---
id: pymatgen-core
version: "2026.8.13"
license: MIT
license_treatment: permissive
maintenance: active
---

# pymatgen-core — Python Materials Genomics is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project (https://materialsproject.org). This repository is for pymatgen-core, which implements the core data structures and algorithms.

License: permissive · Maintenance: active · Downloads: 701.9K/mo

## What it is and what it does

pymatgen-core is the foundational subset of the Pymatgen materials analysis library, split out to provide core data structures and I/O with minimal dependencies. It defines flexible object representations for elements, sites, molecules, and crystal structures, and handles input/output for many computational chemistry codes including VASP, ABINIT, Gaussian, and CIF files. It also includes core analysis tools such as symmetry detection, structure matching, bond valence calculations, and Ewald summation, plus electronic structure data classes for density of states and band structure.

The package is actively maintained as part of the Materials Project ecosystem and is used by thousands of researchers. It imports under the standard pymatgen namespace, so existing code continues to work. If you need higher-level analysis (phase diagrams, Pourbaix diagrams, diffusion analysis), install the full pymatgen package instead, which builds on top of pymatgen-core.

Use it for:

- Parse and manipulate crystal structure files from DFT calculations (VASP, ABINIT, Gaussian) for downstream analysis.
- Detect crystal symmetry and perform lattice/coordinate transformations for structure comparison and matching.
- Build materials science workflows that depend on standardized structure and electronic structure representations.
- Access foundational utilities used by the broader pymatgen ecosystem (atomate, FireWorks, pymatgen-analysis add-ons).
- Calculate bond valence sums and Ewald electrostatic energies for structure validation.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

pymatgen-core provides core data structures and I/O for materials science, including Element, Site, Molecule, and Structure classes with support for VASP, ABINIT, CIF, Gaussian, and other computational chemistry formats.

Yes, if you work with crystal structures or computational materials data. pymatgen-core is actively maintained, well-documented, and widely used in materials research. It has no known vulnerabilities and permissive licensing. The 18 runtime dependencies add medium install friction, but pre-built wheels for Python 3.11–3.14 across major platforms mitigate this. Install the full pymatgen package instead if you need higher-level analysis modules.

## Install

pip install pymatgen-core
uv add pymatgen-core
poetry add pymatgen-core

## Installing pymatgen-core

Before you install: Medium install friction due to 18 runtime dependencies including numpy, scipy, matplotlib, and pandas. Active maintenance with a release 1 day old and continuous integration via GitHub Actions. Supports Python 3.11–3.14 with pre-built wheels across macOS, Linux, and Windows.

License in practice: MIT license is permissive; you may use, modify, and distribute pymatgen-core freely in commercial and private projects, provided you retain the license notice.

Quickstart:

pip install pymatgen-core

from pymatgen.core import Structure
struct = Structure.from_file('structure.cif')

Requires Python 3.11 or later; some functionality (e.g., POTCAR generation) requires additional setup as documented in the pymatgen docs.

Verify before relying:

- Whether the 18 runtime dependencies can be installed without compilation issues on all supported platforms.
- Performance characteristics of coordinate manipulations and periodic boundary condition handling relative to alternatives.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: medium
- Maintenance: active
- Downloads: 701.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

crystal structure representation, materials science data structures, DFT code file I/O, symmetry and lattice operations, computational materials analysis, structure matching and analysis, electronic structure data classes, materials-science, crystallography, computational-chemistry

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