Interactive Code Quality Analysis for your Python project using DPy and Jupyter Notebook

High code quality ensures that software is maintainable as its codebases evolve through contributions from diverse developers. One effective way to maintain high code quality is to identify code smells, which are symptoms indicating deeper quality problems in your codebase.

In this notebook, I'll walk through the process of analyzing an open-source project interactively using DPy, our code smell detection tool designed for Python projects. We'll post-process the analysis results, creating insightful visualizations and interactive summaries that make the findings more accessible and actionable.

Let's explore how combining automated smell detection with interactive data analysis can give you valuable insights into your code quality.