecutionQueue();
public async Task SendModuleDataToDSAsync(Module parameters)
{
var tasks1 = new List<Task>();
var tasks2 = new List<Task>();
foreach (var setting in Module.param)
{
Task job1 = _queue.Run(() => SaveModule(setting));
tasks1.Add(job1);
Task job2 = _queue.Run(() => SaveModule(GetAdvancedData(setting)));
tasks2.Add(job2);
}
await Task.WhenAll(tasks1);
await Task.WhenAll(tasks2);
}

Here's a compact solution that has the least amount of moving parts but still guarantees FIFO ordering (unlike some of the suggested SemaphoreSlim solutions). There are two overloads for Enqueue so you can enqueue tasks with and without return values.
using System;
using System.Threading;
using System.Threading.Tasks;
public class TaskQueue
{
private Task _previousTask = Task.CompletedTask;
public Task Enqueue(Func<Task> asyncAction)
{
return Enqueue(async () => {
await asyncAction().ConfigureAwait(false);
return true;
});
}
public async Task<T> Enqueue<T>(Func<Task<T>> asyncFunction)
{
var tcs = new TaskCompletionSource(TaskCreationOptions.RunContinuationsAsynchronously);
// get predecessor and wait until it's done. Also atomically swap in our own completion task.
await Interlocked.Exchange(ref _previousTask, tcs.Task).ConfigureAwait(false);
try
{
return await asyncFunction().ConfigureAwait(false);
}
finally
{
tcs.SetResult();
}
}
}

Please keep in mind that your first solution queueing all tasks to lists doesn't ensure that the tasks are executed one after another. They're all running in parallel because they're not awaited until the next tasks is startet.
So yes you've to use a SemapohoreSlim to use async locking and await. A simple implementation might be:
private readonly SemaphoreSlim _syncRoot = new SemaphoreSlim(1);
public async Task SendModuleDataToDSAsync(Module parameters)
{
await this._syncRoot.WaitAsync();
try
{
foreach (var setting in Module.param)
{
await SaveModule(setting);
await SaveModule(GetAdvancedData(setting));
}
}
finally
{
this._syncRoot.Release();
}
}
If you can use Nito.AsyncEx the code can be simplified to:
public async Task SendModuleDataToDSAsync(Module parameters)
{
using var lockHandle = await this._syncRoot.LockAsync();
foreach (var setting in Module.param)
{
await SaveModule(setting);
await SaveModule(GetAdvancedData(setting));
}
}

One option is to queue operations that will create tasks instead of queuing already running tasks as the code in the question does.
PseudoCode without locking:
Queue<Func<Task>> tasksQueue = new Queue<Func<Task>>();
async Task RunAllTasks()
{
while (tasksQueue.Count > 0)
{
var taskCreator = tasksQueue.Dequeu(); // get creator
var task = taskCreator(); // staring one task at a time here
await task; // wait till task completes
}
}
// note that declaring createSaveModuleTask does not
// start SaveModule task - it will only happen after this func is invoked
// inside RunAllTasks
Func<Task> createSaveModuleTask = () => SaveModule(setting);
tasksQueue.Add(createSaveModuleTask);
tasksQueue.Add(() => SaveModule(GetAdvancedData(setting)));
// no DB operations started at this point
// this will start tasks from the queue one by one.
await RunAllTasks();
Using ConcurrentQueue would be likely be right thing in actual code. You also would need to know total number of expected operations to stop when all are started and awaited one after another.

Building on your comment under Alexeis answer, your approch with the SemaphoreSlim is correct.
Assumeing that the methods SendInstrumentSettingsToDS and SendModuleDataToDSAsync are members of the same class. You simplay need a instance variable for a SemaphoreSlim and then at the start of each methode that needs synchornization call await lock.WaitAsync() and call lock.Release() in the finally block.
public async Task SendModuleDataToDSAsync(Module parameters)
{
await lock.WaitAsync();
try
{
...
}
finally
{
lock.Release();
}
}
private async Task SendInstrumentSettingsToDS(<param1>, <param2>)
{
await lock.WaitAsync();
try
{
...
}
finally
{
lock.Release();
}
}
and it is importend that the call to lock.Release() is in the finally-block, so that if an exception is thrown somewhere in the code of the try-block the semaphore is released.

Is TPL Dataflow BufferBlock thread safe?

I have a fairly simple producer-consumer pattern where (simplified) I have two producers who produce output that is to be consumed by one consumer.
For this I use System.Threading.Tasks.Dataflow.BufferBlock<T>
A BufferBlock object is created. One Consumer is listening to this BufferBlock, and processes any received input.
Two 'Producerssend data to theBufferBlock` simultaneously
Simplified:
BufferBlock<int> bufferBlock = new BufferBlock<int>();
async Task Consume()
{
while(await bufferBlock.OutputAvailable())
{
int dataToProcess = await outputAvailable.ReceiveAsync();
Process(dataToProcess);
}
}
async Task Produce1()
{
IEnumerable<int> numbersToProcess = ...;
foreach (int numberToProcess in numbersToProcess)
{
await bufferBlock.SendAsync(numberToProcess);
// ignore result for this example
}
}
async Task Produce2()
{
IEnumerable<int> numbersToProcess = ...;
foreach (int numberToProcess in numbersToProcess)
{
await bufferBlock.SendAsync(numberToProcess);
// ignore result for this example
}
}
I'd like to start the Consumer first and then start the Producers as separate tasks:
var taskConsumer = Consume(); // do not await yet
var taskProduce1 = Task.Run( () => Produce1());
var taskProduce2 = Task.Run( () => Produce2());
// await until both producers are finished:
await Task.WhenAll(new Task[] {taskProduce1, taskProduce2});
bufferBlock.Complete(); // signal that no more data is expected in bufferBlock
// await for the Consumer to finish:
await taskConsumer;
At first glance, this is exactly how the producer-consumer was meant: several producers produce data while a consumer is consuming the produced data.
Yet, BufferBlock about thread safety says:
Any instance members are not guaranteed to be thread safe.
And I thought that the P in TPL meant Parallel!
Should I worry? Is my code not thread safe?
Is there a different TPL Dataflow class that I should use?

Yes, the BufferBlock class is thread safe. I can't back this claim by pointing to an official document, because the "Thread Safety" section has been removed from the documentation. But I can see in the source that the class contains a lock object for synchronizing the incoming messages:
/// <summary>Gets the lock object used to synchronize incoming requests.</summary>
private object IncomingLock { get { return _source; } }
When the Post extension method is called (source code), the explicitly implemented ITargetBlock.OfferMessage method is invoked (source code). Below is an excerpt of this method:
DataflowMessageStatus ITargetBlock<T>.OfferMessage(DataflowMessageHeader messageHeader,
T messageValue, ISourceBlock<T> source, bool consumeToAccept)
{
//...
lock (IncomingLock)
{
//...
_source.AddMessage(messageValue);
//...
}
}
It would be strange indeed if this class, or any other XxxBlock class included in the TPL Dataflow library, was not thread-safe. It would severely hamper the ease of use of this great library.

I think an ActionBlock<T> would better suit what your doing since it has a built in buffer that many producers can send data in through. The default block options process the data on single background task but you can set a new value for parallelism and bounded capacity. With ActionBlock<T> the main area of concern to ensure thread safety will be in the delegate you pass that processes each message. The operation of that function has to be independent of each message, i.e. not modifying shared state just like any Parrallel... function.
public class ProducerConsumer
{
private ActionBlock<int> Consumer { get; }
public ProducerConsumer()
{
Consumer = new ActionBlock<int>(x => Process(x));
}
public async Task Start()
{
var producer1Tasks = Producer1();
var producer2Tasks = Producer2();
await Task.WhenAll(producer1Tasks.Concat(producer2Tasks));
Consumer.Complete();
await Consumer.Completion;
}
private void Process(int data)
{
// process
}
private IEnumerable<Task> Producer1() => Enumerable.Range(0, 100).Select(x => Consumer.SendAsync(x));
private IEnumerable<Task> Producer2() => Enumerable.Range(0, 100).Select(x => Consumer.SendAsync(x));
}

How to track if an async/awaitable task is running

I'm trying to transition from the Event-based Asynchronous Pattern where I tracked running methods using unique id's and the asynoperationmanager. As this has now been dropped from Windows 8 Apps I'm trying to get a similar effect with Async/Await but can't quite figure out how.
What I'm trying to achieve is something like
private async Task updateSomething()
{
if(***the method is already running***)
{
runagain = true;
}
else
{
await someMethod();
if (runagain)
{
run the method again
}
}
}
The part I'm struggling with is finding out if the method is running. I've tried creating a Task and looking at the status of both that and the .status of the async method but they don't appear to be the correct place to look.
Thanks
UPDATE: This is the current code I use in .net 4 to achieve the same result. _updateMetaDataAsync is a class based on the Event-Based Asynchronous Pattern.
private void updateMetaData()
{
if (_updateMetaDataAsync.IsTaskRunning(_updateMetaDataGuid_CheckAllFiles))
{
_updateMetaDataGuid_CheckAllFiles_Again = true;
}
else
{
_updateMetaDataGuid_CheckAllFiles_Again = false;
_updateMetaDataAsync.UpdateMetaDataAsync(_updateMetaDataGuid_CheckAllFiles);
}
}
private void updateMetaDataCompleted(object sender, UpdateMetaDataCompletedEventArgs e)
{
if (_updateMetaDataGuid_CheckAllFiles_Again)
{
updateMetaData();
}
}

async/await itself is intended to be used to create sequential operations executed asynchronously from the UI thread. You can get it to do parallel operations, but generally the operations "join" back to the UI thread with some sort of result. (there's also the possibility of doing "fire-and-forget" types of asynchronous operations with await but it's not recommended). i.e. there's nothing inherent to async/await to support progress reporting.
You can get progress out of code using async/await; but you need to use new progress interfaces like IProgress<T>. For more info on progress reporting with async/await, see http://blogs.msdn.com/b/dotnet/archive/2012/06/06/async-in-4-5-enabling-progress-and-cancellation-in-async-apis.aspx. Migrating to this should just be a matter of calling an IProgress delegate instead of a Progress event.

If you're using a Task you've created, you can check the Task's Status property (or just see Task.IsCompleted if completion is the only state you are interested in).
That being said, await will not "return" until the operation either completes, raises an exception, or cancels. You can basically safely assume that, if you're still waiting on the "await", your task hasn't completed.

SemaphoreSlim queueToAccessQueue = new SemaphoreSlim(1);
object queueLock = new object();
long queuedRequests = 0;
Task _loadingTask;
public void RetrieveItems() {
lock (queueLock) {
queuedRequests++;
if (queuedRequests == 1) { // 1 is the minimum size of the queue before another instance is queued
_loadingTask = _loadingTask?.ContinueWith(async () => {
RunTheMethodAgain();
await queueToAccessQueue.WaitAsync();
queuedRequests = 0; // indicates that the queue has been cleared;
queueToAccessQueue.Release()
}) ?? Task.Run(async () => {
RunTheMethodAgain();
await queueToAccessQueue.WaitAsync();
queuedRequests = 0; // indicates that the queue has been cleared;
queueToAccessQueue.Release();
});
}
}
}
public void RunTheMethodAgain() {
** run the method again **
}
The added bonus is that you can see how many items are sitting in the queue!