Android
Asynchronous Programming for app performance in Android
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Kotlin Coroutine & Flows
Coroutines in kotlin are light-weight structures to control the asynchronous functions without killing the thread. Unlike freezing an entire thread when waiting for, let’s say, a task (like a network call) while deleting extra trash and optimizing the code, coroutines "pause" and then “unpause” when the time is right. This means you can write asynchronous code that will look like synchronous code which is easier to comprehend and debug.
Flows are used in combination with coroutines to handle streams of values which are produced over time: updates or events. Issuing and usage of flows is valid both for the data which is changed frequently or updated repeatedly, for example, live feed or in the case of event stream data. Flows are not coroutines that yield one value at the point but generate value sets at different temporal granularity levels and let take these values at these levels.
Benefit of asynchronous programming
Kotlin Coroutines and Flows offer a viable method of dealing with asynchronous work and data streams.
Coroutines
- Readable Asynchronous Code: Coroutines also makes programming asynchronous code look as close to synchronous as it is possible for the underlying runner to be and thus makes code more comprehensible.
- Non-blocking Suspension: The operations created with coroutines are capable of suspending and unwrapping, other operations can proceed in parallel while the coroutine doesn’t need to catch the thread.
- Scoped Task Management: Structured concurrency can make coroutines as easy to manage within scopes as ordinary threads; task cancellation and memory dealing are much more manageable.
- Lightweight: Benefits that come with the use of coroutines include the fact that it uses far less resource than what threads require to get a variety of tasks up and running.
Flows
Efficient Data Streaming: Data flows are used to manage streams which in their turns are suitable for cases when several values are generated at particular moments, such as sensor or GUI events.
Real-time Response: Flows enable the app to respond to the data change as it happens hence suitable for use in real-time updates.
Resource Efficiency: Flows are "cold " until they are collected that is, they do not start producing data until they are used thus, saving on power resources.
Seamless with Coroutines: Coroutines, in their turn, correlate well with flows allowing for plain working with the streams in non-blocking threads.
Usage of both
Coroutine
1. Performing Background Tasks: Another technical concept that is obscure to many people is coroutines which are used as a method of delegating some scopes of work like network access, file operations or a database query, to a background thread while the main UI is not blocked. For instance:
GlobalScope.launch {
val result = performNetworkRequest() withContext(Dispatchers.Main) { updateUI(result) }}
2. Parallel Operations: Coroutines can be used to run two or more functions at a time and then pause a corountine while the rest of its process continues without having to stop threads. This can be done using async and await When we use async and await, it means that after creating an instance of a class, we can then launch it later when executing other code at the same time :
val deferred1 = async { fetchDataPart1() }
val deferred2 = async { fetchDataPart2() }val combinedData = deferred1.await() + deferred2.await() 3. Structured Concurrency: To make the use of coroutine-scoped (like android’s viewModelScope) coroutines can be attached to the life cycle of a given element. This makes it easy for the user to cancel the specific tasks if a component, such as, ViewModel or Activity gets destroyed.
Kotlin
1. Data Streams: Flows are used to process streams of data of definite character – for instance, various measurements from sensors, real-time notifications, network updates etc. It can be made to generate values to be output in the form of a flow:
fun fetchDataStream(): Flow<Int> = flow {
for (i in 1..5) { delay(1000) emit(i) }} 2. State Management in UI: Flows help in UI state updating as a response, making it usable to gather data in the course of the change. For instance, when implementing StateFlow in a ViewModel it can send new data to the UI infinitely. private val _state = MutableStateFlow<MyState>(initialState)
val state: StateFlow<MyState> = _statefun updateState(newState: MyState) { _state.value = newState}
3. Reactive Programming: It also contains the so called Flow operators, like map, filter, collect to shape, filter and manage emitted value reactive manner. This is useful mainly for preparing the data before is needed, so it provides a functional way for handling the stream of data.
fetchDataStream()
.filter { it % 2 == 0 }.map { it * 2 }.collect { println("Collected value: $it") } Conclusion
Coroutine and Flows of Kotlin are quite useful for handling async task and real-time data operations. This poor man’s concurrent future and allows for non-blocking, structured concurrency to make writing clean, readable code for things such as network requests and parallel processing more straightforward. Flows supplement this by handling streaming of data making it possible to support real-time updates and reactive programming. Combined they form the basis of a holistic system of engineering resilient, sustainable and well-architectured applications that minimize code clutter and enhance the user interface.
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