Lightweight framework for Online Analytical Processing (OLAP) and multidimensional analysis
Cubes - Online Analytical Processing Framework for Python
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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.
- 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 – HTTP server based on Flask Blueprint, can be [easily integrated](http://pythonhosted.org/cubes/deployment.html) into your application.
Latest release documentation: http://packages.python.org/cubes
Development documentation: http://cubes.databrewery.org/dev/doc
See examples directory in the source code repository for simple examples and use-cases.
See https://github.com/DataBrewery/cubes-examples for more complex examples.
For cubes models see https://github.com/DataBrewery/cubes-models
Source code is in a Git repository on GitHub.
git clone git://github.com/DataBrewery/cubes
After you’ve cloned, you might want to install all of the development dependencies.
pip install -e .[dev]
Build the documentation like so.
cd doc make help make html
Outputs will go in doc/_*.
Python >= 2.7 and Python >= 3.4.1
Most of the requirements are soft (optional) and need to be satisfied only if certain parts of cubes are being used.
If you have questions, problems or suggestions, you can send a message to the [Google group cubes-discuss](http://groups.google.com/group/cubes-discuss).
IRC channel #databrewery on server irc.freenode.net
Report bugs using [github issue tracking](https://github.com/DataBrewery/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 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.
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