Macrobenchmark 1.2 has shipped a lot of new features in alpha, such as Power metrics and Custom trace metrics, generation of Baseline Profiles without root on Android 13, and recompilation without clearing app data on Android 14. In a large app, this can improve cold startup time by 30% on top of Baseline Profiles! The plugin also allows you to easily automate the new Dex Layout Optimization feature in AGP 8.1, which lets you define BaselineProfileRule tests that collect classes used during startup, and move them to the primary dex file in a multidex app to increase locality. The plugin lets you automate the task of running generation tasks, and pulling profiles from the device and integrating them into your build either periodically, or as part of your release process. Jetpack provides a new Baseline Profile Gradle Plugin in alpha, which supports AGP 8.0+, and can be easily added to your project in Studio Hedgehog (now in canary). Using performance libraries allows you to build performant apps and identify optimizations to maintain high performance, resulting in better end-user experiences.īaseline Profiles allow you to partially compile your app at install time to improve runtime and launch performance, and are getting big improvements in new tooling and libraries: While these changes do make the Laz圜olumn and LazyRow examples a few lines longer, it provides consistency across all lazy layouts. These APIs focus on helping you implement the key and contentType parameters to the standard items APIs that already exist for Laz圜olumn, LazyVerticalGrid as well as their equivalents in APIs like HorizontalPager. To support more lazy layouts, Paging Compose now provides slightly lower level extension methods on LazyPagingItems in itemKey and itemContentType. In Paging Compose 1.0.0-alpha19, there is support for all lazy layouts including custom layouts provided by the Wear and TV libraries. App data can be loaded gradually and gracefully within RecyclerViews or Compose lazy lists. The Paging library allows you to load and display small chunks of data to improve network and system resource consumption. We also added tUpEdgeToEdge() to easily set up the edge-to-edge display in a backward-compatible manner. In the Activity 1.8 alpha releases, The OnBackPressedCallback class now contains new Predictive Back progress callbacks for handling the back gesture starting, progress throughout the gesture, and the back gesture being canceled in addition to the previous handleOnBackPressed() callback for when the back gesture is committed. We are excited to see Google apps adopt Predictive Back including PlayStore, Calendar, News, and TV! The Activity APIs for Predictive Back for Android are stable and we have updated the best practices for using the supported system back callbacks BackHandler (for Compose), OnBackPressedCallback, or OnBackInvokedCallback. It is part of a multi-year release when fully implemented, this feature will let users preview the destination or other result of a back gesture before fully completing it, allowing them to decide whether to continue or stay in the current view. In Android 13, we introduced a predictive back gesture for Android devices such as phones, large screens, and foldables.
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