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https://github.com/minhtule/PredictionIO-Swift-SDK
PredictionIO iOS / macOS SDK
https://github.com/minhtule/PredictionIO-Swift-SDK
Last synced: 9 days ago
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PredictionIO iOS / macOS SDK
- Host: GitHub
- URL: https://github.com/minhtule/PredictionIO-Swift-SDK
- Owner: minhtule
- License: apache-2.0
- Created: 2015-08-07T08:58:42.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2022-07-22T01:11:06.000Z (over 2 years ago)
- Last Synced: 2024-09-21T02:20:03.583Z (about 2 months ago)
- Language: Swift
- Homepage: https://minhtule.github.io/PredictionIO-Swift-SDK
- Size: 678 KB
- Stars: 22
- Watchers: 5
- Forks: 13
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-swift-cn - PredictionIO SDK - A convenient API to communicate with PredictionIO's Event Server and ML Engines. (Libs / API)
README
# PredictionIO Swift SDK
[](https://travis-ci.org/minhtule/PredictionIO-Swift-SDK)
The Swift SDK provides a convenient API for your iOS and macOS application to record your users' behaviors in the [PredictionIO](https://github.com/apache/predictionio) event server and retrieve predictions from PredictionIO engines.
## Requirements
- iOS 10+ or macOS 10.10+
- Xcode 11+
- Swift 5+
- PredictionIO 0.12.0+
## Installation
### Cocoapods
Install [CocoaPods](https://cocoapods.org/), the dependency manager for Cocoa project.
```bash
$ gem install cocoapods
```
To integrate PredictionIO, add the following lines to your `Podfile`.
```ruby
source 'https://github.com/CocoaPods/Specs.git'
platform :ios, '10.0'
use_frameworks!
target '' do
pod 'PredictionIO', '~> 3.0'
end
```
Then run the following command.
```bash
$ pod install
```
Finally, import the SDK in your Swift files before using.
```swift
import PredictionIO
```
## Usage
### EngineClient
Use `EngineClient` to query predictions from the PredictionIO Engines.
```swift
// 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 }
print(response.itemScores)
}
```
### EventClient
Use `EventClient` to send information to the PredictionIO Event Server.
```swift
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 }
print(response.eventID)
}
```
There are other convenience methods to manage User and Item entity types. Please see the [API documentation](http://minhtule.github.io/PredictionIO-Swift-SDK/index.html) for more details.
## Documentation
The documentation is generated by [jazzy](https://github.com/realm/jazzy). To build the documentation, run
```bash
$ jazzy
```
The latest API documentation is available at http://minhtule.github.io/PredictionIO-Swift-SDK/index.html.
## iOS Demo App
Please follow this [quick guide](http://predictionio.apache.org/templates/recommendation/quickstart/) 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](https://github.com/minhtule/Tapster-iOS-Demo), a recommender for comics, to see a more extensive intergration of the SDK.
## License
PredictionIO Swift SDK is released under the Apache License 2.0. Please see
[LICENSE](https://github.com/minhtule/PredictionIO-Swift-SDK/blob/master/LICENSE) for details.