Pros of compose-multiplatform

• Supports multiple platforms (Android, iOS, desktop) with a single codebase
• Leverages Kotlin Multiplatform for shared business logic
• Provides a unified UI framework across platforms

Cons of compose-multiplatform

• Less mature ecosystem compared to Android-specific Compose
• May have performance overhead due to cross-platform abstraction
• Limited access to platform-specific features without additional work

Code Comparison

compose-samples (Android-specific):

@Composable
fun Greeting(name: String) {
    Text(text = "Hello $name!")
}

compose-multiplatform:

@Composable
expect fun PlatformSpecificGreeting(name: String)

@Composable
fun Greeting(name: String) {
    PlatformSpecificGreeting(name)
}

Summary

compose-multiplatform offers cross-platform development capabilities, allowing developers to target multiple platforms with a single codebase. However, it may have limitations in terms of platform-specific features and performance compared to the Android-specific compose-samples. The code structure in compose-multiplatform often requires platform-specific implementations, while compose-samples focuses solely on Android development.

Pros of Epoxy

• Mature library with extensive documentation and community support
• Works well with existing XML-based layouts and Java/Kotlin codebases
• Offers powerful data binding and view holder caching mechanisms

Cons of Epoxy

• Steeper learning curve compared to Jetpack Compose
• Requires more boilerplate code for complex UI structures
• Less flexible for dynamic UI changes compared to declarative approaches

Code Comparison

Epoxy:

class HeaderModel(
    @EpoxyAttribute var title: String
) : EpoxyModelWithHolder<HeaderHolder>() {
    override fun bind(holder: HeaderHolder) {
        holder.titleView.text = title
    }
    override fun getDefaultLayout(): Int = R.layout.header_item
}

Compose Samples:

@Composable
fun Header(title: String) {
    Text(
        text = title,
        style = MaterialTheme.typography.h6
    )
}

The Epoxy example demonstrates the more verbose approach of creating a custom model and binding data to views, while the Compose example showcases the concise, declarative nature of Jetpack Compose for creating UI components.

Pros of Accompanist

• Focuses on providing additional libraries and utilities for Jetpack Compose
• Offers more specialized components like pagers, placeholder, and navigation-animation
• Regularly updated with new features and improvements

Cons of Accompanist

• Smaller scope compared to the comprehensive examples in compose-samples
• May require additional setup and dependencies for specific features
• Less beginner-friendly, as it assumes more familiarity with Compose

Code Comparison

Accompanist (Pager implementation):

val pagerState = rememberPagerState()
HorizontalPager(
    count = 10,
    state = pagerState,
) { page ->
    Text(text = "Page: $page")
}

compose-samples (Basic list implementation):

LazyColumn {
    items(10) { index ->
        Text(text = "Item: $index")
    }
}

Summary

Accompanist provides specialized libraries for Jetpack Compose, offering more advanced components and utilities. compose-samples, on the other hand, focuses on providing comprehensive examples and best practices for building apps with Compose. While Accompanist is great for developers looking for specific enhancements, compose-samples serves as a better starting point for those learning Compose or seeking reference implementations.

Pros of Picasso

• Lightweight and focused on image loading and caching
• Easier to integrate into existing projects without major architectural changes
• More mature and stable, with a longer history of production use

Cons of Picasso

• Limited to image handling, not a comprehensive UI toolkit
• Less modern approach compared to Jetpack Compose's declarative UI
• Fewer built-in animation and layout capabilities

Code Comparison

Picasso (image loading):

Picasso.get()
    .load("https://example.com/image.jpg")
    .into(imageView)

Compose Samples (image loading):

Image(
    painter = rememberImagePainter("https://example.com/image.jpg"),
    contentDescription = "Sample Image"
)

Summary

Picasso is a specialized library for efficient image loading and caching in Android applications. It's lightweight and easy to integrate into existing projects. Compose Samples, on the other hand, showcases Jetpack Compose, a modern toolkit for building native Android UIs. While Compose offers a more comprehensive approach to UI development with declarative syntax and built-in components, Picasso remains a solid choice for projects primarily focused on image handling or those not ready to adopt a new UI paradigm.

Pros of Glide

• Mature and widely adopted image loading library with extensive documentation
• Efficient memory and disk caching for improved performance
• Supports a wide range of image formats and sources

Cons of Glide

• Not specifically designed for Jetpack Compose
• Requires more boilerplate code compared to Compose's built-in image loading
• May have a steeper learning curve for developers new to Android

Code Comparison

Glide:

Glide.with(context)
    .load(imageUrl)
    .placeholder(R.drawable.placeholder)
    .error(R.drawable.error)
    .into(imageView)

Compose-samples:

AsyncImage(
    model = imageUrl,
    contentDescription = null,
    placeholder = painterResource(R.drawable.placeholder),
    error = painterResource(R.drawable.error)
)

Summary

Glide is a powerful image loading library for Android, offering robust features and optimizations. However, Compose-samples showcases modern Android development using Jetpack Compose, providing more concise and declarative UI code. While Glide excels in traditional Android development, Compose-samples demonstrates the simplicity and power of Compose for building user interfaces, including image loading capabilities.

Pros of Litho

• Mature and battle-tested in large-scale production environments
• Efficient recycling and reuse of UI components
• Strong focus on performance optimization for complex UIs

Cons of Litho

• Steeper learning curve due to its unique approach
• Less intuitive API compared to Jetpack Compose
• Limited community resources and third-party libraries

Code Comparison

Litho:

@LayoutSpec
class MyComponentSpec {
  @OnCreateLayout
  static Component onCreateLayout(ComponentContext c) {
    return Text.create(c)
        .text("Hello, Litho!")
        .textSizeDip(20)
        .build();
  }
}

Compose:

@Composable
fun MyComponent() {
    Text(
        text = "Hello, Compose!",
        fontSize = 20.sp
    )
}

Key Differences

• Litho uses a declarative API with Java annotations, while Compose uses Kotlin and a more functional approach
• Litho requires a separate build step for code generation, whereas Compose does not
• Compose offers a more intuitive and concise syntax for UI development
• Litho provides fine-grained control over performance optimizations, while Compose handles many optimizations automatically

Use Cases

• Litho: Large-scale apps with complex UIs and strict performance requirements
• Compose: Modern Android apps prioritizing developer productivity and ease of use