Library for persisting key-value data in common code across multiple platforms. Features include platform-specific settings implementations, factory classes, property delegates, listeners, and experimental support for serialization and coroutines.
This is a Kotlin library for Multiplatform apps, so that common code can persist key-value data.
A Korean translation of this readme is available separately, maintained by @wooram-yang
The Settings interface has implementations on the Android, iOS, macOS, watchOS, tvOS, JS, WasmJS, JVM, and Windows
platforms.
The following table shows the names of implementing classes and what platforms they're available on.
ObservableSettings interfaceSuspendSettings and FlowSettings rather than Settings or ObservableSettingsMapSettings is intended for use in unit tests and will not persist data to storage
When writing multiplatform code, you might need to interoperate with platform-specific code which needs to share the
same data-source. To facilitate this, all Settings implementations wrap a delegate object which you could also use in
your platform code.
Since that delegate is a constructor argument, it should be possible to connect it via any dependency-injection strategy
you might already be using. If your project doesn't have such a system already in place, one strategy is to use expect
declarations, for example
expect val settings: Settings
// or
expect fun createSettings(): Settings
Then the actual implementations can pass the platform-specific delegates.
See Platform constructors below for more details on these delegates.
Some platform implementations also include Factory classes. These make it easier to manage multiple named Settings
objects from common code, or to automate some platform-specific configuration so that delegates don't need to be created
manually. The factory still needs to be injected from platform code, but then from common you can call
val settings1: Settings = factory.create("my_first_settings")
val settings2: Settings = factory.create("my_other_settings")
See Factories below for more details.
However, if all of your key-value logic exists in a single instance in common code, these ways of
instantiation Settings can be inconvenient. To make pure-common usage easier, Multiplatform Settings now includes a
separate module which provides a Settings() factory function, so that you can create a Settings instance like
val settings: Settings = Settings()
See No-arg module below for more details.
The Android implementation is SharedPreferencesSettings, which wraps SharedPreferences.
val delegate: SharedPreferences // ...
val settings: Settings = SharedPreferencesSettings(delegate)
On iOS, macOS, tvOS, or watchOS, NSUserDefaultsSettings wraps NSUserDefaults.
val delegate: NSUserDefaults // ...
val settings: Settings = NSUserDefaultsSettings(delegate)
You can also use KeychainSettings which writes to the Keychain. Construct it by passing a String which will be
interpreted as a service name.
val serviceName: String // ...
val settings: Settings = KeychainSettings(serviceName)
Two JVM implementations exist. PreferencesSettings wraps Preferences and PropertiesSettings wraps Properties.
val delegate: Preferences // ...
val settings: Settings = PreferencesSettings(delegate)
val delegate: Properties // ...
val settings: Settings = PropertiesSettings(delegate)
On JS and WasmJS, StorageSettings wraps Storage.
val delegate: Storage // ...
val settings: Settings = StorageSettings(delegate)
val settings: Settings = StorageSettings() // use localStorage by default
There is a Windows implementation RegistrySettings which wraps the Windows registry.
val rootKey: String = "SOFTWARE\\..." // Will be interpreted as subkey of HKEY_CURRENT_USER
val settings: Settings = RegistrySettings(rootKey)
For some platforms, a Factory class also exists, so that multiple named Settings instances can coexist with the
names being controlled from common code.
On Android, this factory needs a Context parameter
val context: Context // ...
val factory: Settings.Factory = SharedPreferencesSettings.Factory(context)
On most other platforms, the factory can be instantiated without passing any parameter
val factory: Settings.Factory = NSUserDefaultsSettings.Factory()
If you have a Factory reference from your common code, then you can use it to create multiple Settings with
different names.
val settings1: Settings = factory.create("my_first_settings")
val settings2: Settings = factory.create("my_other_settings")
If the default Factorys don't do what you need, you can also implement your own.
To create a Settings instance from common without needing to pass platform-specific dependencies, add
the multiplatform-settings-no-arg gradle dependency. This exports multiplatform-settings as an API dependency, so
you can use it as a replacement for that default dependency.
implementation("com.russhwolf:multiplatform-settings-no-arg:1.3.0")
Then from common code, you can write
val settings: Settings = Settings()
This is implemented via a top-level function Settings() to provide constructor-like
syntax even though Settings has no constructor.
On Android, this delegates to the equivalent of PreferenceManager.getDefaultSharedPreferences() internally. It makes
use of androidx-startup to get a Context
reference without needing to pass one manually. On Apple platforms, it uses . On
JS, it uses . On JVM, it uses the implementation with as a
delegate. On Windows, it reads the name of the executable being built and writes to a subkey of
using that name.
Note that while the main multiplatform-settings module publishes common code to all available Kotlin platforms,
the multiplatform-settings-no-arg module only publishes to platforms which have concrete implementations.
Note also that the no-arg module is there to make getting started easier with less configuration, but there are plenty
of things it doesn't provide, such as the ability to use an encrypted implementation on platforms that support it, or
the ability to substitute a test implementation. Notably, you can't call Settings() from an Android unit test because
the internals that allow it to get a Context reference won't run (not even if you use Robolectric).
If you need a non-default setup you likely are better off not using multiplatform-settings-no-arg.
Once the Settings instance is created, you can store values by calling the various putXXX() methods, or their
operator shortcuts
settings.putInt("key", 3)
settings["key"] = 3
You can retrieve stored values via the getXXX() methods or their operator shortcuts. If a key is not present, then the
supplied default will be returned instead.
val a: Int = settings.getInt("key")
val b: Int = settings.getInt("key", defaultValue = -1)
val c: Int = settings["key", -1]
Nullable methods are also available to avoid the need to use a default value. Instead, null will be returned if a key
is not present.
val a: Int? = settings.getIntOrNull("key")
val b: Int? = settings["key"]
The getXXX() and putXXX() operation for a given key can be wrapped using a property delegate. This has the advantage
of ensuring that the key is always accessed with a consistent type.
val a: Int by settings.int("key")
val b: Int by settings.int("key", defaultValue = -1)
Nullable delegates exists so that absence of a key can be indicated by null instead of a default value
val a: Int? by settings.nullableInt("key")
The key parameter can be omitted for delegates, and the property name will be reflectively used instead.
val a: Int by settings.int() // internally, key is "a"
Existence of a key can be queried
val a: Boolean = settings.hasKey("key")
val b: Boolean = "key" in settings
Values can also be removed by key
settings.remove("key")
settings -= "key"
settings["key"] = null
Finally, all values in a Settings instance can be removed
settings.clear()
The set of keys and amount of entries can be retrieved
val keys: Set<String> = settings.keys
val size: Int = settings.size
Note that for the NSUserDefaultsSettings implementation, some entries are unremovable and therefore may still be
present after a clear() call. Thus, size is not generally guaranteed to be zero after a clear().
Update listeners are available for some implementations. These are marked
with the ObservableSettings interface, which includes an addListener() method.
val observableSettings: ObservableSettings // ...
val settingsListener: SettingsListener = observableSettings.addIntListener(key) { value: Int -> /* ... */ }
val settingsListener: SettingsListener = observableSettings.addNullableIntListener(key) { value: Int? -> /* ... */ }
The SettingsListener returned from the call should be used to signal when you're done listening:
settingsListener.deactivate()
If you don't hold a strong reference to the SettingsListener, it's possible in some implementations that it will be
garbage-collected and stop sending updates.
A testing dependency is available to aid in testing code that interacts with this library.
implementation("com.russhwolf:multiplatform-settings-test:1.3.0")
This includes a MapSettings implementation of the Settings interface, which is backed by an in-memory MutableMap
on all platforms.
The Settings interface is published to all available platforms. Developers who desire implementations outside of the
defaults provided are free to add their own implementations, and are welcome to make pull requests if the implementation
might be generally useful to others. Note that implementations which require external dependencies should be places in a
separate gradle module in order to keep the core multiplatform-settings module dependency-free.
Certain APIs are marked with @ExperimentalSettingsApi or @ExperimentalSettingsImplementation to highlight areas that
may have the potential to break in the future and should not be considered stable to depend on.
The KeychainSettings implementation on Apple platforms and the RegistrySettings implementation on Windows are
considered experimental. Feel free to reach out if they're working well for you, or if you encounter any issues with
them, to help remove that experimental status.
A kotlinx-serialization integration exists so it's easier to save non-primitive data
implementation("com.russhwolf:multiplatform-settings-serialization:1.3.0")
This essentially uses the Settings store as a serialization format. Thus for a serializable class
@Serializable
class SomeClass(val someProperty: String, anotherProperty: Int)
an instance can be stored or retrieved
val someClass: SomeClass
val settings: Settings
// Store values for the properties of someClass in settings
settings.encodeValue(SomeClass.serializer(), "key", someClass)
// Create a new instance of SomeClass based on the data in settings
val newInstance: SomeClass = settings.decodeValue(SomeClass.serializer(), "key", defaultValue)
val nullableNewInstance: SomeClass = settings.decodeValueOrNull(SomeClass.serializer(), "key")
To remove a serialized value, use removeValue() rather than remove()
settings.removeValue(SomeClass.serializer(), "key")
// Don't remove if not all expected data is preset
settings.removeValue(SomeClass.serializer(), "key", ignorePartial = true)
To check for the existance of a serialized value, use containsValue() rather than contains().
val isPresent = settings.containsValue(SomeClass.serializer(), "key")
There's also a delegate API, similar to that for primitives
val someClass: SomeClass by settings.serializedValue(SomeClass.serializer(), "someClass", defaultValue)
val nullableSomeClass: SomeClass? by settings.nullableSerializedValue(SomeClass.serializer(), "someClass")
All APIs also have variants that infer a serializer implicitly rather than taking one as a parameter. These APIs throw if the class is not serializable.
settings.encodeValue("key", someClass)
val newInstance: SomeClass = settings.decodeValue("key", defaultValue)
val nullableNewInstance: SomeClass = settings.decodeValueOrNull("key")
// etc
Usage requires accepting both the @ExperimentalSettingsApi and @ExperimentalSerializationApi annotations.
A separate multiplatform-settings-coroutines dependency includes various coroutine APIs.
implementation("com.russhwolf:multiplatform-settings-coroutines:1.3.0")
This adds flow extensions for all types which use the listener APIs internally.
val observableSettings: ObservableSettings // Only works with ObservableSettings
val flow: Flow<Int> by observableSettings.getIntFlow("key", defaultValue)
val nullableFlow: Flow<Int?> by observableSettings.getIntOrNullFlow("key")
There are also StateFlow extensions, which require a coroutine scope.
val observableSettings: ObservableSettings // Only works with ObservableSettings
val coroutineScope: CoroutineScope
val stateFlow: StateFlow<Int> by observableSettings.getIntStateFlow("key", defaultValue)
val nullableStateFlow: StateFlow<Int?> by observableSettings.getIntOrNullStateFlow("key")
In addition, there are two new Settings-like interfaces: SuspendSettings, which looks similar to Settings but all
functions are marked suspend, and FlowSettings which extends SuspendSettings to also include Flow-based getters
similar to the extensions mentioned above.
val suspendSettings: SuspendSettings // ...
val a: Int = suspendSettings.getInt("key") // This call will suspend
val flowSettings: FlowSettings // ...
val flow: Flow<Int> = flowSettings.getIntFlow("key")
There are APIs provided to convert between these different interfaces so that you can select one to use primarily from common.
val settings: Settings // ...
val suspendSettings: SuspendSettings = settings.toSuspendSettings()
val observableSettings: ObservableSettings // ...
val flowSettings: FlowSettings = observableSettings.toFlowSettings()
// Wrap suspend calls in runBlocking
val blockingSettings: Settings = suspendSettings.toBlockingSettings()
val blockingSettings: ObservableSettings = flowSettings.toBlockingObservableSettings()
An implementation of FlowSettings exists in the multiplatform-settings-datastore dependency, based
on Jetpack DataStore. Because DataStore is now a
multiplatform library, starting in version 1.2.0, this module is available on all platforms where DataStore is
available, rather than being limited to Android and JVM.
implementation("com.russhwolf:multiplatform-settings-datastore:1.3.0")
This provides a DataStoreSettings class
val dataStore: DataStore // = ...
val settings: FlowSettings = DataStoreSettings(dataStore)
You can use this in shared code by converting other ObservableSettings instances to FlowSettings. For example:
// Common
expect val settings: FlowSettings
// Android
actual val settings: FlowSettings = DataStoreSettings(/*...*/)
// iOS
actual val settings: FlowSettings = NSUserDefaultsSettings(/*...*/).toFlowSettings()
Or, if you also include platforms without listener support, you can use SuspendSettings instead.
// Common
expect val settings: SuspendSettings
// Android
actual val settings: SuspendSettings = DataStoreSettings(/*...*/)
// iOS
actual val settings: SuspendSettings = NSUserDefaultsSettings(/*...*/).toSuspendSettings()
// JS
actual val settings: SuspendSettings = StorageSettings().toSuspendSettings()
The experimental multiplatform-settings-make-observable module adds an extension function Settings.makeObservable()
in common code which converts a Settings instance to ObservableSettings by directly wiring in callbacks rather than
native observability methods.
val settings: Settings // = ...
val observableSettings: ObservableSettings = settings.makeObservable()
This has the advantage of enabling observability on platforms which don't have an observable implementation. It has the disadvantage that updates will only be delivered to the same instance where changes were made.
Multiplatform Settings is currently published to Maven Central, so add that to repositories.
repositories {
mavenCentral()
// ...
}
Then, simply add the dependency to your common source-set dependencies
commonMain {
dependencies {
// ...
implementation("com.russhwolf:multiplatform-settings:1.3.0")
}
}
See also the sample project, which uses this structure.
The project includes multiple CI jobs configured using Github Actions. On PRs or updates to the main branch, the build
will run the scripts in build-linux.yml, build-macos.yml, build-windows.yml, and validate-gradle-wrapper.yml.
These builds the library and runs unit tests for all platforms across Linux, Mac, and Windows hosts. In addition, the
library build artifacts are deployed to the local maven repository and the sample project is built for the platforms on
which it is implemented. This ensures that the sample remains in sync with updates to the library.
An addition build script is defined in deploy.yml, which runs on a manual trigger. This builds the library for all
platforms and uploads artifacts to staging on Maven Central. Uploaded artifacts must still be published manually
Copyright 2018-2023 Russell Wolf
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this except compliance the License.
You may obtain a copy of the License at
http:
Unless applicable law agreed to writing, software
distributed under the License distributed an BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express implied.
See the License the specific language governing permissions
limitations under the License.
Made with JetBrains tools
| Class | Backing API | Platforms |
|---|
KeychainSettings2 | Apple Keychain | iOS, macOS, watchOS, tvOS |
NSUserDefaultsSettings1 | User Defaults | iOS, macOS, watchOS, tvOS |
PreferencesSettings1 | java.util.prefs.Preferences | JVM |
PropertiesSettings | java.util.Properties | JVM |
SharedPreferencesSettings1 | android.content.SharedPreferences | Android |
StorageSettings | Web Storage (localStorage) | JS, WasmJS |
RegistrySettings2 | Windows Registry | MingwX64 |
DataStoreSettings3 | androidx.datastore.core.DataStore | Android, JVM, Native |
MapSettings1,4 | kotlin.collections.MutableMap | All platforms |
NSUserDefaults.standardUserDefaultslocalStoragePreferencesPreferences.userRoot()HKEY_CURRENT_USER\SOFTWARESurfaced from shared tags and platforms — no rankings paid for.