Pager

public final void append()

Loads a page at the end of current loaded data. Provides a way to manually trigger appends without scrolling.

This function is no-op if there are no more data to be loaded from the datasource (i.e. append is LoadState.NotLoading.Complete)

Appends that are triggered by scrolling (i.e. if user scrolls to end of the list and triggers PagingConfig.prefetchDistance) takes precedence over this append. This ensures that items that are currently accessed gets loaded in first.

No-op if preceding append returned LoadState.Error. To recover from error, use retry

public final @NonNull Flow<@NonNull PagingData<@NonNull Value>> getFlow()

A cold Flow of PagingData, which emits new instances of PagingData once they become invalidated by PagingSource.invalidate or calls to AsyncPagingDataDiffer.refresh or PagingDataAdapter.refresh.

To consume this stream as a LiveData or in Rx, you may use the extensions available in the paging-runtime or paging-rxjava* artifacts.

NOTE: Instances of PagingData emitted by this Flow are not re-usable and cannot be submitted multiple times. This is especially relevant for transforms such as Flow.combine, which would replay the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the Flow in a way that returns a new instance of PagingData with cached data pre-loaded.

public final void prepend()

Loads a page at the start of current loaded data. Provides a way to manually trigger prepends without scrolling.

This function is no-op if there are no more data to be loaded from the datasource (i.e. prepend is LoadState.NotLoading.Complete)

Prepends that are triggered by scrolling (i.e. if user scrolls to start of the list and triggers PagingConfig.prefetchDistance) takes precedence over this prepend. This ensures that items that are currently accessed gets loaded in first.

No-op if preceding prepend returned LoadState.Error. To recover from error, use retry

public final void refresh()

Refresh all currently loaded data.

The refresh key is the key that was used to load the current first loaded page, and the loadSize is the size of current loaded data.

Note that this is a best-effort attempt to reload all current data. Actual loaded data may differ based on how PagingSource.load handles the same key for different LoadType. For example the current first page might have been a prepended page, and PagingSource.load could handle the same key in different ways for LoadType.PREPEND versus LoadType.REFRESH

public final void refresh(@NonNull Value item)

Refresh based on a given loaded item.

The refresh key is the key that was originally used to the load the page that contains item, and the loadSize is PagingConfig.initialLoadSize.

Note that this is a best-effort attempt to reload around the given loaded item. The requested item is expected to be in the first page of reloaded items but will likely not be the very first reloaded item. For example if two pages are currently loaded with loadKeys MyKey1 and MyKey2 respectively:

• pg1: MyKey1 = items 0, 1, 2, 3

• pg2: MyKey2 = items 4, 5, 6, 7 If this method were called with item 5 - refresh(5) - then the refreshKey will be MyKey2, which will theoretically refresh starting at (item 4) until (item4 + initialLoadSize).

public final void retry()

Retry most recent load that returned PagingSource.LoadResult.Error. No-op if there were no errors.

Applicable to all LoadTypes. The retry is not guaranteed to succeed as the cause of the initial may persist on retries.

public final @NonNull LiveData<@NonNull PagingData<@NonNull Value>> PagingLiveData.getLiveData(
    @NonNull Pager<@NonNull Key, @NonNull Value> receiver
)

A LiveData of PagingData, which mirrors the stream provided by Pager.flow, but exposes it as a LiveData.

NOTE: Instances of PagingData emitted by this LiveData are not re-usable and cannot be submitted multiple times. This is especially relevant because LiveData will replays the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the LiveData in a way that returns a new instance of PagingData with cached data pre-loaded.

public final @NonNull Flowable<@NonNull PagingData<@NonNull Value>> PagingRx.getFlowable(@NonNull Pager<@NonNull Key, @NonNull Value> receiver)

A Flowable of PagingData, which mirrors the stream provided by Pager.flow, but exposes it as a Flowable.

NOTE: Instances of PagingData emitted by this Flowable are not re-usable and cannot be submitted multiple times. This is especially relevant for transforms, which would replay the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the Flowable in a way that returns a new instance of PagingData with cached data pre-loaded.

public final @NonNull Flowable<@NonNull PagingData<@NonNull Value>> PagingRx.getFlowable(@NonNull Pager<@NonNull Key, @NonNull Value> receiver)

A Flowable of PagingData, which mirrors the stream provided by Pager.flow, but exposes it as a Flowable.

NOTE: Instances of PagingData emitted by this Flowable are not re-usable and cannot be submitted multiple times. This is especially relevant for transforms, which would replay the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the Flowable in a way that returns a new instance of PagingData with cached data pre-loaded.

public final @NonNull Observable<@NonNull PagingData<@NonNull Value>> PagingRx.getObservable(
    @NonNull Pager<@NonNull Key, @NonNull Value> receiver
)

An Observable of PagingData, which mirrors the stream provided by Pager.flow, but exposes it as an Observable.

NOTE: Instances of PagingData emitted by this Observable are not re-usable and cannot be submitted multiple times. This is especially relevant for transforms, which would replay the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the Observable in a way that returns a new instance of PagingData with cached data pre-loaded.

public final @NonNull Observable<@NonNull PagingData<@NonNull Value>> PagingRx.getObservable(
    @NonNull Pager<@NonNull Key, @NonNull Value> receiver
)

An Observable of PagingData, which mirrors the stream provided by Pager.flow, but exposes it as an Observable.

NOTE: Instances of PagingData emitted by this Observable are not re-usable and cannot be submitted multiple times. This is especially relevant for transforms, which would replay the latest value downstream. To ensure you get a new instance of PagingData for each downstream observer, you should use the cachedIn operator which multicasts the Observable in a way that returns a new instance of PagingData with cached data pre-loaded.