Paging分页面是google推出的一个结合RecyclerView进行分页加载数据的一个全新架构库,主要是为了解决一次性加载大量数据而形成的资源浪费问题。经过分页的方式,每次加载一页数据,既能够加快界面的渲染,又能够减小对象等资源的建立消耗。具体能够看官网android
分页库主要由如下三个部分组成git
DataSource: 数据源,定义获取数据的方式,有三种方式,分别是github
1. PageKeyedDataSource
2. ItemKeyedDataSource
3. PositionalDataSource. 基于位置信息进行数据的加载,和Room数据库或者本地数据源一块儿搭配。
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PagedListAdapter: 分页库适配器,继承于RecyclerView的适配器,内部须要实现一个DiffUtil.ItemCallback差分器分析数据是否发生了改变。数据库
PagedList: 定义分页库的配置,分别有默认加载数据大小,分页数据大小等。而且经过PagedListAdapter将数据的变化进行更新。bash
因为这次使用的是本地数据,因此须要的列表的位置信息,在这里,咱们须要实现基于PositionalDataSource的数据源架构
class LocalDataSourceFactory:DataSource.Factory<Int, ArticleEntity>() {
override fun create(): DataSource<Int, ArticleEntity> {
return localDataSource
}
companion object {
val localDataSource = object : PositionalDataSource<ArticleEntity>() {
private fun computeCount(): Int {
return 10000
}
private fun loadRangeInternal(startPosition: Int, loadCount: Int): List<ArticleEntity> {
val articleList = mutableListOf<ArticleEntity>()
val authorPrefix = "做者"
val titlePrefix = "我是一个标题"
val typePrefix = "类别"
val timeStampBase = 1531548138000L
for (i in 0 until loadCount) {
var articleEntity = ArticleEntity()
articleEntity.id = (startPosition + i).toString()
articleEntity.author = "$authorPrefix ${articleEntity.id}"
articleEntity.title = "$titlePrefix ${articleEntity.id}"
articleEntity.type = "$typePrefix ${articleEntity.id}"
articleEntity.timeStamp = timeStampBase + i * 1000L
articleList.add(articleEntity)
}
return articleList
}
override fun loadRange(params: LoadRangeParams, callback: LoadRangeCallback<ArticleEntity>) {
Log.e("LoadRange", "range" + params.startPosition)
callback.onResult(loadRangeInternal(params.startPosition, params.loadSize))
}
override fun loadInitial(params: LoadInitialParams, callback: LoadInitialCallback<ArticleEntity>) {
val totalCount = computeCount()
val position = PositionalDataSource.computeInitialLoadPosition(params, totalCount)
val loadSize = PositionalDataSource.computeInitialLoadSize(params, position, totalCount)
callback.onResult(loadRangeInternal(position, loadSize), position, totalCount)
}
}
}
}
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须要实现PositionalDataSource的两个方法,分别是loadInitial和loadRange,loadInitial负责拉取配置的加载条数,即下文的PagedList配置, loadRange负责加载每次分页所需的数据。因此实现数据源很简单,只需定义好首次加载数据和分页加载数据的逻辑既可。ide
因为PagedListAdapter继承自RecyclerView的适配器,因此实现起来并不难,只是须要提供一个差分的实现用来进行数据的分析,代码以下:post
class ArticlePageAdapter : PagedListAdapter<ArticleEntity, ArticleViewHolder>(diffCallback) {
override fun onBindViewHolder(holder: ArticleViewHolder, position: Int) {
holder.bindTo(getItem(position))
}
override fun onCreateViewHolder(parent: ViewGroup, viewType: Int): ArticleViewHolder =
ArticleViewHolder(parent)
companion object {
private val diffCallback = object : DiffUtil.ItemCallback<ArticleEntity>() {
override fun areItemsTheSame(oldItem: ArticleEntity, newItem: ArticleEntity): Boolean =
oldItem.id == newItem.id
override fun areContentsTheSame(oldItem: ArticleEntity, newItem: ArticleEntity): Boolean =
oldItem == newItem
}
}
}
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PagedList主要是设置分页的大小,初始化加载的数据大小等配置。学习
val pagedListConfig =PagedList.Config.Builder().setEnablePlaceholders(true).setPageSize(10).setInitialLoadSizeHint(20).build()
var postList = LivePagedListBuilder(LocalDataSourceFactory(), pagedListConfig).build()
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经过以上代码生成是一个带LiveData的PagedListui
生成DataSource负责数据来源, 接着实现PagedListAdapter负责UI的渲染,最后进行PagedList分页的一些配置。生成一个带LiveData的PagedList,一旦数据进行变化,便会通知pageAdapter调用submitList进行UI的更新
class LocalDataPagingActivity:AppCompatActivity() {
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
setContentView(R.layout.act_local_data_paging)
val pageAdapter = ArticlePageAdapter()
recycle_article.adapter = pageAdapter
recycle_article.layoutManager = LinearLayoutManager(this)
val pagedListConfig = PagedList.Config.Builder().setEnablePlaceholders(true).setPageSize(10).setInitialLoadSizeHint(20).build()
var postList = LivePagedListBuilder(LocalDataSourceFactory(), pagedListConfig).build()
postList.observe(this, Observer {
pageAdapter.submitList(it)
})
}
}
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demo已经上传,点击传送门,若有疑惑或者错误,欢迎指出。
另一个传送门Android Paging分页库的学习(二)—— 结合Room数据库进行分页加载