pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis, primarily used for high-throughput computational materials science. It provides core object representations for crystal structures, molecules, and computational outputs (VASP, Q-Chem, Gaussian, etc.), and extends into analysis modules for phase diagrams, battery electrodes, coordination environments, magnetism, elasticity, surface science, diffraction, and spectroscopy. The library powers the Materials Project database and includes CLI tools for structure manipulation, POTCAR generation, and plotting. It features extensive use of MSONable serialization, abstract base classes, and a correction scheme pattern for DFT energy adjustments. While heavily integrated with the Materials Project ecosystem, its modular design allows reuse of individual analysis components in other materials research pipelines.
VASPy is a pure Python library for manipulating and analyzing VASP (Vienna Ab initio Simulation Package) input and output files. It provides object-oriented parsers for common VASP formats including POSCAR, CONTCAR, XDATCAR, OUTCAR, OSZICAR, INCAR, DOS, ELFCAR, CHGCAR, and also supports Materials Studio formats (XSD, ARC, XTD). The library exposes high-level classes like PosCar, OutCar, DosX, and InCar that encapsulate file parsing, coordinate transformations, and data extraction, enabling users to programmatically read, modify, and visualize simulation results. It also includes a set of command-line scripts for common tasks such as creating VASP inputs, extracting forces, computing zero-point energies, and converting between file formats. The architecture is modular, with separate modules for atomic coordinates, electronic structure, iterative outputs, and Material Studio interoperability, all built on a shared base class and utility functions. Visualization is a key feature, with matplotlib and PyVista backends for plotting DOS, charge densities, and trajectories. The library is designed for computational materials science researchers and DFT practitioners who need to automate post-processing and workflow tasks around VASP calculations.