# Asset Management ## How are assets managed? * `AssetBundle` is a container that provides asynchronous access to application resources (e.g., images, strings, fonts). Resources are associated with a string-based key and can be retrieved as bytes (via `AssetBundle.load`), a string (via `AssetBundle.loadString`), or structured data (via `AssetBundle.loadStructuredData`). A variety of subclasses support different methods for obtaining assets (e.g., `PlatformAssetBundle`, `NetworkAssetBundle`). Some bundles also support caching; if so, keys can be evicted from the bundle’s cache (via `AssetBundle.evict`). * `CachingAssetBundle` caches strings and structured data throughout the application’s lifetime (unless explicitly evicted). Binary data is not cached since the higher level methods are built atop `AssetBundle.load`, and the final representation is more efficient to store. * Every application is associated with a `rootBundle`. This `AssetBundle` contains the resources that were packaged when the application was built (i.e., as specified by `pubspec.yaml`). Though this bundle can be queried directly, `DefaultAssetBundle` provides a layer of indirection so that different bundles can be substituted (e.g., for testing or localization). ## How are assets fetched? * `NetworkAssetBundle` loads resources over the network. It does not implement caching; presumably, this is provided by the network layer. It provides a thin wrapper around dart’s `HttpClient`. * `PlatformAssetBundle` is a `CachingAssetBundle` subclass that fetches resources from a platform-specific application directory via platform messaging (specifically, `Engine`::`HandleAssetPlatformMessage`). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://flutter.megathink.com/brazilian-portuguese/assets/asset-management.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.