MutableState or MutableStateFlow: A Perspective on what to use in Jetpack Compose

When building applications with Jetpack Compose, developers face a pivotal choice: should they use MutableState or MutableStateFlow to manage the state? Does your team have guidelines on when to opt for one over the other? Understanding the differences between these two options is crucial, as each offers distinct advantages depending on the use.

This article will explore the functionalities of both MutableState and MutableStateFlow, comparing their use cases and highlighting how they cater to different needs within the Compose ecosystem. Whether you are new to Compose or looking to deepen your understanding of state management, this discussion will provide valuable insights into making informed decisions when managing state in your apps.

What is MutableState?

MutableState is a state holder in Jetpack Compose that allows you to read and write values in a way that Compose can automatically track changes to that value. When a MutableState object's value changes, the system triggers a recomposition of all the composables that depend on this state. This makes it particularly powerful for building interactive UIs where the display needs to update in response to user interactions or other changes in application state.

Core Features of MutableState

• MutableState ensures that the UI elements always present the most up-to-date state. Once a value is updated, any composable that reads this state will display the updated information.
• Compose utilizes a recomposition mechanism, where only the composables that depend on the changed state are updated, rather than the entire UI tree. This selective recomposition improves performance and responsiveness.
• Using MutableState is straightforward — developers can declare state variables using the mutableStateOf function provided by Compose, simplifying application state management.

Using MutableState in Compose

Integrating MutableState in your Compose application involves declaring a state variable using mutableStateOf. Here’s a simple example:

@Composable
fun CounterExample() {
    val count = remember { mutableStateOf(0) }

    Button(onClick = { count.value++ }) {
        Text("You have clicked ${count.value} times")
    }
}

In this example, count is a MutableState<Int> that holds the number of times a button has been clicked. Each click updates this state, and Compose handles the UI updates automatically.

Benefits of Using MutableState

• Ease of Use: It reduces the boilerplate code needed to set up reactive data flows, making it easier to manage the state within the UI layer.
• Integration with Compose: MutableState is designed to work seamlessly with the reactive patterns of Jetpack Compose, providing a fluid and efficient way to handle dynamic content.
• Suitable for UI-centric State: It is ideal for states confined to specific UI components, providing a straightforward and effective way to manage UI interactions.

Using MutableState with Backing Properties in ViewModel

When working within a ViewModel in Jetpack Compose, MutableState can effectively be used with backing properties to encapsulate and manage the UI-related state. However, while MutableState is similar in some respects to MutableStateFlow, there are critical differences, especially in encapsulation and exposure.

What is a Backing Property?

A backing property allows you to provide a controlled way of accessing and updating your state. It is a common practice in Kotlin to use private mutable state internally in a class (like a ViewModel) while exposing an immutable or read-only version of that state to the outside world.

Example of MutableState with Backing Properties

Here’s how you might typically implement a backing property using MutableState in a ViewModel:

class CounterViewModel : ViewModel() {
    private val _count = mutableStateOf(0)
    val count: State<Int> get() = _count

    fun incrementCount() {
        _count.value++
    }
}

In this example, _count is a private MutableState<Int> which is not directly accessible from outside the ViewModel. Instead, the ViewModel exposes count, a read-only State<Int>. This pattern helps to preserve encapsulation and ensures that the state can only be modified through defined ViewModel methods like incrementCount().

Limitation Compared to MutableStateFlow

While MutableState works well within the scope of Jetpack Compose for managing UI state, it has a notable limitation compared to MutableStateFlow: it cannot be easily transformed into a truly read-only form. When you expose MutableState as a State, you still return the same underlying MutableState instance. Unlike StateFlow, where you can expose a read-only StateFlow from a mutable MutableStateFlow, MutableState does not offer an equivalent mechanism. If someone has access to the MutableState, they can cast it back to MutableState and modify its value, potentially leading to unintended side effects.

val mutableReference = viewModel.count as MutableState<Int>
mutableReference.value = 100  // Compromises the intended encapsulation

Launching Coroutines with Different Dispatchers

In Jetpack Compose and its surrounding architecture, you will likely want to update the UI-related state on the main thread because UI components must be updated from the UI thread. However, there may be scenarios where you perform heavy computations or IO operations that should not block the UI thread, and these tasks are typically dispatched to other threads like Dispatchers.IO or Dispatchers.Default.

Example Scenario: Heavy Computation Before State Update

Let’s consider a scenario where you have to perform a heavy computation before updating a state in your ViewModel:

class ComputationViewModel : ViewModel() {
    private val _result = mutableStateOf(0)
    val result: State<Int> get() = _result

    fun performComputation(input: Int) {
        viewModelScope.launch(Dispatchers.Default) {  // Launching on Default dispatcher
            val computedValue = heavyComputation(input)
            withContext(Dispatchers.Main) {  // Switching back to Main for UI update
                _result.value = computedValue
            }
        }
    }

    private fun heavyComputation(input: Int): Int {
        // Simulate a computation-intensive task
        return input * input
    }
}

This practice should be used to allow backing property like control.

class ComputationViewModel : ViewModel() {
    internal var result by mutableStateOf(0)
        private set
    

    fun performComputation(input: Int) {
        viewModelScope.launch(Dispatchers.Default) {  // Launching on Default dispatcher
            val computedValue = heavyComputation(input)
            withContext(Dispatchers.Main) {  // Switching back to Main for UI update
                _result.value = computedValue
            }
        }
    }

    private fun heavyComputation(input: Int): Int {
        // Simulate a computation-intensive task
        return input * input
    }
}

Key Points in the Example

• Non-UI Dispatcher: The coroutine is launched with Dispatchers.Default is optimized for CPU-intensive work that doesn’t block the main thread.
• Switching Contexts: After the computation, the context is changed to Dispatchers.Main using withContext(Dispatchers.Main). This is necessary because updating the MutableState that Compose is observing must be done on the main thread to prevent issues like race conditions or UI thread blocking. Otherwise, the coroutine will crash, and the state will not be updated.

Introduction to Flows in Jetpack Compose

Flow is particularly useful in reactive programming environments where data changes over time. It provides a way to handle asynchronous data streams within Kotlin's coroutines framework. In Jetpack Compose, Flow can observe changes in data layers, facilitating a data-driven UI architecture.

Key Features of Flow

• Cold Streams: Unlike hot streams, which are active before subscribers listen, Flow is a cold stream. This means that the execution of a Flow does not begin until an observer starts collecting data from it, and it restarts from the beginning with each new collector.
• Asynchronous by Nature: Flow supports asynchronous data sequences without blocking the main thread, allowing it to emit multiple values over time through coroutines.
• Composable Friendly: It integrates seamlessly with Jetpack Compose by allowing composables to reactively update whenever a new item is emitted from the Flow.

Flow and Jetpack Compose

In Jetpack Compose, Flow can effectively feed data changes from the data layer to the UI layer. This can include server responses, database changes, or user input processing. Flow’s ability to emit multiple values and be collected repeatedly makes it ideal for scenarios where data updates frequently and the UI needs to reflect these changes immediately.

Collecting Flows in Compose

You can use the collectAsState() composable function to collect a Flow in Compose. This function collects the values emitted by the Flow and represents them as the state in your composable functions, triggering recomposition whenever the flow emits a new value.

Here is a simple example:

@Composable
fun UserDisplay(userFlow: Flow<User>) {
    val user by userFlow.collectAsState(initial = User())

    Text(text = "Hello, ${user.name}")
}

Using Flow in ViewModel for Heavy Computations

When dealing with heavy computations or long-running tasks, leveraging Flow’s asynchronous capabilities allows for efficient, non-blocking data processing and updating.

Setting Up the ViewModel

Consider a ViewModel that performs a heavy computation and updates a Flow with the result. This computation will be executed on a background thread, exposing the result to the UI layer through a Flow.

class ComputationViewModel : ViewModel() {
    private val _result = MutableStateFlow<Int>(0) // Initial value
    val result: StateFlow<Int> = _result.asStateFlow()

    fun performComputation(input: Int) {
        viewModelScope.launch(Dispatchers.Default) {  // Using the Default dispatcher for CPU-intensive task
            val computedValue = heavyComputation(input)
            _result.emit(computedValue)  // Emitting from any thread is safe
        }
    }

    private fun heavyComputation(input: Int): Int {
        // Simulate a heavy computation
        return input * input
    }
}

Key Aspects of the Implementation

• Emitting on Any Thread: The key advantage here is that _result, a MutableStateFlow, can safely emit new values from any thread. This is a significant benefit over MutableState, where such updates must be made on the main thread. This flexibility is due to StateFlow's design, which is inherently thread-safe.
• Exposure as StateFlow: The internal MutableStateFlow is exposed as a read-only StateFlow using the asStateFlow() function. This ensures that the state can only be modified within the ViewModel, maintaining clean architecture principles.

Comparison of MutableState and MutableStateFlow

1. Scope and Use Case

MutableState

• Scope: Primarily designed to manage UI state within composables in Jetpack Compose.
• Use Case: This approach is best suited for a simple state that is local to individual composables or when the state does not need to be shared across different layers of the application.

MutableStateFlow

• Scope: A general-purpose state holder that is part of Kotlin’s coroutines and flow libraries, making it useful across all application layers.
• Use Case: This is ideal for states that are observed or shared across multiple components or layers of the application, such as in business logic or data handling.

2. Thread Safety and Concurrency

MutableState

• Updates must be made on the main thread, requiring careful threading management when interacting with background tasks.
• A lackof built-in concurrency support can complicate its use in more complex or multi-threaded environments.

MutableStateFlow

• Inherently thread-safe and can safely handle updates from any thread.
• Supports concurrent operations and can be combined with other flows, making it highly effective for reactive programming across different parts of an application.

3. Lifecycle and Stream Capabilities

MutableState

• Tightly coupled with the Compose runtime, which automatically handles lifecycle events within the UI.
• Does not inherently support streaming multiple values over time unless explicitly managed within composables.

MutableStateFlow

• Lifecycle-aware when used within scopes like viewModelScope, enhancing its reliability in long-lived operations.
• As a flow, it naturally supports emitting multiple values over time, providing a robust solution for dynamic data streams.

4. Read-Only Exposure

MutableState

• Does not support transforming into a read-only state directly. If exposed, it can be cast back to MutableState, potentially leading to unintended mutations.

MutableStateFlow

• It can be exposed as StateFlow, a read-only interface that prevents external mutations and adheres to best practices in encapsulation.

Personal Opinion

Flow is a more versatile and powerful tool for handling state across all application layers—from the UI to business logic and data access. The ability of Flow to integrate with coroutines enhances its capability to manage asynchronous data streams efficiently, making it an indispensable part of modern Android development. It allows for more scalable, maintainable, and performant applications by embracing the reactive programming model that is increasingly becoming the norm.

Personally, I find the reliance on the coroutine library for implementing Flow not just a necessity but a significant advantage. The symbiotic relationship between coroutines and Flow provides a framework for dealing with complex state and event-driven programming, often encountered in today's applications. At this point, I cannot imagine using Kotlin without the power and simplicity that coroutines offer. They transform challenging asynchronous programming tasks into more manageable, readable, and maintainable code.