The Python Materials Genomics (pymatgen) library is a robust, open-source Python library for materials analysis. It provides a set of tools for high-throughput computational materials science, including initial setup for calculations and post-calculation analysis to derive useful material properties. The library defines core Python objects for materials data representation, provides well-tested structure and thermodynamic analysis tools, and establishes an open platform for collaborative development of sophisticated analyses of materials data from first principles calculations and experiments. It also offers convenient tools to obtain materials data via the Materials Project's RESTful API. The pymatgen library is used in the Materials Project for structure generation, manipulation, and thermodynamic analysis. It is compatible with Python 2.7 and is designed to be a standalone library. The latest stable version (2.2.4) is available via the Python Package Index, while the "bleeding edge" version is available on GitHub. The library includes several packages for data assimilation, analysis, and visualization. It supports high-throughput compound generation and electronic structure run generation via the alchemy package. The phasediagram package provides tools for generating and plotting phase diagrams. The borg package automatically traverses directories to search for calculations and assimilate data. The library also includes tools for calculating reactions and phase diagrams. It supports the Materials Project's RESTful API, allowing users to access materials data via HTTP. The matproj package provides convenient tools for users to obtain pymatgen objects and data via the Materials API. An example application is the phase stability analysis of the recently synthesized material Li4SnS4. Using pymatgen's analysis tools and interface to the Materials API, the phase and electrochemical stability of Li4SnS4 can be analyzed with minimal computational resources. This demonstrates the power of the pymatgen library in enabling efficient materials analysis and data processing. The open-source nature of the library and the availability of Materials Project data are expected to spur the development of more property apps that use computed data, ultimately enhancing the impact of computational modeling on the materials community.The Python Materials Genomics (pymatgen) library is a robust, open-source Python library for materials analysis. It provides a set of tools for high-throughput computational materials science, including initial setup for calculations and post-calculation analysis to derive useful material properties. The library defines core Python objects for materials data representation, provides well-tested structure and thermodynamic analysis tools, and establishes an open platform for collaborative development of sophisticated analyses of materials data from first principles calculations and experiments. It also offers convenient tools to obtain materials data via the Materials Project's RESTful API. The pymatgen library is used in the Materials Project for structure generation, manipulation, and thermodynamic analysis. It is compatible with Python 2.7 and is designed to be a standalone library. The latest stable version (2.2.4) is available via the Python Package Index, while the "bleeding edge" version is available on GitHub. The library includes several packages for data assimilation, analysis, and visualization. It supports high-throughput compound generation and electronic structure run generation via the alchemy package. The phasediagram package provides tools for generating and plotting phase diagrams. The borg package automatically traverses directories to search for calculations and assimilate data. The library also includes tools for calculating reactions and phase diagrams. It supports the Materials Project's RESTful API, allowing users to access materials data via HTTP. The matproj package provides convenient tools for users to obtain pymatgen objects and data via the Materials API. An example application is the phase stability analysis of the recently synthesized material Li4SnS4. Using pymatgen's analysis tools and interface to the Materials API, the phase and electrochemical stability of Li4SnS4 can be analyzed with minimal computational resources. This demonstrates the power of the pymatgen library in enabling efficient materials analysis and data processing. The open-source nature of the library and the availability of Materials Project data are expected to spur the development of more property apps that use computed data, ultimately enhancing the impact of computational modeling on the materials community.