Optimizing Asynchronous Programming with Flows in Kotlin: Introduction to Flow

1 – Introduction As the complexity of applications grows, handling multiple asynchronous events in real time becomes essential. To this end, Kotlin offers a powerful tool called Flow, which simplifies the management of asynchronous data flows. In this article, we will explore: What is a Flow and how does it differ from other approaches like suspend and async . Real use cases of Flow. Tools like Turbine to test data flows. 2 – What is a Flow? Kotlin Flow is a tool for handling asynchronous data flows. It works like a pipeline that emits values over time, allowing you to handle data streams efficiently. Main Features: Asynchronous: Flow emits values in a non-blocking manner. Cold Stream : A Flow only starts emitting values when there is a "sink" (i.e. when someone consumes the data). Cancellable: If the collector is canceled, the flow is also automatically canceled. 3 – Creating a Flow Simple Example of a Flow import kotlinx.coroutines.* import kotlinx.coroutines.flow.* fun main() = runBlocking { val flow = flow { for (i in 1..3) { emit(i) // Emits a value delay(1000) // Simulates a delay between emissions } } flow.collect { value -> println("Received: $value") } } Console Output Received: 1 Received: 2 Received: 3 Explanation: emit: Sends values to the stream. collect: Consumes the values emitted by the stream. 4 – Comparison: Flow vs. Other Approaches Appearance Flow suspend async Continuous data flow Yes No No Multiple values Yes No (only one value per call) No (returns a single value). Cancellable Yes Yes Yes Typical example Event streams Simple asynchronous calls Parallel computations. 5 – Transforming Data with Flow The real power of Flow lies in its ability to transform the data output with operators. Example: Using operators like map and filter import kotlinx.coroutines.* import kotlinx.coroutines.flow.* fun main() = runBlocking { val flow = flow { for (i in 1..5) { emit(i) } } flow .filter { it % 2 == 0 } // Filter even values .map { it * 10 } // Multiplies the values by 10 .collect { value -> println("Transformed: $value") } } Console Output Transformed: 20 Transformed: 40 6 – Testing Flows with Turbine Turbine is a library that facilitates the validation of values emitted by a Flow. Example with Turbine import app.cash.turbine.test import kotlinx.coroutines.* import kotlinx.coroutines.flow.* import kotlinx.coroutines.test.* fun main() = runTest { // Creates a stream that emits two values with a delay between them val flow = flow { println("Emitting value 1") emit(1) // Emit the first value delay(500) // Wait 500ms println("Emitting value 2") emit(2) // Emit the second value } // Test the flow flow.test { val firstValue = awaitItem() // Wait for the first value println("Value received from stream: $ firstValue ") assert(firstValue == 1) // Validates the first value val secondValue = awaitItem() // Wait for the second value println("Value received from stream: $ secondValue ") assert(secondValue == 2) // Validates the second value awaitComplete() // Check if the stream has completed println("Flow completed successfully!") } } Expected departure at terminal Emitting value 1 Value received from stream: 1 Emitting value 2 Value received from stream: 2 Flow completed successfully! 7 – Real Use Cases of Flow 7.1 – Real Time Update In a chat application, you can use a Flow to stream new messages to the user interface as they arrive from the server. import kotlinx.coroutines.* import kotlinx.coroutines.flow.* fun main() = runBlocking { val messages = flow { val newMessages = listOf("Hi", "How are you?", "See you soon!") for (message in newMessages) { emit(message) delay(1000) // Simulates interval between messages } } messages.collect { message -> println("New message: $message") } } 7.2 – Batch Data Processing Imagine a system that needs to process large batches of data at regular intervals. Flow makes this implementation easy. import kotlinx.coroutines.* import kotlinx.coroutines.flow.* fun main() = runBlocking { val batchFlow = flow { val lots = listOf("Lot1", "Lot2", "Lot3") for (lot in lots) { issue(batch) delay(2000) // Simulates processing time } } batchFlow.collect { lot -> println("Processing: $batch") } } 8 – Conclusion Flow is a powerful tool for handling asynchronous data in Kotlin , allowing you to emit, transform, and consume values in re

Mar 27, 2025 - 09:14

Optimizing Asynchronous Programming with Flows in Kotlin: Introduction to Flow

1 – Introduction

As the complexity of applications grows, handling multiple asynchronous events in real time becomes essential. To this end, Kotlin offers a powerful tool called Flow, which simplifies the management of asynchronous data flows.

In this article, we will explore:

What is a Flow and how does it differ from other approaches like suspend and async .
Real use cases of Flow.
Tools like Turbine to test data flows.

2 – What is a `Flow`?

Kotlin Flow is a tool for handling asynchronous data flows. It works like a pipeline that emits values over time, allowing you to handle data streams efficiently.

Main Features:

Asynchronous: Flow emits values in a non-blocking manner.
Cold Stream : A Flow only starts emitting values when there is a "sink" (i.e. when someone consumes the data).
Cancellable: If the collector is canceled, the flow is also automatically canceled.

3 – Creating a `Flow`

Simple Example of a `Flow`

import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*

fun main() = runBlocking {
    val flow = flow {
        for (i in 1..3) {
            emit(i) // Emits a value
            delay(1000) // Simulates a delay between emissions
        }
    }

    flow.collect { value ->
        println("Received: $value")
    }
}

Console Output

Received: 1
Received: 2
Received: 3

Explanation:

emit: Sends values to the stream.
collect: Consumes the values emitted by the stream.

4 – Comparison: Flow vs. Other Approaches

Appearance	Flow	suspend	async
Continuous data flow	Yes	No	No
Multiple values	Yes	No (only one value per call)	No (returns a single value).
Cancellable	Yes	Yes	Yes
Typical example	Event streams	Simple asynchronous calls	Parallel computations.

5 – Transforming Data with `Flow`

The real power of Flow lies in its ability to transform the data output with operators.

Example: Using operators like `map` and `filter`

import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*

fun main() = runBlocking {
    val flow = flow {
        for (i in 1..5) {
            emit(i)
        }
    }

    flow
        .filter { it % 2 == 0 } // Filter even values
        .map { it * 10 } // Multiplies the values by 10
        .collect { value ->
            println("Transformed: $value")
        }
}

Console Output

Transformed: 20
Transformed: 40

6 – Testing Flows with Turbine

Turbine is a library that facilitates the validation of values emitted by a Flow.

Example with Turbine

import app.cash.turbine.test
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.test.*

fun main() = runTest {
// Creates a stream that emits two values with a delay between them
    val flow = flow {
        println("Emitting value 1")
        emit(1) // Emit the first value
        delay(500) // Wait 500ms
        println("Emitting value 2")
        emit(2) // Emit the second value
    }

// Test the flow
    flow.test {
        val firstValue = awaitItem() // Wait for the first value
        println("Value received from stream: $ firstValue ")
        assert(firstValue == 1) // Validates the first value

        val secondValue = awaitItem() // Wait for the second value
        println("Value received from stream: $ secondValue ")
        assert(secondValue == 2) // Validates the second value

        awaitComplete() // Check if the stream has completed
        println("Flow completed successfully!")
    }
}

Expected departure at terminal

Emitting value 1
Value received from stream: 1
Emitting value 2
Value received from stream: 2
Flow completed successfully!

7 – Real Use Cases of `Flow`

7.1 – Real Time Update

In a chat application, you can use a Flow to stream new messages to the user interface as they arrive from the server.

import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*

fun main() = runBlocking {
    val messages = flow {
        val newMessages = listOf("Hi", "How are you?", "See you soon!")
        for (message in newMessages) {
            emit(message)
            delay(1000) // Simulates interval between messages
        }
    }

    messages.collect { message ->
        println("New message: $message")
    }
}

7.2 – Batch Data Processing

Imagine a system that needs to process large batches of data at regular intervals. Flow makes this implementation easy.

import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*

fun main() = runBlocking {
    val batchFlow = flow {
        val lots = listOf("Lot1", "Lot2", "Lot3")
        for (lot in lots) {
            issue(batch)
            delay(2000) // Simulates processing time
        }
    }

    batchFlow.collect { lot ->
        println("Processing: $batch")
    }
}

8 – Conclusion

Flow is a powerful tool for handling asynchronous data in Kotlin , allowing you to emit, transform, and consume values in real time. It is essential for building modern applications, especially in scenarios that require handling continuous streams of events.

Summary:

Flow is ideal for continuous, cancelable data streams.
Operators like map and filter make it easier to transform the outputted data.
Tools like Turbine simplify flow testing.

References:
Official Kotlin documentation on coroutines
Turbine Documentation