https://github.com/apache/predictionio-sdk-ruby

PredictionIO Ruby SDK
https://github.com/apache/predictionio-sdk-ruby

big-data predictionio scala

Last synced: about 1 month ago
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PredictionIO Ruby SDK

• Host: GitHub
• URL: https://github.com/apache/predictionio-sdk-ruby
• Owner: apache
• License: apache-2.0
• Archived: true
• Created: 2013-02-01T13:29:10.000Z (over 11 years ago)
• Default Branch: develop
• Last Pushed: 2018-09-20T18:41:33.000Z (over 5 years ago)
• Last Synced: 2024-04-25T23:57:36.699Z (about 1 month ago)
• Topics: big-data, predictionio, scala
• Language: Ruby
• Size: 104 KB
• Stars: 191
• Watchers: 29
• Forks: 39
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Lists

• awesome-ruby - PredictionIO Ruby SDK - The PredictionIO Ruby SDK provides a convenient API to quickly record your users' behavior and retrieve personalized predictions for them. (Machine Learning)

README

        


# Apache PredictionIO Ruby SDK

[![Build Status](https://api.travis-ci.org/apache/predictionio-sdk-ruby.svg?branch=develop)](https://github.com/apache/predictionio-sdk-ruby)

[![Gem Version](https://badge.fury.io/rb/predictionio.svg)](http://badge.fury.io/rb/predictionio)

The Ruby SDK provides a convenient wrapper for PredictionIO Event Server API and

Engine API. It allows you to quickly record your users' behavior and retrieve

personalized predictions for them.

## Documentation

Full Ruby SDK documentation can be found [here](http://www.rubydoc.info/github/apache/incubator-predictionio-sdk-ruby).

Please see the [PredictionIO App Integration

Overview](http://predictionio.apache.org/appintegration/) to

understand how the SDK can be used to integrate PredictionIO Event Server and

Engine with your application.

## Installation

Ruby 2+ required!

The module is published to [RubyGems](http://rubygems.org/gems/predictionio) and

can be installed directly by:

```sh

gem install predictionio

```

Or using [Bundler](http://bundler.io/) with:

```

gem 'predictionio', '0.12.1'

```

## Sending Events to Event Server

Please refer to [Event Server

documentation](http://predictionio.apache.org/datacollection/) for

event format and how the data can be collected from your app.

### Instantiate Event Client and connect to PredictionIO Event Server

```ruby

require 'predictionio'

# Define environment variables.

ENV['PIO_THREADS'] = '50' # For async requests.

ENV['PIO_EVENT_SERVER_URL'] = 'http://localhost:7070'

ENV['PIO_ACCESS_KEY'] = 'YOUR_ACCESS_KEY' # Find your access key with: `$ pio app list`.

# Create PredictionIO event client.

client = PredictionIO::EventClient.new(ENV['PIO_ACCESS_KEY'], ENV['PIO_EVENT_SERVER_URL'], Integer(ENV['PIO_THREADS']))

```

### Create a `$set` user event and send it to Event Server

```ruby

client.create_event(

  '$set',

  'user',

  user_id

)

```

### Create a `$set` item event and send it to Event Server

```ruby

client.create_event(

  '$set',

  'item',

  item_id,

  { 'properties' => { 'categories' => ['Category 1', 'Category 2'] } }

)

```

### Create a `$set` item event and send it to Event Server to specific channel

*NOTE:* channels are supported in PIO version >= 0.9.2 only. Channel must be created first.

```ruby

client.create_event(

  '$set',

  'item',

  item_id,

  { 'properties' => { 'categories' => ['Category 1', 'Category 2'], 'channel' => 'test-channel'} }

)

```

### Create a user 'rate' item event and send it to Event Server

```ruby

client.create_event(

  'rate',

  'user',

  user_id, {

    'targetEntityType' => 'item',

    'targetEntityId' => item_id,

    'properties' => { 'rating' => 10 }

  }

)

```

### Asynchronous request

To send an async request, simply use the `acreate_event` method instead of

`create_event`. Be aware that the asynchronous method does not throw errors.

It's best to use the synchronous method when first getting started.

## Query PredictionIO Engine

### Connect to the Engine:

```ruby

# Define environmental variables.

ENV['PIO_ENGINE_URL'] = 'http://localhost:8000'

# Create PredictionIO engine client.

client = PredictionIO::EngineClient.new(ENV['PIO_ENGINE_URL'])

```

### Send a prediction query to the engine and get the predicted result:

```ruby

# Get 5 recommendations for items similar to 10, 20, 30.

response = client.send_query(items: [10, 20, 30], num: 5)

```

## Mailing List

Please use the Apache mailing lists. Subscription instructions are

[here](http://predictionio.apache.org/support/).

## Issue Tracker

Use [the Apache JIRA](https://issues.apache.org/jira/browse/PIO), and file any

issues under the `Ruby SDK` component.

## Contributing

Please follow these

[instructions](http://predictionio.apache.org/community/contribute-code/).

## License

[Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0).