{"id":27267842,"url":"https://github.com/hachmannlab/chemml","last_synced_at":"2025-10-21T19:59:52.511Z","repository":{"id":30970148,"uuid":"113404097","full_name":"hachmannlab/chemml","owner":"hachmannlab","description":"ChemML is a machine learning and informatics program suite for the chemical and materials sciences.","archived":false,"fork":false,"pushed_at":"2025-08-20T15:31:42.000Z","size":98622,"stargazers_count":170,"open_issues_count":7,"forks_count":32,"subscribers_count":12,"default_branch":"master","last_synced_at":"2025-10-21T19:59:22.751Z","etag":null,"topics":["data-science","deep-learning","drug-discovery","machine-learning","materials-informatics","quantum-mechanics"],"latest_commit_sha":null,"homepage":"https://hachmannlab.github.io/chemml","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hachmannlab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2017-12-07T04:48:18.000Z","updated_at":"2025-10-21T13:31:28.000Z","dependencies_parsed_at":"2023-02-16T21:45:25.741Z","dependency_job_id":"b46de93f-d105-439c-8d67-573bef752ddb","html_url":"https://github.com/hachmannlab/chemml","commit_stats":{"total_commits":797,"total_committers":16,"mean_commits":49.8125,"dds":"0.13174404015056462","last_synced_commit":"f6a259b1a195fbc1fe214c955cd9601aa5f3237f"},"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"purl":"pkg:github/hachmannlab/chemml","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hachmannlab%2Fchemml","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hachmannlab%2Fchemml/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hachmannlab%2Fchemml/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hachmannlab%2Fchemml/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hachmannlab","download_url":"https://codeload.github.com/hachmannlab/chemml/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hachmannlab%2Fchemml/sbom","scorecard":{"id":452052,"data":{"date":"2025-08-11","repo":{"name":"github.com/hachmannlab/chemml","commit":"b06e981a454d82435794752910dffaf5c35a86c4"},"scorecard":{"version":"v5.2.1-40-gf6ed084d","commit":"f6ed084d17c9236477efd66e5b258b9d4cc7b389"},"score":3.3,"checks":[{"name":"Packaging","score":-1,"reason":"packaging workflow not detected","details":["Warn: no GitHub/GitLab publishing workflow detected."],"documentation":{"short":"Determines if the project is published as a package that others can easily download, install, easily update, and uninstall.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#packaging"}},{"name":"Maintained","score":0,"reason":"0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0","details":null,"documentation":{"short":"Determines if the project is \"actively maintained\".","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#maintained"}},{"name":"Token-Permissions","score":-1,"reason":"No tokens found","details":null,"documentation":{"short":"Determines if the project's workflows follow the principle of least privilege.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#token-permissions"}},{"name":"Dangerous-Workflow","score":-1,"reason":"no workflows found","details":null,"documentation":{"short":"Determines if the project's GitHub Action workflows avoid dangerous patterns.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#dangerous-workflow"}},{"name":"Code-Review","score":2,"reason":"Found 2/7 approved changesets -- score normalized to 2","details":null,"documentation":{"short":"Determines if the project requires human code review before pull requests (aka merge requests) are merged.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#code-review"}},{"name":"CII-Best-Practices","score":0,"reason":"no effort to earn an OpenSSF best practices badge detected","details":null,"documentation":{"short":"Determines if the project has an OpenSSF (formerly CII) Best Practices Badge.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#cii-best-practices"}},{"name":"Binary-Artifacts","score":10,"reason":"no binaries found in the repo","details":null,"documentation":{"short":"Determines if the project has generated executable (binary) artifacts in the source repository.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#binary-artifacts"}},{"name":"Security-Policy","score":0,"reason":"security policy file not detected","details":["Warn: no security policy file detected","Warn: no security file to analyze","Warn: no security file to analyze","Warn: no security file to analyze"],"documentation":{"short":"Determines if the project has published a security policy.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#security-policy"}},{"name":"Vulnerabilities","score":10,"reason":"0 existing vulnerabilities detected","details":null,"documentation":{"short":"Determines if the project has open, known unfixed vulnerabilities.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#vulnerabilities"}},{"name":"License","score":10,"reason":"license file detected","details":["Info: project has a license file: LICENSE:0","Info: FSF or OSI recognized license: BSD 3-Clause \"New\" or \"Revised\" License: LICENSE:0"],"documentation":{"short":"Determines if the project has defined a license.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#license"}},{"name":"Fuzzing","score":0,"reason":"project is not fuzzed","details":["Warn: no fuzzer integrations found"],"documentation":{"short":"Determines if the project uses fuzzing.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#fuzzing"}},{"name":"Signed-Releases","score":0,"reason":"Project has not signed or included provenance with any releases.","details":["Warn: release artifact v0.5.2 not signed: https://api.github.com/repos/hachmannlab/chemml/releases/18400647","Warn: release artifact v0.5.2 does not have provenance: https://api.github.com/repos/hachmannlab/chemml/releases/18400647"],"documentation":{"short":"Determines if the project cryptographically signs release artifacts.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#signed-releases"}},{"name":"Branch-Protection","score":-1,"reason":"internal error: error during branchesHandler.setup: internal error: githubv4.Query: Resource not accessible by integration","details":null,"documentation":{"short":"Determines if the default and release branches are protected with GitHub's branch protection settings.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#branch-protection"}},{"name":"Pinned-Dependencies","score":-1,"reason":"no dependencies found","details":null,"documentation":{"short":"Determines if the project has declared and pinned the dependencies of its build process.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#pinned-dependencies"}},{"name":"SAST","score":0,"reason":"SAST tool is not run on all commits -- score normalized to 0","details":["Warn: 0 commits out of 29 are checked with a SAST tool"],"documentation":{"short":"Determines if the project uses static code analysis.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#sast"}}]},"last_synced_at":"2025-08-19T08:26:05.053Z","repository_id":30970148,"created_at":"2025-08-19T08:26:05.053Z","updated_at":"2025-08-19T08:26:05.053Z"},"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":280325298,"owners_count":26311419,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-21T02:00:06.614Z","response_time":58,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","deep-learning","drug-discovery","machine-learning","materials-informatics","quantum-mechanics"],"created_at":"2025-04-11T10:01:30.628Z","updated_at":"2025-10-21T19:59:52.506Z","avatar_url":"https://github.com/hachmannlab.png","language":"Python","funding_links":[],"categories":["Representation Engineering","Libraries"],"sub_categories":["Machine Learning"],"readme":"[![codecov](https://codecov.io/gh/hachmannlab/chemml/branch/master/graph/badge.svg)](https://codecov.io/gh/hachmannlab/chemml)\n[![version status](http://img.shields.io/pypi/v/chemml.svg?style=flat)](https://pypi.python.org/pypi/chemml)\n[![license](http://img.shields.io/badge/license-BSD-blue.svg?style=flat)](https://github.com/hachmannlab/chemml/blob/master/LICENSE)\n\n\n# ChemML\nChemML is a machine learning and informatics program suite for the analysis, mining, and modeling of chemical and materials data.\nPlease check the [ChemML website](https://hachmannlab.github.io/chemml) for more information.\n\n   - ChemML documentation: https://hachmannlab.github.io/chemml\n\n\n\n\u003cp align=\"center\"\u003e\n  \u003cimg align=\"middle\" src=\"./docs/images/logo.png\" alt=\"ChemML\" width=\"400px\" class=\"center\"\u003e\n \u003c/p\u003e\n\n\n## Code Design:\nChemML is developed in the Python 3 programming language and makes use of a host of data analysis and ML libraries(accessible through the Anaconda distribution), as well as domain-specific libraries. \nThe development follows a strictly modular and object-oriented design to make the overall code as flexible and versatile as possible.\n\nThe format of library is similar to the well known libraries like Scikit-learn. \n\n\n## Latest Version:\n   - to find out about the latest version and release history, click [here](https://pypi.org/project/chemml/#history)\n\n## Installation and Dependencies:\nWe strongly recommend you to install ChemML in an Anaconda environment. The instructions to create the environment, install ChemML’s dependencies, and subsequently install ChemML using the Python Package Index (PyPI) via pip are as follows:\n\n    conda create --name chemml_env python=3.12\n    source activate chemml_env\n    conda install -c conda-forge openbabel nb_conda_kernels python-graphviz\n    pip install chemml\n\nHere is a list of external libraries that will be installed with chemml:\n   - numpy\n   - pandas\n   - tensorflow\n   - rdkit\n   - scikit-learn\n   - matplotlib\n   - seaborn\n   - lxml\n   - openpyxl\n   - ipywidgets\n   - shap\n   - lime\n\nWe also require the user to install PyTorch depending on their operating system and GPU configuration, which can be done by following the wizard on this page:\n\nhttps://pytorch.org/get-started/locally/\n\nNote: The PyTorch CUDA 12.4 install has been tested with CUDA 12.5 and works fine, but future CUDA versions may not be compatible. If any issues arise from CUDA compatibility, it is recommended to follow the instructions on the PyTorch website to compile from source.\n\n## Citation:\nPlease cite the use of ChemML as:\n\n    Main citation:\n\n    @article{haghighatlari2019chemml,\n        title        = {{ChemML}: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data},\n        author       = {Haghighatlari, Mojtaba and Vishwakarma, Gaurav and Altarawy, Doaa and Subramanian, Ramachandran and Kota, Bhargava U and Sonpal, Aditya and Setlur, Srirangaraj and Hachmann, Johannes},\n        year         = 2020,\n        journal      = {Wiley Interdisciplinary Reviews: Computational Molecular Science},\n        publisher    = {Wiley Online Library},\n        volume       = 10,\n        doi          = {https://doi.org/10.1002/wcms.1458},\n        pages        = {e1458},\n    }\n\n    \n    Other references:\n\n    @article{chemml_review2019,\n    author = {Haghighatlari, Mojtaba and Hachmann, Johannes},\n    doi = {https://doi.org/10.1016/j.coche.2019.02.009},\n    issn = {2211-3398},\n    journal = {Current Opinion in Chemical Engineering},\n    month = {jan},\n    pages = {51--57},\n    title = {Advances of machine learning in molecular modeling and simulation},\n    volume = {23},\n    year = {2019}\n    }\n\n    @article{Hachmann2018,\n    author = {Hachmann, Johannes and Afzal, Mohammad Atif Faiz and Haghighatlari, Mojtaba and Pal, Yudhajit},\n    doi = {10.1080/08927022.2018.1471692},\n    issn = {10290435},\n    journal = {Molecular Simulation},\n    number = {11},\n    pages = {921--929},\n    title = {Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space},\n    volume = {44},\n    year = {2018}\n    }\n\n    @article{vishwakarma2019towards,\n    title={Towards autonomous machine learning in chemistry via evolutionary algorithms},\n    author={Vishwakarma, Gaurav and Haghighatlari, Mojtaba and Hachmann, Johannes},\n    journal={ChemRxiv preprint},\n    year={2019}\n    }\n\n## License:\nChemML is copyright (C) 2014-2022 Johannes Hachmann and Mojtaba Haghighatlari, Aditya Sonpal, Gaurav Vishwakarma and Aatish Pradhan all rights reserved.\nChemML is distributed under 3-Clause BSD License (https://opensource.org/licenses/BSD-3-Clause).\n\n## About us:\n\n### Maintainers:\n    - Johannes Hachmann, hachmann@buffalo.edu\n    - Mojtaba Haghighatlari\n    - Aditya Sonpal, adityaso@buffalo.edu\n    - Aatish Pradhan, aatishpr@buffalo.edu\n    - Nitin Murthy, nitinmad@buffalo.edu\n    University at Buffalo - The State University of New York (UB)\n\n### Contributors:\n    - Doaa Altarawy (MolSSI): scientific advice and software mentor \n    - Aditya Sonpal (UB): graph convolution NNs, XAI\n    - Aatish Pradhan (UB): autoML and Jupyter GUI developer\n    - Gaurav Vishwakarma (UB): automated model optimization\n    - Ramachandran Subramanian (UB): Magpie descriptor library port\n    - Bhargava Urala Kota (UB): library database\n    - Srirangaraj Setlur (UB): scientific advice\n    - Venugopal Govindaraju (UB): scientific advice\n    - Krishna Rajan (UB): scientific advice\n    \n\n    - We encourage any contributions and feedback. Feel free to fork and make pull-request to the \"development\" branch.\n\n### Acknowledgements:\n    - ChemML is based upon work supported by the U.S. National Science Foundation under grant #OAC-1751161 and in part by #OAC-1640867.\n    - ChemML was also supported by start-up funds provided by UB's School of Engineering and Applied Science and UB's Department of Chemical and Biological Engineering, the New York State Center of Excellence in Materials Informatics through seed grant #1140384-8-75163, and the U.S. Department of Energy under grant #DE-SC0017193.\n    - Mojtaba Haghighatlari received 2018 Phase-I and 2019 Phase-II Software Fellowships by the Molecular Sciences Software Institute (MolSSI) for his work on ChemML.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhachmannlab%2Fchemml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhachmannlab%2Fchemml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhachmannlab%2Fchemml/lists"}