Ways of Cubes Deployment data brewery Stefan Urbanek ■ @Stiivi ■ [email protected] ■ February 2014 

Simple Slicer Public store Slicer server HTML & JS Application HTTP request JSON reply model Run Slicer server Provide desired output 1 3 2 Query server from JavaScript GET /cubes ! GET /cube/{CUBE}/model ! GET /cube/{CUBE}/aggregate?… > slicer serve slicer.ini 

WSGI Slicer Public store WSGI HTML & JS Application HTTP request JSON reply Slicer Flask App model Same usage as stand-alone Slicer server 

Slicer as a Service Internal Public store Slicer server Web Application PHP, RoR, Django HTTP request JSON reply model HTML GET /cube/{CUBE}/aggregate?… Run a Slicer server instance Provide desired output 1 3 4 Query with HTTP requests 2 Get the model using HTTP GET /cubes ! GET /cube/{CUBE}/model 

Python Application from cubes import Workspace ! workspace = Workspace(“slicer.ini”) browser = workspace.browser(…) result = browser.aggregate(…) Public store JSON reply Cubes Python API Django, Flask, … HTML model Python Web App handles the request Python Web App provides output 1 2 3 Application uses the Cubes directly: 

Flask Blueprint* * http://flask.pocoo.org/docs/blueprints/ Public store Flask HTML Slicer Blueprint model from flask import Flask from cubes.server import slicer ! app = Flask(__name__) ! app.register_blueprint(slicer, url_prefix=“/slicer", config="slicer.ini") Register Slicer as part of Flask app Provide Slicer API as additional
 “raw analytical data” API do whatever you want in Flask 1 2 

Summary 

Slicer server (stand-alone) HTTP JSON Flask Slicer Blueprint HTTP JSON Python App ? ? Cubes Python API WSGI + Slicer server HTTP JSON separate integrated 

Links Cubes Home cubes.databrewery.org github github.com/Stiivi/cubes Development Documentation cubes.databrewery.org/dev/doc/ for github master HEAD