We have added Python support to our Transformation engine. Python is a handy and versatile programming language. It also has a lot of useful libraries. Particularly interesting may be the SciPy stack. All Python transformations run in our public docker image with Python 3.5.1 and have an 8GB memory limit.
The interface is highly similar to the existing R transformations. You can start by setting input and output mapping in the UI. The tables from input mapping will be created as CSV files in in/tables directory. Result CSV files from out/tables directory will be uploaded to your project Storage. All your python code has to do is read the CSV file, do some magic and then write a CSV file.
If you need some packages from PyPI, you can list them in the packages section of the UI. By the way, the SciPy stack is installed by default.
If you are interested in writing Python transformations, we have an introduction article in documentation with some examples that show how to work with the input and output files.