Expanding PyProcar for new features, maintainability, and reliability

This paper presents a comprehensive update to PyProcar, a versatile Python package for analyzing and visualizing density functional theory (DFT) calculations in materials science. The latest version introduces a modularized codebase, a centralized example data repository, and a robust testing framework, offering a more reliable, maintainable, and scalable platform. Expanded support for various DFT codes broadens its applicability across research environments. Enhanced documentation and an example gallery make the package more accessible to new and experienced users. Incorporating advanced features such as band unfolding, noncollinear calculations, and derivative calculations of band energies enriches its analytic capabilities, providing deeper insights into electronic and structural properties. The package also incorporates PyPoscar, a specialized toolkit for manipulating POSCAR files, broadening its utility in computational materials science. These advancements solidify PyProcar's position as a comprehensive and highly adaptable tool, effectively serving the evolving needs of the materials science community.