Every time you hear about Kotlin Coroutines, you probably think about an easy, concise, and performant solution for handling asynchronous tasks like, for example, network requests. But is that their only purpose? Let's consider the usages of Kotlin Coroutines beyond concurrency.
Kotlin Coroutines Primitives
Let's start by understanding, how Coroutines underlying mechanism works. If we take a look at Kotlin Coroutines Primitives, it's only about a few classes and functions:
Continuation
CoroutineContext
suspendCoroutine
createCoroutine
startCoroutine
That's all that we have in our kotlin-stdlib
. But what are they used for? Let's dive deeper into how Kotlin Coroutines are designed to work.
Continuation
Continuation is just an interface with two members: context
and resumeWith
:
public interface Continuation<in T> {
public val context: CoroutineContext
public fun resumeWith(result: Result<T>)
}
What does it do and what its purpose? Continuation
– is literally Coroutine in primary. It's like a buffed callback with ability to propagate additional information and provide useful result of execution to coroutine.
We haven't talked about CoroutineContext
yet, let's consider only resumeWith
for now.
resumeWith
Like any other callback, this is a function that is called when coroutine finishes its work. It uses kotlin.Result
to propagate any exceptions that occur inside coroutine in a safe way.
So, we can literally create our concurrency logic using Continuation
in the next way:
suspend fun executeNetworkRequest(): String =
suspendCoroutine { continuation ->
thread {
continuation.resumeWith(someBlockingRequest())
}
}
suspendCoroutine
– is a bridge between kotlin coroutines code and non-coroutine-based code.
Or use existing asynchronous (pseudo-code):
suspend fun executeNetworkRequest(): String =
suspendCoroutine { continuation ->
apiService.getSomething()
// onSuccess & onFailure is a callback
.onSuccess(continuation::resume)
.onFailure(continuation::resumeWithException)
.executeAsync()
}
Continuation<in T>.resume(..)
is the extension to avoid passingkotlin.Result
every time.
So, we can not only implement our concurrency logic but use existing and make it work with Kotlin Coroutines.
startCoroutine
Also, we can start suspend functions from non-suspend contexts using startCoroutine
. In Kotlin it's always used in the end if your main
function is suspend
.
kotlinx.coroutines
also uses it to run coroutines, but the mechanism there is much harder, of course.
import kotlin.coroutines.*
fun main() {
val operation: suspend () -> Unit = ::a
operation.startCoroutine(
object : Continuation<Unit> {
// we will talk about it lower
override val coroutineContext = EmptyCoroutineContext
// called when coroutine finished its work
override fun resumeWith(result: Result<Unit>) {
println(
if(result.isSuccess)
"Successfully done"
else "Error happenned: ${result.exceptionOrNull()}"
)
}
}
)
}
suspend fun a() {...}
But, of course, you can't just call suspend functions from
kotlinx.coroutines
when executing coroutines in such way.
CoroutineContext
Now we came to another member of Continuation
– CoroutineContext
. What is it for?
In programming, we often handle multiple tasks at once, and managing them efficiently can be challenging. Kotlin's CoroutineContext
helps address this challenge. It's a provider that propagates needed data to the coroutine. In the real world, it's usually about passing parameters across complex chain of coroutines.
To be more clear, CoroutineContext in
kotlinx.coroutines
stands for structured concurrency.
Simple example
Let's create from our previous example for startCoroutine
code with the ability to retrieve values from CoroutineContext
:
import kotlin.coroutines.*
// define our container for data we need inside coroutine
// it should always inherit 'CoroutineContext.Element'
data class ExecutionContext(val someInt: Int) : CoroutineContext.Element {
override val key = EXECUTION_CONTEXT_KEY
}
// define type-safe key using which we will get our value
val EXECUTION_CONTEXT_KEY = object : CoroutineContext.Key<ExecutionContext> {}
// define coroutine context that we will pass into Continuation
private val myCoroutineContext = object : CoroutineContext {
private val values = mapOf<CoroutineContext.Key<*>, CoroutineContext.Element>(
EXECUTION_CONTEXT_KEY to ExecutionContext(10000)
)
override operator fun <E : CoroutineContext.Element> get(key: CoroutineContext.Key<E>): E? {
return values[key] as? E
}
// .. we omit other functions for simplicity
}
suspend fun a() {
// here we retrieve value from coroutine context
// coroutineContext is compiler intrinsic, can be called
// only from suspend world
val executionContext = coroutineContext[EXECUTION_CONTEXT_KEY]!!
println(executionContext.someInt!!)
}
fun main() {
val operation: suspend () -> Unit = ::a
operation.startCoroutine(
object : Continuation<Unit> {
override val context: CoroutineContext = myCoroutineContext
override fun resumeWith(result: Result<Unit>) {
println(
if(result.isSuccess)
"Successfully done"
else "Error happenned: ${result.exceptionOrNull()}"
)
}
}
)
}
CoroutineContext.Element
– is the abstract that is used for storing elements insideCoroutineContext
CoroutineContext.Key
– is the identifier ofCoroutineContext.Element
.
You can play around with this code here.
Real-project example
Let's imagine that we have our API service. Usually, we need to have some layer of authorization, so let's consider next example (as for such, I took gRPC):
// let's define an element that will persist in `CoroutineContext`
data class AuthorizationContext(
val accessHash: String?,
val provider: AuthorizationProvider,
) : CoroutineContext.Element {
companion object Key : CoroutineContext.Key<AuthorizationContext>
override val key: CoroutineContext.Key<*> = Key
}
// now we define our interceptor
class AuthorizationInterceptor(
private val authorizationProvider: AuthorizationProvider,
) : CoroutineContextServerInterceptor() {
companion object {
private val ACCESS_TOKEN_METADATA_KEY: Metadata.Key<String> =
Metadata.Key.of("access-token", Metadata.ASCII_STRING_MARSHALLER)
}
override fun coroutineContext(call: ServerCall<*, *>, headers: Metadata): CoroutineContext {
return AuthorizationContext(
accessHash = headers.get(ACCESS_TOKEN_METADATA_KEY),
provider = authorizationProvider,
)
}
}
CoroutineContext
in kotlinx.coroutines
is literally just a Map<K : CoroutineContext.Key, V : CoroutineContext.Element>
(to be more accurate, it's ConcurrentHashMap on JVM, for example), same as it was in our example above. But, if we talk about kotlinx.coroutines
, it's propagated to all children coroutines within the desired coroutine (we didn't have such a mechanism).
So, now we can get it in children coroutines:
suspend inline fun provideAuthorization(block: (UserId) -> Unit) {
val authContext = coroutineContext[AuthorizationContext]
authContext.accessHash ?: throw StatusException(Status.UNAUTHORIZED)
val userId = authContext.provider.provide(authContext.accessHash)
return block(userId)
}
Interesting fact: coroutineContext is the only property in Kotlin that has
suspend
modifier. 👀
For gRPC, we also need to register our Interceptor and write our RPCs. But the idea of this solution for gRPC is simple – decouple logic and simplify developer experience.
For Java, gRPC uses ThreadLocal, so we can also consider
CoroutineContext
as an alternative toThreadLocal
. We cannot useThreadLocal
within coroutines, because usually coroutine is not linked to a specific thread (especially, when we talk aboutwithContext
). Coroutines are more likely to be resumed on another thread (in addition, different coroutines can run on a single thread).
But, doesn't it mean that the only reason why coroutines exist – is concurrency? Let me explain.
Sequence
One of the most common-place examples is the – kotlin.sequences.Sequence<T>
. In brief, it's a lazy collection that iterates only when you start consuming elements. You can read about them more here.
If you ever looked at SequenceScope
sources, it uses suspend functions under the hood:
@RestrictSuspension
public abstract class SequenceScope<in T> internal constructor() {
/**
* Yields a value to the [Iterator] being built and suspends
* until the next value is requested.
*/
public abstract suspend fun yield(value: T)
// ... other
}
@RestrictSuspension
disallows consumers from calling non-members suspend functions.
So, the idea is elements are consumed lazily. You can use them as regular collections and take advantage of lazy iteration.
But how does it work under the hood? Let's take a look at implementation sources:
private typealias State = Int
private const val State_NotReady: State = 0
private const val State_ManyNotReady: State = 1
private const val State_ManyReady: State = 2
private const val State_Ready: State = 3
private const val State_Done: State = 4
private const val State_Failed: State = 5
private class SequenceBuilderIterator<T> : SequenceScope<T>(), Iterator<T>, Continuation<Unit> {
private var state = State_NotReady
private var nextValue: T? = null
private var nextIterator: Iterator<T>? = null
var nextStep: Continuation<Unit>? = null
override fun hasNext(): Boolean {
while (true) {
when (state) {
State_NotReady -> {}
State_ManyNotReady ->
if (nextIterator!!.hasNext()) {
state = State_ManyReady
return true
} else {
nextIterator = null
}
State_Done -> return false
State_Ready, State_ManyReady -> return true
else -> throw exceptionalState()
}
state = State_Failed
val step = nextStep!!
nextStep = null
step.resume(Unit) // IMPORTANT: it starts executing next yield
}
}
override fun next(): T {
when (state) {
State_NotReady, State_ManyNotReady -> return nextNotReady()
State_ManyReady -> {
state = State_ManyNotReady
return nextIterator!!.next()
}
State_Ready -> {
state = State_NotReady
@Suppress("UNCHECKED_CAST")
val result = nextValue as T
nextValue = null
return result
}
else -> throw exceptionalState()
}
}
private fun nextNotReady(): T {
if (!hasNext()) throw NoSuchElementException() else return next()
}
private fun exceptionalState(): Throwable = when (state) {
State_Done -> NoSuchElementException()
State_Failed -> IllegalStateException("Iterator has failed.")
else -> IllegalStateException("Unexpected state of the iterator: $state")
}
override suspend fun yield(value: T) {
nextValue = value
state = State_Ready
return suspendCoroutineUninterceptedOrReturn { c ->
nextStep = c
COROUTINE_SUSPENDED
}
}
override fun resumeWith(result: Result<Unit>) {
result.getOrThrow() // just rethrow exception if it is there
state = State_Done
}
override val context: CoroutineContext
get() = EmptyCoroutineContext
}
COROUTINE_SUSPENDED
is a special constant used internally by the Kotlin compiler to manage coroutine suspension and resumption. It's not something developers typically interact with directly, but rather, it serves as an internal signal within the coroutine machinery.
Looks a bit hard to read, isn't it? Let's go step by step:
- First, we start with states. We have next states, let's talk about them in brief:
- State_NotReady: The iterator is not ready to provide an item right now. It might be waiting for an operation or further processing to make an item available.
- State_ManyNotReady: The iterator is prepared to provide multiple items, but they aren't ready immediately. It's waiting for a signal that items are ready for consumption (basically, waits for terminal operator).
- State_ManyReady: The iterator is ready to provide multiple items right now. It can immediately give the next item from the sequence.
- State_Ready: The iterator has a single item ready to be provided. It's set to immediately give the item when asked.
- State_Done: The iterator has no more items to provide. It has completed its job of producing elements from the sequence. We reach this state when we leave
SequenceBuilder
- State_Failed: Something unexpected happened, and the iterator encountered an issue. Usually, this should not happen.
hasNext
based on state, returns a value or set of values when it's ready to consume. Moreover, it starts execution of sequence on every iteration insidewhile
. So, if there'sState_NotReady
, it makes it ready by executing next yields.- The
next
function retrieves the next item from the iterator based on its current state (same tohasNext
). If next was called withouthasNext
, you can reachnextNotReady()
. In other situations, it will simply return value. yield
function just changes states of sequence iterator implementation. When new elements added it changes toState_Ready
. UsingsuspendCoroutineUninterceptedOrReturn
suspends the coroutine (execution) and resumes it later. It will be started when previous coroutine (suspend point) will be finished.
To finish my explanation, let's just end with how could we make the same functionality just by using callbacks:
val sequence = sequence {
yield(1) {
yield(2) {
yield(3) { /* ... */ }
}
}
}But, it looks a bit hard to read, isn't it? That's why coroutines are useful in this particular situation.
In the end, it doesn't look that complex, am I right?
DeepRecursiveScope
Now, let's discuss another case for Kotlin Coroutines – DeepRecursiveScope
. As you probably know, usually when specific function call itself, we have a probability of running into StackOverflowError
as every call contributes it to our stack.
For the same purpose, for example, also exists
tailrec
language construction. The difference is thattailrec
cannot have branching (conditional checks) with calls to other functions.You can read about that more here.
So, DeepRecursiveScope
doesn't rely on traditional stack flow, but uses all the features Coroutines offer.
We won't stop on exact implementation details of DeepRecursiveScope
(you can take a look at it here) as it has the same idea to Sequence
with additional behaviour to support mechanisms that is provided, but let's discuss how Kotlin Coroutines solves this particular problem.
Coroutines internally
How exactly it solves the problem? As I mentioned before, Coroutines are inspired by CPS (Continuation Passing Style), but it's not exactly what Kotlin Compiler does to handle coroutines that efficiently.
Kotlin Compiler uses a combination of optimizations to manage coroutines stack and execution efficiently. Let's check what exactly it does:
- Compiler transformations: Kotlin Compiler generates State Machine, same to what we saw in the implementation details of Sequences. It doesn't get rid of all stack calls but reduces it enough to not run into
StackOverflowError
. - Heap-Allocation of Continuations: In a traditional callback chain, each function call pushes data onto the call stack. If the chain is deep, this can consume a lot of stack space. In the coroutine approach, when a coroutine is suspended, its continuation is stored on the heap as an object. This continuation object holds the necessary information (stack, dispatcher, etc) to resume the coroutine's execution. This heap storage allows for a much greater capacity to handle deep call chains without risking stack overflow.
The exact mechanism of coroutines is next:
- Serialization: Suspended coroutine's stack state is saved in a heap-allocated continuation object.
- Resumption: When ready to resume, the framework sets up a native stack to mimic captured state.
- Memory Copy: Serialized stack state is copied from the continuation object to the native stack.
- Context Configuration: Execution context is configured to match original state.
- Program Counter: Program counter is set to saved value for correct instruction.
- Invocation: Continuation code is invoked using CPS, resuming execution.
Stack restoring also helps us with resuming on different threads as they don't know anything about our coroutine's stack.
So, from now we can understand how coroutines internally work. Let's move on to other examples where Kotlin coroutines are used beyond concurrency.
Jetpack Compose
If you ever worked with Compose and, for example, handling pointer events, you have probably mentioned that there're some hacks used from Coroutines for listening to updates:
@RestrictsSuspension // <---
@JvmDefaultWithCompatibility
interface AwaitPointerEventScope : Density {
// ...
suspend fun awaitPointerEvent(
pass: PointerEventPass = PointerEventPass.Main
): PointerEvent
suspend fun <T> withTimeoutOrNull(
timeMillis: Long,
block: suspend AwaitPointerEventScope.() -> T
): T? = block()
suspend fun <T> withTimeout(
timeMillis: Long,
block: suspend AwaitPointerEventScope.() -> T
): T = block()
// ...
}
So, as you see, scope that is used to handle pointer events is marked with @RestrictsSuspension
. If we come to the documentation provided, we'll see next:
This is a restricted suspension scope. Code in this scope is
always called un-dispatched and may only suspend for calls
to [awaitPointerEvent]. These functions resume synchronously and the caller may mutate the result
**before** the next await call to affect the next stage of the input processing pipeline.
awaitPointerEvent
is handled using kotlin primitives, without kotlinx.coroutines
. As in such situation we don't need any kotlinx.coroutines
logic (it's fairly just a callback that is called from Main-looper thread after user's action).
Android SDK
As we can use suspend
functions in all situations where we do need callback, there're also other useful cases where we can apply such logic. For example, while requesting permissions:
val result = Warden
.with(this)
.requestPermission(Manifest.permission.CALL_PHONE)
when (result) {
is PermissionState.Denied -> dialNumber(phoneNumber)
PermissionState.Granted -> startCall(phoneNumber)
}
In example, we're using Warden library.
Conclusion
In conclusion, this article has explored various facets of Kotlin Coroutines, emphasizing their versatility beyond traditional concurrency tasks. We've delved into the inner workings of coroutines primitives, discussed their use in Sequences and complex problem-solving scenarios like deep recursion, and examined real-world examples that showcase their broad applicability. The title, "Coroutines are not just about concurrency," aptly reflects the diverse capabilities that Kotlin coroutines offer in modern software development.
Feel free to casually drop your expertise in the water cooler chat!