I'm currently looking into incorporating the Paging Architecture library (version 2.1.0-beta01
at the time of writing) into my app. One components is a list which allows the user to delete individual items from it. This list is network-only and caching localy with Room does not make sense.
PagedList
is immutable and does not support modification. I have read that having a copy of the list which is than modified and returned as the new one is the way to go. The documentation states the same:
If you have more granular update signals, such as a network API signaling an update to a single item in the list, it's recommended to load data from the network into memory. Then present that data to the PagedList via a DataSource that wraps an in-memory snapshot. Each time the in-memory copy changes, invalidate the previous DataSource, and a new one wrapping the new state of the snapshot can be created.
I currently have the basic recommended implementation to show a simple list. My DataSource
looks like this:
class MyDataSource<SomeItem> : PageKeyedDataSource<Int, SomeItem>() {
override fun loadInitial(params: LoadInitialParams<Int>, callback: LoadInitialCallback<Int, SomeItem>) {
// Simple load from API and notification of `callback`.
}
override fun loadAfter(params: LoadParams<Int>, callback: LoadCallback<Int, SomeItem>) {
// Simple load from API and notification of `callback`.
}
override fun loadBefore(params: LoadParams<Int>, callback: LoadCallback<Int, SomeItem>) {
// Simple load from API and notification of `callback`.
}
}
How would a concrete implementation of an in-memory cache (without Room and without invalidating the entire dataset) as referenced in the documentation look like?