Cubes is a light-weight Python framework and set of tools for Online Analytical Processing (OLAP), multidimensional analysis and browsing of aggregated data.
Focus on data analysis, in human way
Purpose is to provide a framework for giving analyst or any application end-user understandable and natural way of presenting the multidimensional data. One of the main features is the logical model, which serves as abstraction over physical data to provide end-user layer.
Features:
- OLAP and aggregated browsing (default backend is for relational databse - ROLAP)
- multidimensional analysis
- logical view of analysed data - how analysts look at data, how they think of data, not not how the data are physically implemented in the data stores
- hierarchical dimensions (attributes that have hierarchical dependencies, such as category-subcategory or country-region)
- localizable metadata and data
- OLAP server (WSGI HTTP server with JSON API based on Wergzeug)
Latest release documentation: http://packages.python.org/cubes
Development documentation: http://cubes.databrewery.org/dev/doc
See examples directory for simple examples and use-cases. Also see:
https://github.com/stiivi/cubes-examples
for more complex examples.
Github source repository: https://github.com/Stiivi/cubes
Developed using python 2.7.
Most of the requirements are soft (optional) and need to be satisfied only if certain parts of cubes are being used.
- SQLAlchemy from http://www.sqlalchemy.org/ version >= 0.7.4 - for SQL backend
- Werkzeug from http://werkzeug.pocoo.org/ for Slicer server
- Jinja2 from http://jinja.pocoo.org/docs/ for HTML presenters
- PyMongo for mongo and mongo2 backend
- pytz for mongo2 backend
If you have questions, problems or suggestions, you can send a message to the Google group or write to the author.
- Google group: http://groups.google.com/group/cubes-discuss
- IRC channel #databrewery on server irc.freenode.net
Report bugs using github issue tracking: https://github.com/Stiivi/cubes/issues
If you are browsing the code and you find something that:
- is over-complicated or not obvious
- is redundant
- can be done in better Python-way
... please let it be known.
Cubes is written and maintained by Stefan Urbanek (@Stiivi on Twitter) stefan.urbanek@gmail.com and various contributors. See AUTHORS file for more information.
Cubes is licensed under MIT license with following addition:
If your version of the Software supports interaction with it remotely
through a computer network, the above copyright notice and this permission
notice shall be accessible to all users.
Simply said, that if you use it as part of software as a service (SaaS) you have to provide the copyright notice in an about, legal info, credits or some similar kind of page or info box.
For full license see the LICENSE file.