PredictionIO Swift SDK

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The Swift SDK provides a convenient API for your iOS and macOS application to record your users’ behaviors in the PredictionIO event server and retrieve predictions from PredictionIO engines.


  • iOS 10+ or macOS 10.10+
  • Xcode 11+
  • Swift 5+
  • PredictionIO 0.12.0+



Install CocoaPods, the dependency manager for Cocoa project.

$ gem install cocoapods

To integrate PredictionIO, add the following lines to your Podfile.

source ''
platform :ios, '10.0'

target '<Your target name>' do
    pod 'PredictionIO', '~> 3.0'

Then run the following command.

$ pod install

Finally, import the SDK in your Swift files before using.

import PredictionIO



Use EngineClient to query predictions from the PredictionIO Engines.

// Response format of a Recommendation engine.
struct RecommendationResponse: Decodable {
    struct ItemScore: Decodable {
        let item: String
        let score: Double

    let itemScores: [ItemScore]

let engineClient = EngineClient(baseURL: "http://localhost:8000")
let query = [
    "user": "1",
    "num": 2

engineClient.sendQuery(query, responseType: RecommendationResponse.self) { result in
    guard let response = result.value else { return }



Use EventClient to send information to the PredictionIO Event Server.

let eventClient = EventClient(accessKey: "Access key of the app", baseURL: "http://localhost:7070")
let event = Event(
    event: "rate",
    entityType: "user",
    entityID: "1",
    targetEntity: (type: "item", id: "9"),
    properties: [
        "rating": 5

eventClient.createEvent(event) { result in
    guard let response = result.value else { return }


There are other convenience methods to manage User and Item entity types. Please see the API documentation for more details.


The documentation is generated by jazzy. To build the documentation, run

$ jazzy

The latest API documentation is available at

iOS Demo App

Please follow this quick guide to start the Event Server and set up a Recommendation Engine on your local machine first.

You also need to:

  • Include your app’s access key in RatingViewController.swift.
  • Import some data using the python script as instructed in step 4. Alternatively, you can use the demo app to record new rating events; however, remember to re-train and deploy the engine before querying for recommendations.
  • Run the simulator!

There are 2 screens in the demo app:

  • Rating: corresponding to step 4. Collecting Data in the quick guide.
  • Recommendation: corresponding to step 6. Use the Engine in the quick guide.

Tapster iOS Demo

Also check out Tapster iOS, a recommender for comics, to see a more extensive intergration of the SDK.


PredictionIO Swift SDK is released under the Apache License 2.0. Please see LICENSE for details.