pymatgen
Python Materials Genomics is a robust materials analysis code that defines core object representations for structures
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later.
- Some functionality (e.g., POTCAR generation) requires additional setup beyond the base install.
- Low install friction with a single runtime dependency (pymatgen-core).
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for both academic and commercial projects. No copyleft obligations.
last release 2026-05-04 (102 days) · last repo commit 2026-08-13 · 1,942 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 929,373 downloads/mo, #4,705 on PyPI
Alternatives
Verify before relying
pip install pymatgen
from pymatgen.core import Structure
struct = Structure.from_file('structure.cif')- 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
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 on this page. Verify before relying on it.
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
pymatgen on PyPI
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.
Requires Python 3.11 or later. Some functionality (e.g., POTCAR generation) requires additional setup beyond the base install.
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')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 the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepymatgen-core |
| Maintenance | Actively maintained 102 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 929,373 / month, #4,705 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: ChemistryTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: PhysicsTopic :: Software Development :: Libraries :: Python Modules |
Evidence: pymatgen-2026.5.4-py3-none-any.whl
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See also pymatgen-core · mp-api · pymatgen-io-validation · emmet-core · atomate2 · vasprun-xml · PyCifRW · dpdata · pyxtal · chgnet