Use generated Android SDKs

Firebase Data Connect client SDKs let you call your server-side queries and mutations directly from a Firebase app. You generate a custom client SDK in parallel as you design the schemas, queries and mutations you deploy to your Data Connect service. Then, you integrate methods from this SDK into your client logic.

As we've mentioned elsewhere, it's important to note that Data Connect queries and mutations are not submitted by client code and executed on the server. Instead, when deployed, Data Connect operations are stored on the server like Cloud Functions. This means you need to deploy corresponding client-side changes to avoid breaking existing users (for example, on older app versions).

That's why Data Connect provides you with a developer environment and tooling that lets you prototype your server-deployed schemas, queries and mutations. It also generates client-side SDKs automatically, while you prototype.

When you've iterated updates to your service and client apps, both server- and client-side updates are ready to deploy.

Generate your Kotlin SDK

As with most Firebase projects, work on your Firebase Data Connect client code takes place in a local project directory. Both the Data Connect VS Code extension and the Firebase CLI are important local tools for generating and managing client code.

SDK generation options are keyed to several entries in the dataconnect.yaml file generated when you initialized your project.

Initialize SDK generation

In your connector.yaml, add your outputDir, package and (for the web SDK) packageJsonDir.

connectorId: movies
generate:
  kotlinSdk:
    outputDir: ../../../src/main/java/com/myapplication
    package: com.myapplication

Replace outputDir with the path of the directory into which the generated code will be placed; this path is relative to the directory that contains the connector.yaml file itself. Replace package with the Kotlin package statement to be used in the generated files, or omit package to use a default package.

Update SDKs while prototyping

If you're prototyping interactively with the Data Connect VS Code extension and its Data Connect emulator, SDK source files are automatically generated and updated while you modify .gql files defining schemas, queries and mutations. This can be a useful feature in hot (re)loading workflows.

In other scenarios, if you're using the Data Connect emulator from the Firebase CLI, you can set a watch on .gql updates and also have SDK sources automatically updated.

Alternatively, you can use the CLI to regenerate SDKs whenever .gql files are changed:

firebase dataconnect:sdk:generate --watch

Generate SDKs for integration and for production releases

In some scenarios, such as preparing project sources to submit for CI tests, you can call the Firebase CLI for a batch update.

In these cases, use firebase dataconnect:sdk:generate.

Set up client code

Incorporate Data Connect into your client code

To set up your client code to use Data Connect and your generated SDK, first follow the standard Firebase setup instructions.

Then, add the following into the plugins section in app/build.gradle.kts:

// The Firebase team tests with version 1.8.22; however, other 1.8 versions,
// and all newer versions are expected work too.
kotlin("plugin.serialization") version "1.8.22" // MUST match the version of the Kotlin compiler

Then, add the following into the dependencies section in app/build.gradle.kts:

implementation("com.google.firebase:firebase-dataconnect:16.0.0-beta03")
implementation("org.jetbrains.kotlinx:kotlinx-coroutines-core:1.7.3")
implementation("org.jetbrains.kotlinx:kotlinx-serialization-core:1.5.1")
implementation("com.google.firebase:firebase-auth:23.1.0") // Optional
implementation("com.google.firebase:firebase-appcheck:18.0.0") // Optional

Initialize the Data Connect Android SDK

Initialize your Data Connect instance using the information you used to set up Data Connect (all available in the Firebase console Data Connect tab).

The ConnectorConfig object

The SDK requires a connector configuration object.

This object is automatically generated from serviceId and location in dataconnect.yaml, and connectorId in connector.yaml.

Getting a connector instance

Now that you've set up a configuration object, get a Data Connect connector instance. The code for your connector will be generated by the Data Connect emulator. If your connector name is movies and the Kotlin package is com.myapplication, as specified in connector.yaml, then retrieve the connector object by calling:

val connector = com.myapplication.MoviesConnector.instance

Run queries and mutations

With the connector object, you can run queries and mutations as defined in the GraphQL source code. Suppose your connector has these operations defined:

mutation createMovie($title: String!, $releaseYear: Int!, $genre: String!, $rating: Int!) {
  movie_insert(data: {
    title: $title
    releaseYear: $releaseYear
    genre: $genre
    rating: $rating
  })
}

query getMovieByKey($key: Movie_Key!) {
  movie(key: $key) { id title }
}

query listMoviesByGenre($genre: String!) {
  movies(where: {genre: {eq: $genre}}) {
    id
    title
  }
}

then you could create and retrieve a movie as follows:

val connector = MoviesConnector.instance

val addMovieResult1 = connector.createMovie.execute(
  title = "Empire Strikes Back",
  releaseYear = 1980,
  genre = "Sci-Fi",
  rating = 5
)

val movie1 = connector.getMovieByKey.execute(addMovieResult1.data.key)

println("Empire Strikes Back: ${movie1.data.movie}")

You can also retrieve multiple movies:

val connector = MoviesConnector.instance

val addMovieResult2 = connector.createMovie.execute(
  title="Attack of the Clones",
  releaseYear = 2002,
  genre = "Sci-Fi",
  rating = 5
)

val listMoviesResult = connector.listMoviesByGenre.execute(genre = "Sci-Fi")

println(listMoviesResult.data.movies)

You can also collect a Flow that will only produce a result when a new query result is retrieved using a call to the query's execute() method.

val connector = MoviesConnector.instance

connector.listMoviesByGenre.flow(genre = "Sci-Fi").collect { data ->
  println(data.movies)
}

connector.createMovie.execute(
  title="A New Hope",
  releaseYear = 1977,
  genre = "Sci-Fi",
  rating = 5
)

connector.listMoviesByGenre.execute(genre = "Sci-Fi") // will cause the Flow to get notified

Prototype and test your Android application

Instrument clients to use a local emulator

You can use the Data Connect emulator, whether from the Data Connect VS Code extension or from the CLI.

Instrumenting the app to connect to the emulator is the same for both scenarios.

val connector = MoviesConnector.instance

// Connect to the emulator on "10.0.2.2:9399"
connector.dataConnect.useEmulator()

// (alternatively) if you're running your emulator on non-default port:
connector.dataConnect.useEmulator(port = 9999)

// Make calls from your app

To switch to production resources, comment out lines for connecting to the emulator.

Data types in Data Connect SDKs

The Data Connect server represents common and custom GraphQL data types. These are represented in the SDK as follows.

Data Connect Type	Kotlin
String	String
Int	Int (32-bit integer)
Float	Double (64-bit float)
Boolean	Boolean
UUID	java.util.UUID
Date	com.google.firebase.dataconnect.LocalDate (was java.util.Date until 16.0.0-beta03)
Timestamp	com.google.firebase.Timestamp
Int64	Long
Any	com.google.firebase.dataconnect.AnyValue