SSEPython - Plugin for Qlik

About

Python Plugin to add Machine Learning capabilities in Qlik using SSE (Server Side Extension). Time series forecasting supports both script execution and expression capability calls.

Inprogress - (Email capability) for Prediction Summary.

Setup

Qlik Sense Desktop

1. Install Qlik Sense Desktop (June 2017 release or later).
2. Make sure you have Python 3.4 (or later) installed as well as the grpcio package.
3. Add SSEPlugin=SSEPython,localhost:50052 on a new line in your Settings.ini file located at C:\Users[user]\Documents\Qlik\Sense or C:\user[user]\AppData\Local\Programs\Qlik\Sense\Engine.
4. Copy the .qvf file from the selected example folder to C:\Users[user]\Documents\Qlik\Sense\Apps.
5. Run the corresponding SSEPython.py package.
6. Start Qlik Sense Desktop and open the app for the examples.

Qlik Sense Enterprise

1. Install Qlik Sense Enterprise (June 2017 release or later).
2. Make sure you have Python 3.4 (or later) installed as well as the grpcio package.
3. Add the SSE plugin settings in QMC under Analytic connections by inserting the following values: name:SSEPython, host: localhost, port:50052
4. Add the .qvf file from the selected example folder to QMC.
5. Run the corresponding SSEPython.py python package.
6. Start Qlik Sense Enterprise and open the app for the examples.

Output Samples

Capability Call from Qlik

Code Samples

Link to Plugin Code - SSEPython.py

Linear Regression

Time Series Forecasting Using Prophet

Time Series Forecasting Using Prophet - Multi Field Return

Plugin Function Declaration JSON

Qlik BundleRow Sample Data