Kotlin’s function type variance is an important concept that helps developers understand how types behave when dealing with function inputs and outputs. If you’ve ever wondered why function parameters and return types follow different variance rules, this post will clear things up..! Understanding Variance in Kotlin Variance determines how subtyping relationships work in a type hierarchy....
Kotlin has a robust type system, but one of the trickiest concepts to grasp is contravariance. If you’ve ever scratched your head wondering how contravariance works and why it’s useful, you’re in the right place. This blog will break it down in simple terms with examples so you can fully understand Kotlin contravariance and use...
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In modern Android and Kotlin development, handling asynchronous data streams efficiently is crucial. Whether you’re working with API responses, user input events, or real-time updates, Kotlin Flow provides a powerful, coroutine-based solution. In this guide, we’ll explore Kotlin Flow in-depth, covering its concepts, operators, builders, real-world use cases, and best practices.
Kotlin Flow is a cold, asynchronous, and reactive stream API introduced as part of Kotlin Coroutines. It is designed to handle sequential data streams efficiently, making it a great alternative to RxJava and LiveData.
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.runBlocking
fun simpleFlow(): Flow<Int> = flow {
for (i in 1..5) {
emit(i) // Emitting values one by one
}
}
fun main() = runBlocking {
simpleFlow().collect { value -> println(value) }
}Output:
1
2
3
4
5Use Flow when dealing with data streams that require coroutine support and backpressure handling.
flow {} – Custom Flow Creationval customFlow: Flow<Int> = flow {
for (i in 1..3) {
emit(i) // Emit values
}
}flowOf() – Flow from Fixed Valuesval numbersFlow = flowOf(1, 2, 3, 4, 5)asFlow() – Convert Collections to Flowval listFlow = listOf(1, 2, 3).asFlow()map {} – Transform Each ElementsimpleFlow().map { it * 2 }.collect { println(it) }Output: 2, 4, 6, 8, 10
filter {} – Filter ElementssimpleFlow().filter { it % 2 == 0 }.collect { println(it) }Output: 2, 4
collectLatest {} – Cancel Previous CollectionsimpleFlow().collectLatest { value ->
println("Processing $value")
}flatMapConcat {} – Sequential Mappingval flow1 = flowOf(1, 2, 3)
flow1.flatMapConcat { value -> flowOf(value * 10) }
.collect { println(it) }Output: 10, 20, 30
val job = launch {
simpleFlow().collect { println(it) }
}
delay(2000)
job.cancel() // Cancels the Flowflow {
emit(1)
throw RuntimeException("Error!")
}.catch { e -> println("Caught: ${e.message}") }
.collect { println(it) }StateFlow is similar to LiveData and is used to store a single state that updates over time.
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
fun main() = runBlocking {
val stateFlow = MutableStateFlow(0)
val job = launch {
stateFlow.collect { value ->
println("Collector received: $value")
}
}
delay(500)
stateFlow.value = 1
delay(500)
stateFlow.value = 2
delay(500)
job.cancel()
}
//Output
Collector received: 0
Collector received: 1
Collector received: 2StateFlow always emits the latest value to collectors. It behaves like LiveData, and collectors receive the current state immediately upon subscription.
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
fun main() = runBlocking {
// Create a MutableSharedFlow with a buffer capacity of 2
val sharedFlow = MutableSharedFlow<Int>(
replay = 0,
extraBufferCapacity = 2
)
val job1 = launch {
sharedFlow.collect { value ->
println("Collector 1 received: $value")
}
}
val job2 = launch {
sharedFlow.collect { value ->
println("Collector 2 received: $value")
}
}
// Delay to ensure collectors are active before emitting
delay(100)
sharedFlow.emit(10)
sharedFlow.emit(20)
delay(500)
job1.cancel()
job2.cancel()
}
// Output
Collector 1 received: 10
Collector 2 received: 10
Collector 1 received: 20
Collector 2 received: 20By default, MutableSharedFlow has no buffer and replay = 0, meaning it won’t emit any value unless a collector is ready at the moment of emission.
extraBufferCapacity = 2, allowing SharedFlow to buffer a couple of values while the collectors start.delay(100) before emitting, ensuring both collectors are already collecting.This way, both collectors reliably receive all values.
SharedFlow broadcasts emitted values to all active collectors. It’s great for one-time events (like navigation, snackbars, etc.), and multiple collectors will receive the same emissions.
Kotlin Flow is a modern, efficient, and coroutine-friendly way to handle asynchronous data streams. By using Flow builders, operators, exception handling, and StateFlow/SharedFlow, developers can build scalable, efficient applications.
Kotlin’s coroutines have revolutionized asynchronous programming by making concurrency more manageable and readable. But to truly harness their power, understanding Coroutine Scopes is essential. In this guide, we’ll break down what Coroutine Scopes are, why they matter, and how they fit into Kotlin’s concurrency model. What Are Coroutine Scopes? A Coroutine Scope defines the lifecycle...
Kotlin is a powerful and flexible programming language that introduces many advanced features to make development easier. One such feature is Use-Site Variance in Kotlin, which helps handle type variance effectively in generic programming. If you’ve ever struggled with understanding variance in Kotlin, this guide will break it down in a simple, easy-to-understand way. What...
Kotlin’s Flow API has transformed the way we think about asynchronous data streams. But when your app needs to hold state or broadcast events, two specialized types of Flows shine the brightest: StateFlow and SharedFlow.
In this guide, we’ll break down StateFlow and SharedFlow in a simple way. Whether you’re working with Jetpack Compose, MVVM, or traditional Android UI, you’ll understand when and how to use each one — with examples.
StateFlow is similar to LiveData and is used to store a single state that updates over time.
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
fun main() = runBlocking {
val stateFlow = MutableStateFlow(0)
val job = launch {
stateFlow.collect { value ->
println("Collector received: $value")
}
}
delay(500)
stateFlow.value = 1
delay(500)
stateFlow.value = 2
delay(500)
job.cancel()
}
//Output
Collector received: 0
Collector received: 1
Collector received: 2StateFlow always emits the latest value to collectors. It behaves like LiveData, and collectors receive the current state immediately upon subscription.
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
fun main() = runBlocking {
// Create a MutableSharedFlow with a buffer capacity of 2
val sharedFlow = MutableSharedFlow<Int>(
replay = 0,
extraBufferCapacity = 2
)
val job1 = launch {
sharedFlow.collect { value ->
println("Collector 1 received: $value")
}
}
val job2 = launch {
sharedFlow.collect { value ->
println("Collector 2 received: $value")
}
}
// Delay to ensure collectors are active before emitting
delay(100)
sharedFlow.emit(10)
sharedFlow.emit(20)
delay(500)
job1.cancel()
job2.cancel()
}
// Output
Collector 1 received: 10
Collector 2 received: 10
Collector 1 received: 20
Collector 2 received: 20By default, MutableSharedFlow has no buffer and replay = 0, meaning it won’t emit any value unless a collector is ready at the moment of emission.
extraBufferCapacity = 2, allowing SharedFlow to buffer a couple of values while the collectors start.delay(100) before emitting, ensuring both collectors are already collecting.This way, both collectors reliably receive all values.
SharedFlow broadcasts emitted values to all active collectors. It’s great for one-time events (like navigation, snackbars, etc.), and multiple collectors will receive the same emissions.
Kotlin’s StateFlow and SharedFlow are powerful tools to build reactive UIs that are predictable, scalable, and cleanly architected. Understanding the difference between state and event helps you choose the right flow for the right situation.
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