{"library":"jarvis-tools","type":"library","category":null,"description":"jarvis-tools is an open-source Python package for data-driven atomistic materials design, developed by NIST. It provides modules for crystal structure analysis, high-throughput DFT workflows, machine learning descriptors, and access to the JARVIS-DFT and JARVIS-FF databases. Current version is 2026.4.2, released monthly (around end of each month).","language":"python","status":"active","version":"2026.4.2","tags":["materials-science","dft","machine-learning","crystal-structure","high-throughput","materials-design","jarvis"],"install":[{"cmd":"pip install jarvis-tools","imports":["from jarvis.core.atoms import Atoms","from jarvis.core.graphs import Graph","from jarvis.core.utils import get_fractional_coordinates"]},{"cmd":"pip install git+https://github.com/atomgptlab/jarvis-tools.git","imports":[]}],"homepage":"https://jarvis.nist.gov","github":"https://github.com/atomgptlab/jarvis-tools","docs":null,"changelog":null,"pypi":"https://pypi.org/project/jarvis-tools/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":25,"avg_install_s":14.6,"avg_import_s":4.65,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/jarvis-tools/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}