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Orange

build: passing coverage: poor code quality: worse

Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. It can be used through a nice and intuitive user interface or, for more advanced users, as a module for the Python programming language.

This is an early development version of Orange 3. The current stable version 2.7 is available (binaries and sources).

Installing

This version of Orange requires Python 3.2 or newer. To build it, run::

pip install numpy
pip install -r requirements.txt
python setup.py develop

inside a virtual environment that uses Python 3.2.

Installation of SciPy and qt-graph-helpers is sometimes challenging because of their non-python dependencies that have to be installed manually. Detailed guides for some platforms can be found in the wiki.

Starting Orange Canvas

Orange Canvas requires PyQt, which is not pip-installable in Python 3. You have to download and install it system-wide. Make sure that the virtual environment for orange is created with --system-site-packages, so it will have access to the installed PyQt4.

To start Orange Canvas from the command line, run:

python3 -m Orange.canvas

Windows dev setup

Windows + GCC:

python setup.py build_ext -i --compile=mingw32

About

Orange 3 data mining suite: http://orange.biolab.si

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