Evaluation of Python code quality using multiple source code analyzers

Abstract

Python has become one of the most popular programming languages in recent years, particularly in the fields of data analysis and scientific computing. To further improve code quality, this thesis proposes the development of a service tool that records the progress of GitHub projects and conducts a comprehensive multi-metric analysis of Python code. The static code analysis is performed using a variety of Python tools, and the thesis begins with a literature review that introduces the fundamental components of good code in Python. The tool's features are then presented, followed by a description of the analysis procedure and code examples. Two real-world GitHub projects from the domains of data analysis and image processing are examined, and the findings of the analyses are reported. This thesis emphasises the importance of code quality in software development and provides developers with a valuable tool for enhancing their code.