---
id: pymatgen
version: "2026.5.4"
license: MIT
license_treatment: permissive
maintenance: active
---

# pymatgen — Python Materials Genomics is a robust materials analysis code that defines core object representations for structures

License: permissive · Maintenance: active · Downloads: 929.4K/mo

## What it is and what it does

Pymatgen is a materials analysis library that provides object-oriented representations of crystalline structures, molecules, and sites, along with tools for reading and writing computational chemistry file formats (VASP, ABINIT, Gaussian, CIF, XYZ, and others). It is used by thousands of researchers and underpins the Materials Project, a large-scale materials database and analysis platform.

The library includes analysis capabilities for phase diagrams, Pourbaix diagrams, diffusion analysis, reaction pathways, and electronic structure properties like density of states and band structure. It integrates with the Materials Project REST API and is optimized for coordinate manipulations using NumPy and SciPy vectorization. The codebase is actively maintained by the Materialyze Lab, the ABINIT group, and other research teams, with continuous integration testing and a growing ecosystem of community add-ons.

Use it for:

- Parse and manipulate crystal structures from VASP, ABINIT, or Gaussian output files for post-processing analysis
- Generate phase diagrams and Pourbaix diagrams for thermodynamic stability assessment
- Analyze electronic structure data including band structures and density of states
- Query and download structures and properties from the Materials Project database
- Automate high-throughput computational materials workflows with standardized structure handling

## Worth the install?

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

Pymatgen provides Python classes and analysis tools for materials science workflows, including structure representation, file I/O for computational chemistry formats (VASP, ABINIT, Gaussian, CIF), phase diagrams, electronic structure analysis, and integration with the Materials Project REST API.

Yes. Pymatgen is a mature, actively maintained library with no known vulnerabilities, low install friction, and broad adoption in computational materials science. The MIT license imposes no restrictions. Install it if you work with crystal structures, computational chemistry outputs, or materials databases; skip it if your work does not involve materials analysis.

## Install

pip install pymatgen
uv add pymatgen
poetry add pymatgen

## Installing pymatgen

Before you install: Low install friction with a single runtime dependency (pymatgen-core). Active maintenance with last commit 2026-08-13 and continuous integration via GitHub Actions. Used by thousands of researchers and powers the Materials Project analysis pipeline.

License in practice: MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both academic and commercial projects. No copyleft obligations.

Quickstart:

pip install pymatgen

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 beyond the base install.

Verify before relying:

- Specific performance characteristics for large structure datasets or high-throughput workflows
- Completeness of Materials Project REST API integration and any rate-limiting behavior
- Availability and maturity of the add-on ecosystem mentioned in the description

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 929.4K/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

materials structure analysis python, VASP ABINIT file parsing, phase diagram generation, crystal structure manipulation, electronic structure DOS band structure, computational materials science, materials project integration, materials-science, computational-chemistry, crystal-structures

[View on SkillFed](https://skillfed.io/packages/pymatgen) · [View on PyPI](https://pypi.org/project/pymatgen/)