Kotlin Multiplatform Academy · 课时

将数据表作为 Flow 观察

在数据库发生变化时获取响应式更新

第 4 / 4 课13 个步骤

将数据表作为 Flow 观察 是 CoddyKit 上的免费 Kotlin Multiplatform Academy 课时。这是第 4 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Kotlin Multiplatform Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Kotlin Multiplatform Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Why Observe Instead of Poll

Re-running a query by hand misses changes. SQLDelight can push fresh results to you whenever the table changes.

Add the Coroutines Extension

Reactive queries need the coroutines-extensions artifact, which adds Flow support on top of your generated queries.

implementation("app.cash.sqldelight:coroutines-extensions:2.0.2")

Turn a Query into a Flow

Call asFlow on any select query to get a Flow that re-emits whenever the underlying table is written.

val flow = queries.selectAll().asFlow()

Map to Results

asFlow gives a query holder, so chain mapToList to emit a ready Kotlin list each time the data changes.

val players = queries.selectAll()
    .asFlow()
    .mapToList(Dispatchers.IO)

Single-Row Streams

For one row use mapToOneOrNull, which emits the row or null and updates automatically as that row changes.

queries.selectById(1)
    .asFlow()
    .mapToOneOrNull(Dispatchers.IO)

Collect in Shared Code

You consume the stream by collecting it. Every insert, update or delete to that table triggers a fresh emission.

players.collect { list -> render(list) }

Expose It as StateFlow

Wrap the Flow in a StateFlow so your shared ViewModel holds the latest list as a single source of truth.

val state = players.stateIn(scope, SharingStarted.Eagerly, emptyList())

Android Collects with Compose

On Android, collectAsState turns the StateFlow into Compose state, so the list recomposes automatically on every change.

val list by viewModel.state.collectAsState()

iOS Collects from Swift

On iOS you observe the same StateFlow from Swift and update SwiftUI, so both apps stay in sync with the database.

One Write, Both UIs Update

Insert a row anywhere and every active Flow re-emits. The database becomes the live source driving both platforms.

Pick the Right Dispatcher

Run mapping off the main thread by passing a background dispatcher, keeping the UI smooth while queries run.

Quick Check

You collect selectAll().asFlow().mapToList(...). When does it emit again?

在交互式课程中回答

Recap: Live Data

You turned queries into Flows, mapped them to results, exposed StateFlow, and let both UIs update on every write. Your shared database is now reactive. ✅

免费开始

用 AI 导师学习 Kotlin — 免费

在浏览器中编写并运行真实代码，获得全天候 AI 导师的即时帮助，并在网页或应用中继续学习。

课程: 30
课程: 120

免费开始学习查看完整课程

常见问题解答

「将数据表作为 Flow 观察」课时是免费的吗？

是的 — 「将数据表作为 Flow 观察」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Kotlin Multiplatform Academy 课程的其余内容，请升级到 CoddyKit PRO。 Kotlin Multiplatform Academy 课程共包含 4 节课。

「将数据表作为 Flow 观察」这节课中我会学到什么？

在数据库发生变化时获取响应式更新你通过在浏览器中直接运行的动手代码来练习 Kotlin Multiplatform Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Kotlin Multiplatform Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Kotlin Multiplatform Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 4 节课，共 4 节。

「将数据表作为 Flow 观察」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Kotlin Multiplatform Academy 课中编写并运行代码吗？

能。每节 Kotlin Multiplatform Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

← 返回 Kotlin Multiplatform Academy