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Cubes is a light-weight Python framework and set of tools for development ofreporting and analytical applications, Online Analytical Processing (OLAP),multidimensional analysis and browsing of aggregated data. It is part ofData Brewery.
Getting Started¶
- Introduction
- Installation
- Tutorial
Data Modeling¶
- Logical Model and Metadata
- Schemas and Models
- Localization
Aggregation, Slicing and Dicing¶
- Slicing and Dicing
Analytical Workspace¶
- Analytical Workspace
- Authorization and Authentication
- Configuration
Slicer Server and Tool¶
- OLAP Server
- Server Deployment
- slicer - Command Line Tool
Backends¶
- SQL Backend
- MongoDB Backend
- Google Analytics Backend
- Mixpanel Backend
- Slicer Server
Recipes¶
- Recipes
Extension Development¶
- Backends
- Model Providers
- Authenticators and Authorizers
Developer’s Reference¶
- Model Reference
- Model Providers Reference
- Aggregation Browser Reference
- Formatters Reference
- Aggregation Browsing Backends
- Authentication and Authorization
Quick Notes 1.0.1 File
Release Notes¶
- Cubes Release Notes
Contact and Getting Help¶
Quick Notes 2013
If you have questions, problems or suggestions, you can send a message toGoogle group or write to the author (Stefan Urbanek).
Report bugs in github issues tracking
There is an IRC channel #databrewery on server irc.freenode.net.
License¶
Cubes is licensed under MIT license with small addition:
Quick Notes 2019
Simply said, that if you use it as part of software as a service (SaaS) youhave to provide the copyright notice in an about, legal info, credits or somesimilar kind of page or info box.