Efficiently Merge Two Kotlin Flows A Comprehensive Guide

Jul 7, 2025 by stackunigon 57 views

How to Efficiently Merge Two Kotlin Flows into One

In Kotlin, flows are a powerful tool for handling asynchronous data streams. They provide a clean and efficient way to work with sequences of data that are produced over time. Often, you'll encounter scenarios where you need to combine multiple flows into a single flow. This article explores different techniques for merging two flows into one, focusing on best practices and addressing common challenges.

Understanding Kotlin Flows

Before diving into merging flows, let's establish a clear understanding of what Kotlin flows are and why they are so valuable. Kotlin Flows are a type of cold asynchronous data stream that emits multiple values sequentially. They are part of Kotlin's coroutines library and provide a more structured and efficient way to handle asynchronous data compared to traditional approaches like callbacks or RxJava Observables.

Key Characteristics of Kotlin Flows:

Asynchronous: Flows operate asynchronously, allowing you to perform non-blocking operations and avoid freezing the main thread.
Cold Streams: Flows are cold, meaning they don't start emitting values until a collector starts observing them. This allows for efficient resource management.
Sequential Emission: Flows emit values sequentially, ensuring a predictable order of data processing.
Cancellation Support: Flows support cancellation, enabling you to stop the flow when it's no longer needed, preventing resource leaks.
Backpressure Handling: Flows offer various operators for handling backpressure, allowing you to control the rate at which data is emitted and consumed.

Why Use Flows?

Improved Code Readability: Flows provide a clean and declarative way to express asynchronous data streams, making your code easier to read and understand.
Simplified Error Handling: Flows have built-in mechanisms for handling errors, making your code more robust.
Efficient Resource Management: Flows' cold nature and cancellation support ensure efficient resource usage.
Rich Set of Operators: Flows come with a wide range of operators for transforming, filtering, and combining data streams.

Common Use Cases for Merging Flows

Merging flows is a common requirement in many applications. Here are a few examples:

Combining Data from Multiple Sources: Imagine you're building an application that displays data from multiple sources, such as a local database and a remote API. You can use flows to fetch data from each source and then merge the flows to present a unified data stream to the user interface.
Handling User Input and Network Events: In an interactive application, you might need to react to both user input events (like button clicks) and network events (like data updates from a server). Merging flows allows you to handle these different types of events in a coordinated manner.
Implementing Reactive UIs: Reactive user interfaces respond to changes in data automatically. Flows are an excellent tool for implementing reactive UIs, and merging flows can help you combine different data streams that drive the UI.

Techniques for Merging Two Flows

Kotlin provides several operators for merging flows. Let's explore the most common and effective techniques.

1. The `merge` Operator

The merge operator is the most straightforward way to combine two or more flows into a single flow. It simply emits values from each flow as they arrive, without any specific ordering or interleaving guarantees.

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

fun main() = runBlocking {
    val flow1 = flowOf(1, 2, 3).onEach { delay(100) }
    val flow2 = flowOf("a", "b", "c").onEach { delay(150) }

    val mergedFlow = merge(flow1, flow2)

    mergedFlow.collect {
        println(it)
    }
}

Explanation:

We create two flows, flow1 emitting integers and flow2 emitting strings. We use onEach { delay(...) } to simulate asynchronous emissions.
The merge(flow1, flow2) operator combines the two flows into mergedFlow.
The collect function subscribes to the merged flow and prints each emitted value.

Output (may vary due to concurrency):

1
a
2
b
3
c

Key Characteristics of merge:

Unordered Emission: Values from the input flows are emitted in the order they become available.
Concurrent Emission: If multiple flows emit values simultaneously, they will be processed concurrently.
No Interleaving Guarantees: The order in which values from different flows are interleaved is not guaranteed.

2. The `zip` Operator

The zip operator combines two flows by emitting pairs of values, one from each flow. It waits for both flows to emit a value before emitting a pair. If one flow emits values faster than the other, the extra values from the faster flow will be buffered until the slower flow emits a corresponding value.

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

fun main() = runBlocking {
    val flow1 = flowOf(1, 2, 3).onEach { delay(100) }
    val flow2 = flowOf("a", "b", "c").onEach { delay(150) }

    val zippedFlow = flow1.zip(flow2) { num, letter ->
        "$num-$letter"
    }

    zippedFlow.collect {
        println(it)
    }
}

Explanation:

We create two flows, flow1 emitting integers and flow2 emitting strings.
The flow1.zip(flow2) { num, letter -> ... } operator combines the flows. The lambda expression { num, letter -> ... } defines how the values from the two flows are combined.
In this case, we create a string by concatenating the integer and the letter.
The collect function subscribes to the zipped flow and prints each emitted value.

Output:

1-a
2-b
3-c

Key Characteristics of zip:

Paired Emission: Values are emitted in pairs, one from each flow.
Buffering: If one flow emits values faster, the extra values are buffered.
Termination: The resulting flow completes when any of the input flows completes.

3. The `combine` Operator

The combine operator is similar to zip, but it emits a new value whenever any of the input flows emits a value. It combines the latest values from each flow, even if the other flows haven't emitted a new value yet. This is useful when you need to react to changes in any of the input flows.

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

fun main() = runBlocking {
    val flow1 = flowOf(1, 2, 3).onEach { delay(100) }
    val flow2 = flowOf("a", "b", "c").onEach { delay(150) }

    val combinedFlow = combine(flow1, flow2) { num, letter ->
        "$num-$letter"
    }

    combinedFlow.collect {
        println(it)
    }
}

Explanation:

We create two flows, flow1 emitting integers and flow2 emitting strings.
The combine(flow1, flow2) { num, letter -> ... } operator combines the flows. The lambda expression { num, letter -> ... } defines how the latest values from the two flows are combined.
The collect function subscribes to the combined flow and prints each emitted value.

Output (may vary due to concurrency):

1-a
2-a
2-b
3-b
3-c

Key Characteristics of combine:

Latest Value Combination: Emits a new value whenever any input flow emits a value, combining the latest values from each flow.
No Buffering: Doesn't buffer values; it uses the latest value from each flow.
Initial Emission: May emit an initial value as soon as the first value from any flow is available.

Addressing the Specific Question: Improving Flow Merging with `_uiState.update`

The original question raises an interesting point about merging flows and updating UI state. The user mentions a situation where they need to call _uiState.update { } and return _uiState.value to ensure all edge cases are handled correctly. They also wonder why .update { } doesn't return the updated value directly.

Let's break down this issue and explore potential solutions.

The Problem: Updating UI State with Flows

When working with flows in UI applications, it's common to use a StateFlow or SharedFlow to hold the UI state. These flows are designed to emit the current state to any collectors, making it easy to update the UI reactively.

The _uiState.update { } function is a convenient way to update the state atomically. It takes a lambda expression that receives the current state and returns the new state. However, as the user points out, it doesn't directly return the updated value.

This can lead to situations where you need to access the updated state immediately after calling update { }, requiring you to access _uiState.value separately. This can feel a bit redundant and might introduce potential race conditions if not handled carefully.

Why `update { }` Doesn't Return the Value

The reason update { } doesn't return the updated value is primarily due to its design for atomic state updates. The update function is optimized for thread safety and ensuring that state updates are consistent, especially in concurrent environments. Returning the value directly might introduce overhead and complexity that could compromise the atomicity and performance of the update operation.

Solutions and Best Practices

Here are a few approaches to address this issue and improve your flow merging and UI state update logic:

Using combine for UI State Updates: The combine operator is particularly well-suited for scenarios where you need to update the UI state based on multiple flows. You can combine your input flows and then use the combine lambda to calculate the new UI state and emit it to your StateFlow or SharedFlow.
```
import kotlinx.coroutines.flow.*
import kotlinx.coroutines.runBlocking

data class UiState(val data1: Int? = null, val data2: String? = null)

fun main() = runBlocking {
    val flow1 = MutableStateFlow<Int?>(null)
    val flow2 = MutableStateFlow<String?>(null)
    val _uiState = MutableStateFlow(UiState())
    val uiState = _uiState.asStateFlow()

    val collecting = launch {
        uiState.collect {
            println("UI State: $it")
        }
    }

    combine(flow1, flow2) {
        data1, data2 ->
        UiState(data1, data2)
    }.onEach {
        _uiState.value = it
    }.collect()

    flow1.emit(1)
    flow2.emit("a")
    flow1.emit(2)

    collecting.cancel()
}
```
Explanation:
- We define a UiState data class to represent the UI state.
- We create two MutableStateFlow instances, flow1 and flow2, to represent the input data streams.
- We create a MutableStateFlow called _uiState to hold the UI state and expose it as a StateFlow called uiState.
- We use combine to combine flow1 and flow2. The lambda expression calculates the new UiState based on the latest values from the input flows.
- We use onEach to emit the calculated UiState to _uiState.
- This approach ensures that the UI state is updated whenever any of the input flows emit a new value.

Using transform for Complex State Updates: If your state update logic is more complex and involves multiple steps, you can use the transform operator to process the input flows and emit intermediate values before updating the UI state.

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

data class UiState(val data1: Int? = null, val data2: String? = null)

fun main() = runBlocking {
    val flow1 = flowOf(1, 2, 3).onEach { delay(100) }
    val flow2 = flowOf("a", "b", "c").onEach { delay(150) }
    val _uiState = MutableStateFlow(UiState())
    val uiState = _uiState.asStateFlow()

    val collecting = launch {
        uiState.collect {
            println("UI State: $it")
        }
    }

    merge(flow1, flow2.map { it.toInt() }).transform {
        emit(it)
        _uiState.update {
            it.let {
                UiState(it, it.toString())
            }
        }
    }.collect()

    collecting.cancel()
}

Explanation:

We use transform to process each emitted value from the merged flow.
Inside the transform block, we can perform multiple operations, including updating the _uiState using _uiState.update { }.
This approach allows for more fine-grained control over the state update process.

Creating a Custom Extension Function (Advanced): If you find yourself repeating the pattern of calling _uiState.update { } and then accessing _uiState.value frequently, you could create a custom extension function that encapsulates this logic.
```
import kotlinx.coroutines.flow.*

fun <T> MutableStateFlow<T>.updateAndGet(function: (T) -> T): T {
    value = function(value)
    return value
}
```
Explanation:
- This extension function adds a new function called updateAndGet to MutableStateFlow.
- The updateAndGet function takes a lambda expression that receives the current state and returns the new state.
- It updates the state using value = function(value) and then returns the updated value.
Usage:
```
import kotlinx.coroutines.flow.*    
import kotlinx.coroutines.runBlocking

data class UiState(val data1: Int? = null, val data2: String? = null)

fun main() = runBlocking {
    val _uiState = MutableStateFlow(UiState())

    val newState = _uiState.updateAndGet {
        UiState(1, "a")
    }

    println("New UI State: $newState")
}
```
- This approach provides a more concise way to update the state and get the updated value in a single operation.

Conclusion

Merging flows is a fundamental technique in Kotlin coroutines for handling asynchronous data streams. The merge, zip, and combine operators offer different ways to combine flows, each with its own characteristics and use cases. When updating UI state with flows, consider using combine for simple updates or transform for more complex scenarios. If you find yourself repeating a pattern, creating a custom extension function can improve code readability and maintainability. By understanding these techniques and best practices, you can efficiently and effectively merge flows in your Kotlin applications.

This article has provided a comprehensive guide on merging two Kotlin flows into one, covering various techniques, addressing common challenges, and offering practical solutions for UI state updates. By applying these principles, you can build robust and reactive applications that leverage the power of Kotlin flows.

Understanding Kotlin Flows

Key Characteristics of Kotlin Flows:

Why Use Flows?

Common Use Cases for Merging Flows

Techniques for Merging Two Flows

1. The merge Operator

2. The zip Operator

3. The combine Operator

Addressing the Specific Question: Improving Flow Merging with _uiState.update

The Problem: Updating UI State with Flows

Why update { } Doesn't Return the Value

Solutions and Best Practices

Conclusion

1. The `merge` Operator

2. The `zip` Operator

3. The `combine` Operator

Addressing the Specific Question: Improving Flow Merging with `_uiState.update`

Why `update { }` Doesn't Return the Value