Code quality is an important factor to create robust software and grab contributors to free software projects. When it comes to code quality measurement, there are some tools available for the Python world like pep8 and pylint, but neither of them creates a full report with all possible quality measurements, nor perform analyses related to code quality history (available for all projects that use a version control system, like Git) and author influence on code quality.
Our work is centered in creating a tool that integrates all available measurements of Python code quality, with respect to time and authors, with rich visualizations and suggestions to improve the actual code quality. This tool will be available as free/libre software soon.
We have analyzed some of most used Python projects, including scientific packages such as numpy and scipy and, will be publishing a comparative study soon. We envision these quality reports being generated automatically for easy-of-use So one of the planned features is integration with GitHub and Jenkins, so that the tool can create reports as soon as a push is made to the repository.