- Asynchronous Programming
- Asynchrony is viral
- Async void
- Prefer Task.FromResult over Task.Run for pre-computed or trivially computed data
- Avoid using Task.Run for long running work that blocks the thread
- Avoid using Task.Result and Task.Wait
- Prefer await over ContinueWith
- Always create TaskCompletionSource<T> with TaskCreationOptions.RunContinuationsAsynchronously
- Always dispose CancellationTokenSource(s) used for timeouts
- Always flow CancellationToken(s) to APIs that take a CancellationToken
- Cancelling uncancellable operations
- Always call FlushAsync on StreamWriter(s) or Stream(s) before calling Dispose
- Prefer async/await over directly returning Task
- ConfigureAwait
- Scenarios
Asynchronous programming has been around for several years on the .NET platform but has historically been very difficult to do well. Since the introduction of async/await in C# 5 asynchronous programming has become mainstream. Modern frameworks (like ASP.NET Core) are fully asynchronous and it's very hard to avoid the async keyword when writing web services. As a result, there's been lots of confusion on the best practices for async and how to use it properly. This section will try to lay out some guidance with examples of bad and good patterns of how to write asynchronous code.
Once you go async, all of your callers SHOULD be async, since efforts to be async amount to nothing unless the entire callstack is async. In many cases, being partially async can be worse than being entirely synchronous. Therefore it is best to go all in, and make everything async at once.
❌ BAD This example uses the Task.Result
and as a result blocks the current thread to wait for the result. This is an example of sync over async.
public int DoSomethingAsync()
{
var result = CallDependencyAsync().Result;
return result + 1;
}
✅ GOOD This example uses the await keyword to get the result from CallDependencyAsync
.
public async Task<int> DoSomethingAsync()
{
var result = await CallDependencyAsync();
return result + 1;
}
Use of async void in ASP.NET Core applications is ALWAYS bad. Avoid it, never do it. Typically, it's used when developers are trying to implement fire and forget patterns triggered by a controller action. Async void methods will crash the process if an exception is thrown. We'll look at more of the patterns that cause developers to do this in ASP.NET Core applications but here's a simple example:
❌ BAD Async void methods can't be tracked and therefore unhandled exceptions can result in application crashes.
public class MyController : Controller
{
[HttpPost("/start")]
public IActionResult Post()
{
BackgroundOperationAsync();
return Accepted();
}
public async void BackgroundOperationAsync()
{
var result = await CallDependencyAsync();
DoSomething(result);
}
}
✅ GOOD Task
-returning methods are better since unhandled exceptions trigger the TaskScheduler.UnobservedTaskException
.
public class MyController : Controller
{
[HttpPost("/start")]
public IActionResult Post()
{
Task.Run(BackgroundOperationAsync);
return Accepted();
}
public async Task BackgroundOperationAsync()
{
var result = await CallDependencyAsync();
DoSomething(result);
}
}
For pre-computed results, there's no need to call Task.Run
, that will end up queuing a work item to the thread pool that will immediately complete with the pre-computed value. Instead, use Task.FromResult
, to create a task wrapping already computed data.
❌ BAD This example wastes a thread-pool thread to return a trivially computed value.
public class MyLibrary
{
public Task<int> AddAsync(int a, int b)
{
return Task.Run(() => a + b);
}
}
✅ GOOD This example uses Task.FromResult
to return the trivially computed value. It does not use any extra threads as a result.
public class MyLibrary
{
public Task<int> AddAsync(int a, int b)
{
return Task.FromResult(a + b);
}
}
💡NOTE: Using Task.FromResult
will result in a Task
allocation. Using ValueTask<T>
can completely remove that allocation.
✅ GOOD This example uses a ValueTask<int>
to return the trivially computed value. It does not use any extra threads as a result. It also does not allocate an object on the managed heap.
public class MyLibrary
{
public ValueTask<int> AddAsync(int a, int b)
{
return new ValueTask<int>(a + b);
}
}
Long running work in this context refers to a thread that's running for the lifetime of the application doing background work (like processing queue items, or sleeping and waking up to process some data). Task.Run
will queue a work item to the thread pool. The assumption is that that work will finish quickly (or quickly enough to allow reusing that thread within some reasonable timeframe). Stealing a thread-pool thread for long-running work is bad since it takes that thread away from other work that could be done (timer callbacks, task continuations etc). Instead, spawn a new thread manually to do long running blocking work.
💡 NOTE: The thread pool grows if you block threads but it's bad practice to do so.
💡 NOTE:Task.Factory.StartNew
has an option TaskCreationOptions.LongRunning
that under the covers creates a new thread and returns a Task that represents the execution. Using this properly requires several non-obvious parameters to be passed in to get the right behavior on all platforms.
💡 NOTE: Don't use TaskCreationOptions.LongRunning
with async code as this will create a new thread which will be destroyed after first await
.
❌ BAD This example steals a thread-pool thread forever, to execute queued work on a BlockingCollection<T>
.
public class QueueProcessor
{
private readonly BlockingCollection<Message> _messageQueue = new BlockingCollection<Message>();
public void StartProcessing()
{
Task.Run(ProcessQueue);
}
public void Enqueue(Message message)
{
_messageQueue.Add(message);
}
private void ProcessQueue()
{
foreach (var item in _messageQueue.GetConsumingEnumerable())
{
ProcessItem(item);
}
}
private void ProcessItem(Message message) { }
}
✅ GOOD This example uses a dedicated thread to process the message queue instead of a thread-pool thread.
public class QueueProcessor
{
private readonly BlockingCollection<Message> _messageQueue = new BlockingCollection<Message>();
public void StartProcessing()
{
var thread = new Thread(ProcessQueue)
{
// This is important as it allows the process to exit while this thread is running
IsBackground = true
};
thread.Start();
}
public void Enqueue(Message message)
{
_messageQueue.Add(message);
}
private void ProcessQueue()
{
foreach (var item in _messageQueue.GetConsumingEnumerable())
{
ProcessItem(item);
}
}
private void ProcessItem(Message message) { }
}
There are very few ways to use Task.Result
and Task.Wait
correctly so the general advice is to completely avoid using them in your code.
Using Task.Result
or Task.Wait
to block wait on an asynchronous operation to complete is MUCH worse than calling a truly synchronous API to block. This phenomenon is dubbed "Sync over async". Here is what happens at a very high level:
- An asynchronous operation is kicked off.
- The calling thread is blocked waiting for that operation to complete.
- When the asynchronous operation completes, it unblocks the code waiting on that operation. This takes place on another thread.
The result is that we need to use 2 threads instead of 1 to complete synchronous operations. This usually leads to thread-pool starvation and results in service outages.
The SynchronizationContext
is an abstraction that gives application models a chance to control where asynchronous continuations run. ASP.NET (non-core), WPF and Windows Forms each have an implementation that will result in a deadlock if Task.Wait or Task.Result is used on the main thread. This behavior has led to a bunch of "clever" code snippets that show the "right" way to block waiting for a Task. The truth is, there's no good way to block waiting for a Task to complete.
💡NOTE: ASP.NET Core does not have a SynchronizationContext
and is not prone to the deadlock problem.
❌ BAD The below are all examples that are, in one way or another, trying to avoid the deadlock situation but still succumb to "sync over async" problems.
public string DoOperationBlocking()
{
// Bad - Blocking the thread that enters.
// DoAsyncOperation will be scheduled on the default task scheduler, and remove the risk of deadlocking.
// In the case of an exception, this method will throw an AggregateException wrapping the original exception.
return Task.Run(() => DoAsyncOperation()).Result;
}
public string DoOperationBlocking2()
{
// Bad - Blocking the thread that enters.
// DoAsyncOperation will be scheduled on the default task scheduler, and remove the risk of deadlocking.
return Task.Run(() => DoAsyncOperation()).GetAwaiter().GetResult();
}
public string DoOperationBlocking3()
{
// Bad - Blocking the thread that enters, and blocking the theadpool thread inside.
// In the case of an exception, this method will throw an AggregateException containing another AggregateException, containing the origonal exception.
return Task.Run(() => DoAsyncOperation().Result).Result;
}
public string DoOperationBlocking4()
{
// Bad - Blocking the thread that enters, and blocking the theadpool thread inside.
return Task.Run(() => DoAsyncOperation().GetAwaiter().GetResult()).GetAwaiter().GetResult();
}
public string DoOperationBlocking5()
{
// Bad - Blocking the thread that enters.
// Bad - No effort has been made to prevent a present SynchonizationContext from becoming deadlocked.
// In the case of an exception, this method will throw an AggregateException wrapping the original exception.
return DoAsyncOperation().Result;
}
public string DoOperationBlocking6()
{
// Bad - Blocking the thread that enters.
// Bad - No effort has been made to prevent a present SynchonizationContext from becoming deadlocked.
return DoAsyncOperation().GetAwaiter().GetResult();
}
public string DoOperationBlocking7()
{
// Bad - Blocking the thread that enters.
// Bad - No effort has been made to prevent a present SynchonizationContext from becoming deadlocked.
var task = DoAsyncOperation();
task.Wait();
return task.GetAwaiter().GetResult();
}
Task
existed before the async/await keywords were introduced and as such provided ways to execute continuations without relying on the language. Although these methods are still valid to use, we generally recommend that you prefer async
/await
to using ContinueWith
. ContinueWith
also does not capture the SynchronizationContext
and as a result is actually semantically different to async
/await
.
❌ BAD The example uses ContinueWith
instead of async
public Task<int> DoSomethingAsync()
{
return CallDependencyAsync().ContinueWith(task =>
{
return task.Result + 1;
});
}
✅ GOOD This example uses the await
keyword to get the result from CallDependencyAsync
.
public async Task<int> DoSomethingAsync()
{
var result = await CallDependencyAsync();
return result + 1;
}
TaskCompletionSource<T>
is an important building block for libraries trying to adapt things that are not inherently awaitable to be awaitable via a Task
. It is also commonly used to build higher-level operations (such as batching and other combinators) on top of existing asynchronous APIs. By default, Task
continuations will run inline on the same thread that calls Try/Set(Result/Exception/Canceled). As a library author, this means having to understand that calling code can resume directly on your thread. This is extremely dangerous and can result in deadlocks, thread-pool starvation, corruption of state (if code runs unexpectedly) and more.
Always use TaskCreationOptions.RunContinuationsAsynchronously
when creating the TaskCompletionSource<T>
. This will dispatch the continuation onto the thread pool instead of executing it inline.
❌ BAD This example does not use TaskCreationOptions.RunContinuationsAsynchronously
when creating the TaskCompletionSource<T>
.
public Task<int> DoSomethingAsync()
{
var tcs = new TaskCompletionSource<int>();
var operation = new LegacyAsyncOperation();
operation.Completed += result =>
{
// Code awaiting on this task will resume on this thread!
tcs.SetResult(result);
};
return tcs.Task;
}
✅ GOOD This example uses TaskCreationOptions.RunContinuationsAsynchronously
when creating the TaskCompletionSource<T>
.
public Task<int> DoSomethingAsync()
{
var tcs = new TaskCompletionSource<int>(TaskCreationOptions.RunContinuationsAsynchronously);
var operation = new LegacyAsyncOperation();
operation.Completed += result =>
{
// Code awaiting on this task will resume on a different thread-pool thread
tcs.SetResult(result);
};
return tcs.Task;
}
💡NOTE: There are 2 enums that look alike. TaskCreationOptions.RunContinuationsAsynchronously
and TaskContinuationOptions.RunContinuationsAsynchronously
. Be careful not to confuse their usage.
CancellationTokenSource
objects that are used for timeouts (are created with timers or uses the CancelAfter
method), can put pressure on the timer queue if not disposed.
❌ BAD This example does not dispose the CancellationTokenSource
and as a result the timer stays in the queue for 10 seconds after each request is made.
public async Task<Stream> HttpClientAsyncWithCancellationBad()
{
var cts = new CancellationTokenSource(TimeSpan.FromSeconds(10));
using (var client = _httpClientFactory.CreateClient())
{
var response = await client.GetAsync("http://backend/api/1", cts.Token);
return await response.Content.ReadAsStreamAsync();
}
}
✅ GOOD This example disposes the CancellationTokenSource
and properly removes the timer from the queue.
public async Task<Stream> HttpClientAsyncWithCancellationGood()
{
using (var cts = new CancellationTokenSource(TimeSpan.FromSeconds(10)))
{
using (var client = _httpClientFactory.CreateClient())
{
var response = await client.GetAsync("http://backend/api/1", cts.Token);
return await response.Content.ReadAsStreamAsync();
}
}
}
Cancellation is cooperative in .NET. Everything in the call-chain has to be explicitly passed the CancellationToken
in order for it to work well. This means you need to explicitly pass the token into other APIs that take a token if you want cancellation to be most effective.
❌ BAD This example neglects to pass the CancellationToken
to Stream.ReadAsync
making the operation effectively not cancellable.
public async Task<string> DoAsyncThing(CancellationToken cancellationToken = default)
{
byte[] buffer = new byte[1024];
// We forgot to pass flow cancellationToken to ReadAsync
int read = await _stream.ReadAsync(buffer, 0, buffer.Length);
return Encoding.UTF8.GetString(buffer, 0, read);
}
✅ GOOD This example passes the CancellationToken
into Stream.ReadAsync
.
public async Task<string> DoAsyncThing(CancellationToken cancellationToken = default)
{
byte[] buffer = new byte[1024];
// This properly flows cancellationToken to ReadAsync
int read = await _stream.ReadAsync(buffer, 0, buffer.Length, cancellationToken);
return Encoding.UTF8.GetString(buffer, 0, read);
}
One of the coding patterns that appears when doing asynchronous programming is cancelling an uncancellable operation. This usually means creating another task that completes when a timeout or CancellationToken
fires, and then using Task.WhenAny
to detect a complete or cancelled operation.
❌ BAD This example uses Task.Delay(-1, token)
to create a Task
that completes when the CancellationToken
fires, but if it doesn't fire, there's no way to dispose the CancellationTokenRegistration
. This can lead to a memory leak.
public static async Task<T> WithCancellation<T>(this Task<T> task, CancellationToken cancellationToken)
{
// There's no way to dispose the registration
var delayTask = Task.Delay(-1, cancellationToken);
var resultTask = await Task.WhenAny(task, delayTask);
if (resultTask == delayTask)
{
// Operation cancelled
throw new OperationCanceledException();
}
return await task;
}
✅ GOOD This example disposes the CancellationTokenRegistration
when one of the Task(s)
complete.
public static async Task<T> WithCancellation<T>(this Task<T> task, CancellationToken cancellationToken)
{
var tcs = new TaskCompletionSource<object>(TaskCreationOptions.RunContinuationsAsynchronously);
// This disposes the registration as soon as one of the tasks trigger
using (cancellationToken.Register(state =>
{
((TaskCompletionSource<object>)state).TrySetResult(null);
},
tcs))
{
var resultTask = await Task.WhenAny(task, tcs.Task);
if (resultTask == tcs.Task)
{
// Operation cancelled
throw new OperationCanceledException(cancellationToken);
}
return await task;
}
}
❌ BAD This example does not cancel the timer even if the operation successfuly completes. This means you could end up with lots of timers, which can flood the timer queue.
public static async Task<T> TimeoutAfter<T>(this Task<T> task, TimeSpan timeout)
{
var delayTask = Task.Delay(timeout);
var resultTask = await Task.WhenAny(task, delayTask);
if (resultTask == delayTask)
{
// Operation cancelled
throw new OperationCanceledException();
}
return await task;
}
✅ GOOD This example cancels the timer if the operation succesfully completes.
public static async Task<T> TimeoutAfter<T>(this Task<T> task, TimeSpan timeout)
{
using (var cts = new CancellationTokenSource())
{
var delayTask = Task.Delay(timeout, cts.Token);
var resultTask = await Task.WhenAny(task, delayTask);
if (resultTask == delayTask)
{
// Operation cancelled
throw new OperationCanceledException();
}
else
{
// Cancel the timer task so that it does not fire
cts.Cancel();
}
return await task;
}
}
When writing to a Stream
or StreamWriter
even if the asynchronous overloads are used for writing, the underlying data might be buffered. When data is buffered, disposing the Stream
or StreamWriter
will synchronously write/flush, which results in blocking the thread and could lead to thread-pool starvation.
💡NOTE: This is only problematic if the underlying subsystem does IO.
❌ BAD This example ends up blocking the request by writing synchronously to the HTTP-response body.
app.Run(async context =>
{
// The implicit Dispose call will synchronously write to the response body
using (var streamWriter = new StreamWriter(context.Response.Body))
{
await streamWriter.WriteAsync("Hello World");
}
});
✅ GOOD This example asynchronously flushes any buffered data before disposing the StreamWriter
.
app.Run(async context =>
{
using (var streamWriter = new StreamWriter(context.Response.Body))
{
await streamWriter.WriteAsync("Hello World");
// Force an asynchronous flush
await streamWriter.FlushAsync();
}
});
There are benefits to using the async
/await
keyword instead of directly returning the Task
:
- Asynchronous and synchronous exceptions are normalized to always be asynchronous.
- The code is easier to modify (consider adding a
using
, for example). - Diagnostics of asynchronous methods are easier (debugging hangs etc).
- Exceptions thrown will be automatically wrapped in the returned
Task
instead of surprising the caller with an actual exception.
❌ BAD This example directly returns the Task
to the caller.
public Task<int> DoSomethingAsync()
{
return CallDependencyAsync();
}
✅ GOOD This examples uses async/await instead of directly returning the Task.
public async Task<int> DoSomethingAsync()
{
return await CallDependencyAsync();
}
💡NOTE: There are performance considerations when using an async state machine over directly returning the Task
. It's always faster to directly return the Task
since it does less work but you end up changing the behavior and potentially losing some of the benefits of the async state machine.
TBD
The above tries to distill general guidance, but doesn't do justice to the kinds of real-world situations that cause code like this to be written in the first place (bad code). This section tries to take concrete examples from real applications and turn them into something simple to help you relate these problems to existing codebases.
❌ BAD The Timer
callback is void
-returning and we have asynchronous work to execute. This example uses async void
to accomplish it and as a result can crash the process if an exception occurs.
public class Pinger
{
private readonly Timer _timer;
private readonly HttpClient _client;
public Pinger(HttpClient client)
{
_client = client;
_timer = new Timer(Heartbeat, null, 1000, 1000);
}
public async void Heartbeat(object state)
{
await _client.GetAsync("http://mybackend/api/ping");
}
}
❌ BAD This attempts to block in the Timer
callback. This may result in thread-pool starvation and is an example of sync over async
public class Pinger
{
private readonly Timer _timer;
private readonly HttpClient _client;
public Pinger(HttpClient client)
{
_client = client;
_timer = new Timer(Heartbeat, null, 1000, 1000);
}
public void Heartbeat(object state)
{
_client.GetAsync("http://mybackend/api/ping").GetAwaiter().GetResult();
}
}
✅ GOOD This example uses an async Task
-based method and discards the Task
in the Timer
callback. If this method fails, it will not crash the process. Instead, it will fire the TaskScheduler.UnobservedTaskException
event.
public class Pinger
{
private readonly Timer _timer;
private readonly HttpClient _client;
public Pinger(HttpClient client)
{
_client = client;
_timer = new Timer(Heartbeat, null, 1000, 1000);
}
public void Heartbeat(object state)
{
// Discard the result
_ = DoAsyncPing();
}
private async Task DoAsyncPing()
{
await _client.GetAsync("http://mybackend/api/ping");
}
}
Imagine a BackgroundQueue
with a FireAndForget
that takes a callback. This method will execute the callback at some time in the future.
❌ BAD This will force callers to either block in the callback or use an async void
delegate.
public class BackgroundQueue
{
public static void FireAndForget(Action action) { }
}
❌ BAD This calling code is creating an async void
method implicitly. The compiler fully supports this today.
public class Program
{
public void Main(string[] args)
{
var httpClient = new HttpClient();
BackgroundQueue.FireAndForget(async () =>
{
await httpClient.GetAsync("http://pinger/api/1");
});
Console.ReadLine();
}
}
✅ GOOD This BackgroundQueue implementation offers both sync and async
callback overloads.
public class BackgroundQueue
{
public static void FireAndForget(Action action) { }
public static void FireAndForget(Func<Task> action) { }
}
It's pretty common to cache the result of an asynchronous operation and ConcurrentDictionary
is a good data structure for doing that. GetOrAdd
is a convenience API for trying to get an item if it's already there or adding it if it isn't. The callback is synchronous so it's tempting to write code that uses Task.Result
to produce the value of an asynchronous process but that can lead to thread-pool starvation.
❌ BAD This may result in thread-pool starvation since we're blocking the request thread if the person data is not cached.
public class PersonController : Controller
{
private AppDbContext _db;
// This cache needs expiration
private static ConcurrentDictionary<int, Person> _cache = new ConcurrentDictionary<int, Person>();
public PersonController(AppDbContext db)
{
_db = db;
}
public IActionResult Get(int id)
{
var person = _cache.GetOrAdd(id, (key) => db.People.FindAsync(key).Result);
return Ok(person);
}
}
✅ GOOD This implementation won't result in thread-pool starvation since we're storing a task instead of the result itself.
ConcurrentDictionary.GetOrAdd
will potentially run the cache callback multiple times in parallel. This can result in kicking off expensive computations multiple times.
public class PersonController : Controller
{
private AppDbContext _db;
// This cache needs expiration
private static ConcurrentDictionary<int, Task<Person>> _cache = new ConcurrentDictionary<int, Task<Person>>();
public PersonController(AppDbContext db)
{
_db = db;
}
public async Task<IActionResult> Get(int id)
{
var person = await _cache.GetOrAdd(id, (key) => db.People.FindAsync(key));
return Ok(person);
}
}
✅ GOOD This implementation fixes the multiple-executing callback issue by using the async
lazy pattern.
public class PersonController : Controller
{
private AppDbContext _db;
// This cache needs expiration
private static ConcurrentDictionary<int, AsyncLazy<Person>> _cache = new ConcurrentDictionary<int, AsyncLazy<Person>>();
public PersonController(AppDbContext db)
{
_db = db;
}
public async Task<IActionResult> Get(int id)
{
var person = await _cache.GetOrAdd(id, (key) => new AsyncLazy<Person>(() => db.People.FindAsync(key))).Value;
return Ok(person);
}
private class AsyncLazy<T> : Lazy<Task<T>>
{
public AsyncLazy(Func<Task<T>> valueFactory) : base(valueFactory)
{
}
}
}
Constructors are synchronous. If you need to initialize some logic that may be asynchronous, there are a couple of patterns for dealing with this.
Here's an example of using a client API that needs to connect asynchronously before use.
public interface IRemoteConnectionFactory
{
Task<IRemoteConnection> ConnectAsync();
}
public interface IRemoteConnection
{
Task PublishAsync(string channel, string message);
Task DisposeAsync();
}
❌ BAD This example uses Task.Result
to get the connection in the constructor. This could lead to thread-pool starvation and deadlocks.
public class Service : IService
{
private readonly IRemoteConnection _connection;
public Service(IRemoteConnectionFactory connectionFactory)
{
_connection = connectionFactory.ConnectAsync().Result;
}
}
✅ GOOD This implementation uses a static factory pattern in order to allow asynchronous construction:
public class Service : IService
{
private readonly IRemoteConnection _connection;
private Service(IRemoteConnection connection)
{
_connection = connection;
}
public static async Task<Service> CreateAsync(IRemoteConnectionFactory connectionFactory)
{
return new Service(await connectionFactory.ConnectAsync());
}
}
This API runs the specified action as the impersonated Windows identity. Unfortunately there's no asynchronous version of the callback.
❌ BAD This example tries to execute the query asynchronously, and then wait for it outside of the call to RunImpersonated
. This will throw because the query might be executing outside of the impersonation context.
public async Task<IEnumerable<Product>> GetDataImpersonatedAsync(SafeAccessTokenHandle safeAccessTokenHandle)
{
Task<IEnumerable<Product>> products = null;
WindowsIdentity.RunImpersonated(
safeAccessTokenHandle,
context =>
{
products = _db.QueryAsync("SELECT Name from Products");
}};
return await products;
}
❌ BAD This example uses Task.Result
to get the connection in the constructor. This could lead to thread-pool starvation and deadlocks.
public IEnumerable<Product> GetDataImpersonatedAsync(SafeAccessTokenHandle safeAccessTokenHandle)
{
return WindowsIdentity.RunImpersonated(
safeAccessTokenHandle,
context => _db.QueryAsync("SELECT Name from Products").Result);
}
💡NOTE There's no good alternative here. This API shouldn't be used with an asynchronous callback. See https://github.com/dotnet/corefx/issues/24977