The assessment toolkit provides a set of tools implemented in python helping build a graph from software system artifacts such as source code structures, dependencies, issues, commit history, and others, and analyze the software system for its quality and technical debt based on this graph.
The framework is a research tool and is not of stable production quality yet.
To setup saapy based environment please follow steps similar to below. The saapy library is not on pypi yet hence a somewhat unconventional process.
- Make sure you have python 3.5+ installed and use it as a default python environment in the next steps.
- Create the projects root directory:
mkdir ~/Projects && cd ~/Projects
- Clone saapy from GitHub. If you have it already cloned, you can skip this step.
git clone https://github.com/ashapochka/saapy.git
- Create python3 virtual environment to isolate saapy specific installation.
pyvenv saapyenv
- Activate the environment and run further steps in it (check on terminal cmd prefix)
source saapyenv/bin/activate - Install numpy explicitly otherwise pymc installation fails later on.
pip install numpy
- Install saapy third party dependencies in a batch (can take a couple of minutes).
pip install -r saapy/requirements.txt
- Install saapy itself in the development mode.
pip install -e ./saapy
First, make sure you executed the steps in the Installation section. To prepare the assessment environment for a specific project follow the steps:
- Create a project working directory.
mkdir ~/Projects/prj1 && cd ~/Projects/prj1
- Activate the environment if inactive.
source ../saapyenv/bin/activate - Add any files required for processing into the working directory.
- Run Jupyter notebook server to write and execute assessment notebooks
based on the saapy.
jupyter-notebook --working-dir=`pwd`
(c) Andriy Shapochka