Search Packages

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

pymatgen-core

Pymatgen Core Modules

shakenbreak

Defect structure-searching employing chemically-guided bond distortions

mat3ra-api-examples

Example usage of Exabyte.io platform through its RESTful API: programmatically create materials and modeling workflows, execute simulations on the cloud, analyze data and build machine learning models

mat-vis-client

Pure Python client for mat-vis PBR textures — HTTP range reads, zero deps

pyroll-core

PyRoll rolling simulation framework - core library.

bgolearn

[arXiv:2601.06820] Offical implement of Bgolearn

esse

JSON schemas and examples representing structural data, characteristic properties, modeling workflows and related data about materials standardizing the diverse landscape of information

atomai

Deep and Machine Learning for Microscopy

metallurgy

Calculates approximate properties of alloy compositions.

qmpy-rester

A toolkit for querying data in OQMD.

pyroll-report

PyRoll rolling simulation framework - core library.

qmflows

Automation of computations in quantum chemistry.

pypbr

PyPBR is a Python library for easy and fast manipulation of Physically Based Rendering (PBR) materials with PyTorch integration.

pyroll

Metapackage to replace old pyroll package.

pyroll-lendl-equivalent-method

Plugin for PyRolL providing the equivalent rectangle method by Lendl.

dfttopif

Library for parsing Density Functional Theory calculations

pysipfenn

Python python toolset for Structure-Informed Property and Feature Engineering with Neural Networks. It offers unique advantages through (1) effortless extensibility, (2) optimizations for ordered, dilute, and random atomic configurations, and (3) automated model tuning.

bgokit

[arXiv:2601.06820] Offical implement of Bgolearn

quasigraph

Graph-like chemical and geometric descriptor toolkit for studying materials with machine learning models.

muse-xtal

A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials

nano-qmflows

Derivative coupling calculation

pyroll-freiberg-flow-stress

Plugin for PyRoll providing Freiberg flow stress approach and material database.

pkynetics

A comprehensive library for thermal analysis kinetic methods