Analytics for Kotlin (Server)


With Analytics-Kotlin, you can send data using Kotlin applications to any analytics or marketing tool without having to learn, test, or implement a new API every time. Analytics-Kotlin enables you to process and track the history of a payload, while Segment controls the API and prevents unintended operations.

Analytics-Kotlin is in public beta and currently supports these destinations with Segment actively adding more to the list. Segment’s First-Access and Beta terms govern this library.

You can choose to set up your Analytics Kotlin source on mobile or on the server. Segment doesn’t support device-mode destinations on the server-side.

If you’re migrating to Analytics-Kotlin from a different mobile library, you can skip to the migration guide.

Getting Started

To get started with the Analytics-Kotlin server library:

  1. Create a Source in Segment.
    1. Go to Connections > Sources > Add Source.
    2. Search for Kotlin (Server) and click Add source.
  2. Add the Analytics dependency to your build.gradle.

    Segment recommends you to install the library with a build system like Gradle, as it simplifies the process of upgrading versions and adding integrations. The library is distributed through Jitpack. Add the analytics module to your build.gradle as a dependency as shown in the code sample below.

      repositories {
        maven { url 'https://jitpack.io' }
      }
      dependencies {
          implementation 'com.github.segmentio.analytics-kotlin:core:+'
      }
    
  3. Initialize and configure the client.

    Segment recommends you to initialize the client in your main function.

     Analytics("YOUR_WRITE_KEY") {
         application = "MainApp"
         flushAt = 3
         flushInterval = 10
     }
    


    Note: Unlike the Analytics-Android SDK, the Analytics-Kotlin SDK doesn’t provide a singleton instance and relies on you to keep track of the instance.


    These are the options you can apply to configure the client:

    Option Name Description
    writeKey required This is your Segment write key.
    application Default set to null.
    The application specific object (in the case of Android: ApplicationContext).
    apiHost Default set to api.segment.io/v1.
    This sets a default API Host to which Segment sends events.
    autoAddSegmentDestination Default set to true.
    This automatically adds the Segment Destination plugin. You can set this to false if you want to manually add the Segment Destination plugin.
    collectDeviceId Default set to false.
    Set to true to automatically collect the device Id.
    defaultSettings Default set to {}.
    The settings object used as fallback in case of network failure.
    flushAt Default set to 20.
    The count of events at which Segment flushes events.
    flushInterval Default set to 30 (seconds).
    The interval in seconds at which Segment flushes events.
    recordScreenViews Default set to false.
    Set to true to automatically trigger screen events on Activity Start.
    storageProvider Default set to ConcreteStorageProvider.
    The provider for storage class. It’s best not to modify this as it can disrupt your storage logic and you won’t be able to correctly store events.
    trackApplicationLifecycleEvents Default set to false.
    Set to true to automatically track Lifecycle events.
    trackDeepLinks Default set to false.
    Set to true to automatically track opened Deep Links based on intents.
    useLifecycleObserver Default set to false.
    Set to true to use LifecycleObserver to track Application lifecycle events.

Tracking Methods

Once you’ve installed the mobile or server Analytics-Kotlin library, you can start collecting data through Segment’s tracking methods:

For any of the different methods described, you can replace the properties and traits in the code samples with variables that represent the data collected.

Identify

The Identify method lets you tie a user to their actions and record traits about them. This includes a unique user ID and any optional traits you know about them like their email, name, address. The traits option can include any information you want to tie to the user. When using any of the reserved traits, be sure the information reflects the name of the trait. For example, email should always be a string of the user’s email address.

fun identify(userId: String, traits: JsonObject = emptyJsonObject)

// If <T> is annotated with @Serializable you will not need to provide a serializationStrategy
fun <T> identify(userId: String, traits: T, serializationStrategy: KSerializer<T>)
analytics.identify("user-123", buildJsonObject {
    put("username", "MisterWhiskers")
    put("email", "hello@test.com")
    put("plan", "premium")
});

Track

The Track method lets you record the actions your users perform. Every action triggers an event, which also has associated properties that the track method records.

fun track(name: String, properties: JsonObject = emptyJsonObject)

// If <T> is annotated with @Serializable you will not need to provide a serializationStrategy
fun <T> track(name: String, properties: T, serializationStrategy: KSerializer<T>)
analytics.track("View Product", buildJsonObject {
    put("productId", 123)
    put("productName" "Striped trousers")
});

Screen

The Screen method lets you record whenever a user sees a screen in your mobile app, along with optional extra information about the page being viewed.

You’ll want to record a screen event whenever the user opens a screen in your app. This could be a view, fragment, dialog or activity depending on your app.

Not all integrations support screen, so when it’s not supported explicitly, the screen method tracks as an event with the same parameters.

fun screen(screenTitle: String, properties: JsonObject = emptyJsonObject, category: String = "")

// If <T> is annotated with @Serializable you will not need to provide a serializationStrategy
fun <T> screen(screenTitle: String, properties: T, category: String = "", serializationStrategy: KSerializer<T>)
analytics.screen("ScreenName", buildJsonObject {
    put("productSlug", "example-product-123")
});

Add the AndroidRecordScreenPlugin to enable automatic screen tracking.

Group

The Group method lets you associate an individual user with a group— whether it’s a company, organization, account, project, or team. This includes a unique group identifier and any additional group traits you may have, like company name, industry, number of employees. You can include any information you want to associate with the group in the traits option. When using any of the reserved group traits, be sure the information reflects the name of the trait. For example, email should always be a string of the user’s email address.

fun group(groupId: String, traits: JsonObject = emptyJsonObject)

// If <T> is annotated with @Serializable you will not need to provide a serializationStrategy
fun <T> group(groupId: String, traits: T, serializationStrategy: KSerializer<T>)
analytics.group("user-123", buildJsonObject {
    put("username", "MisterWhiskers")
    put("email", "hello@test.com")
    put("plan", "premium")
});

Plugin Architecture

Segment’s plugin architecture enables you to modify and augment how the analytics client works. From modifying event payloads to changing analytics functionality, plugins help to speed up the process of getting things done.

Plugins are run through a timeline, which executes in order of insertion based on their entry types. Segment has these 5 entry types:

Type Details
before Executes before event processing begins.
enrichment Executes as the first level of event processing.
destination Executes as events begin to pass off to destinations.
after Executes after all event processing completes. You can use this to perform cleanup operations.
utility Executes only with manual calls such as Logging.

Fundamentals

There are 3 basic types of plugins that you can use as a foundation for modifying functionality. They are: Plugin, EventPlugin, and DestinationPlugin.

Plugin

Plugin acts on any event payload going through the timeline.

For example, if you want to add something to the context object of any event payload as an enrichment:

class SomePlugin: Plugin {
    override val type = Plugin.Type.Enrichment
    override val name = "SomePlugin"

    override var lateinit analytics: Analytics

    override fun execute(event: BaseEvent): BaseEvent? {
        event.putInContext("foo", "bar")
        return event
    }
}

EventPlugin

EventPlugin is a plugin interface that acts on specific event types. You can choose the event types by only overriding the event functions you want.

For example, if you only want to act on track & identify events:

class SomePlugin: EventPlugin {
    override fun track(event: TrackEvent): BaseEvent? {
        // code to modify track event
        return event
    }
    override fun identify(event: TrackEvent): BaseEvent? {
        // code to modify identify event
        return event
    }
}

DestinationPlugin

The DestinationPlugin interface is commonly used for device-mode destinations. This plugin contains an internal timeline that follows the same process as the analytics timeline, enabling you to modify and augment how events reach a particular destination.

For example, if you want to implement a device-mode destination plugin for Amplitude, you can use this:

class AmplitudePlugin: DestinationPlugin() {
    override val key = "Amplitude" // This is the name of the destination plugin, it is used to retrieve settings internally

    val amplitudeSDK: Amplitude // This is an instance of the partner SDK

    init { // Initializing the partner SDK and setting things up
        amplitudeSDK = Amplitude.instance
        amplitudeSDK.initialize(applicationContext, "API_KEY");
    }

    /*
    * Implementing this function allows this plugin to hook into any track events
    * coming into the analytics timeline
    */
    override fun track(event: TrackEvent): BaseEvent? {
        amplitudeSDK.logEvent(event.name)
        return event
    }
}

Advanced concepts

  • setup(Analytics): Use this function to setup your plugin. This implicitly calls once the plugin registers.
  • update(Settings): Use this function to react to any settings updates. This implicitly calls when settings update. You can force a settings update by calling analytics.checkSettings().
  • AndroidLifecycle hooks Plugins can also hook into AndroidLifecycle functions by implementing an interface. These functions call implicitly as the lifecycle events process.
  • DestinationPlugin timeline: The destination plugin contains an internal timeline that follows the same process as the analytics timeline, enabling you to modify/augment how events reach the particular destination. For example if you only wanted to add a context key when sending an event to Amplitude:
val amplitudePlugin = AmplitudePlugin()
analytics.add(amplitudePlugin) // add amplitudePlugin to the analytics client

val amplitudeEnrichment = object: Plugin {
    override val type = Plugin.Type.Enrichment
    override val name = "SomePlugin"

    override var lateinit analytics: Analytics

    override fun execute(event: BaseEvent): BaseEvent? {
        event.putInContext("foo", "bar")
        return event
    }
}

amplitudePlugin.add(amplitudeEnrichment) // add enrichment plugin to amplitude timeline

Adding a plugin

Adding plugins enable you to modify your analytics implementation to best fit your needs. You can add a plugin using this:

val yourPlugin = SomePlugin()
analytics.add(yourPlugin)

Though you can add plugins anywhere in your code, it’s best to implement your plugin when you configure the client.

Here’s an example of adding a plugin to the context object of any event payload as an enrichment:

class SomePlugin: Plugin {
    override val type = Plugin.Type.Enrichment
    override val name = "SomePlugin"

    override var lateinit analytics: Analytics

    override fun execute(event: BaseEvent): BaseEvent? {
        event.putInContext("foo", "bar")
        return event
    }
}
val yourPlugin = SomePlugin()
analytics.add(yourPlugin)

Utility Methods

The Analytics-Kotlin utility methods help you work with plugins from the analytics timeline. They include:

There’s also the Flush method to help you manage the current queue of events.

Add

The Add method lets you add a plugin to the analytics timeline.

fun add(plugin: Plugin): Analytics
val plugin = object: Plugin {
    override val type = Plugin.Type.Enrichment
    override val name = "SomePlugin"
    override var lateinit analytics: Analytics
}
analytics.add(plugin)

Find

The Find method lets you find a registered plugin from the analytics timeline.

fun find(pluginName: String): Plugin
val plugin = analytics.find("SomePlugin")

Remove

The Remove methods lets you remove a registered plugin from the analytics timeline.

fun remove(pluginName: String): Analytics
analytics.remove("SomePlugin")

Flush

The Flush method lets you force flush the current queue of events regardless of what the flushAt and flushInterval is set to.

public fun flush()
analytics.flush("SomePlugin")

This page was last modified: 14 Sep 2021



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