Bubbles is a Python ETL Framework and set of tools. It can be used for processing, auditing and inspecting data. Focus is on understandability and transparency of the process.
Project page: http://bubbles.databrewery.org
Blog: http://blog.databrewery.org
Bubbles is a Python framework for:
- ETL (extraction, transformation and loading)
- preparation of data for further analysis
- data probing – analysing properties of data, mostly categorical in nature
- data quality monitoring
- virtual data objects – abstraction of table-like structured datasets. Datasets are treated the same, no matter whether the source is a text file or a database table.
Requires at least Python 3.3.
To install Bubbles framework type:
pip install bubbles
To install Bubbles from sources, you can get it from Github:
https://github.com/Stiivi/bubbles
Introduction to bubbles (Slideshare presentation)
Operations (Scribd document)
Documentation can be found at: http://packages.python.org/bubbles
Project source repository is being hosted at Github: https://github.com/Stiivi/bubbles
git clone git://github.com/Stiivi/bubbles.git
If you have questions, problems or suggestions, you can send a message to the Google group or write to the author.
- Report issues here: https://github.com/Stiivi/bubbles/issues
- Google group: http://groups.google.com/group/databrewery
Stefan Urbanek [email protected]
Bubbles 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.