{"id":38508125,"url":"https://github.com/lincc-frameworks/hyrax","last_synced_at":"2026-05-18T23:01:35.258Z","repository":{"id":251286071,"uuid":"836953183","full_name":"lincc-frameworks/hyrax","owner":"lincc-frameworks","description":"Hyrax - A low-code framework for rapid experimentation with ML \u0026 unsupervised discovery in astronomy","archived":false,"fork":false,"pushed_at":"2026-04-22T19:43:36.000Z","size":26806,"stargazers_count":30,"open_issues_count":86,"forks_count":5,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-04-22T20:10:04.431Z","etag":null,"topics":["machine-learning","mlops"],"latest_commit_sha":null,"homepage":"https://hyrax.readthedocs.io/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lincc-frameworks.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2024-08-01T22:51:04.000Z","updated_at":"2026-04-16T21:31:45.000Z","dependencies_parsed_at":"2024-08-02T00:45:54.492Z","dependency_job_id":"ff54953c-8178-48b8-b2a0-79f4ca58e7fc","html_url":"https://github.com/lincc-frameworks/hyrax","commit_stats":null,"previous_names":["lincc-frameworks/fibad","lincc-frameworks/hyrax"],"tags_count":25,"template":false,"template_full_name":null,"purl":"pkg:github/lincc-frameworks/hyrax","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lincc-frameworks%2Fhyrax","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lincc-frameworks%2Fhyrax/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lincc-frameworks%2Fhyrax/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lincc-frameworks%2Fhyrax/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lincc-frameworks","download_url":"https://codeload.github.com/lincc-frameworks/hyrax/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lincc-frameworks%2Fhyrax/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32203362,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-23T20:19:26.138Z","status":"ssl_error","status_checked_at":"2026-04-23T20:19:23.520Z","response_time":53,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["machine-learning","mlops"],"created_at":"2026-01-17T06:17:57.323Z","updated_at":"2026-04-24T00:01:19.148Z","avatar_url":"https://github.com/lincc-frameworks.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Hyrax\n### A Low-Code Framework for Rapid Experimentation with ML \u0026 Unsupervised Discovery in Astronomy\n[![Template](https://img.shields.io/badge/Template-LINCC%20Frameworks%20Python%20Project%20Template-brightgreen)](https://lincc-ppt.readthedocs.io/en/latest/)\n[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/lincc-frameworks/hyrax/smoke-test.yml)](https://github.com/lincc-frameworks/hyrax/actions/workflows/smoke-test.yml)\n[![codecov](https://codecov.io/gh/lincc-frameworks/hyrax/branch/main/graph/badge.svg)](https://codecov.io/gh/lincc-frameworks/hyrax)\n[![Read the Docs](https://img.shields.io/readthedocs/hyrax)](https://hyrax.readthedocs.io/en/latest)\n[![PyPI](https://img.shields.io/pypi/v/hyrax?color=blue\u0026logo=pypi\u0026logoColor=white)](https://pypi.org/project/hyrax/)\n\nHyrax is an extensible platform that handles much of the boilerplate code that is often required for a machine learning project in astronomy. Hyrax users are able to focus on the science work of model development and results analysis instead of infrastructure.\n\nHyrax is not tied to a specific model or data modality but rather is intended to encourage an ecosystem of models and data for rapid experimentation.\nIf the algorithm you want can be implemented in PyTorch, then Hyrax can likely reduce the boilerplate code required for a reproducible project.\n\n\n## Getting Started \nHyrax can be installed via pip:\n\n```\n\u003e\u003e pip install hyrax\n```\n\nHyrax is officially supported and tested with Python versions 3.11, 3.12, and 3.13.\nOther versions may work but are not guaranteed to be compatible.\n\nCheck out [Getting started](https://hyrax.readthedocs.io/en/latest/getting_started.html) and\n[Common workflows](https://hyrax.readthedocs.io/en/latest/common_workflows.html) in the documentation for usage examples.\n\n\n## Existing Hyrax Projects\nHyrax has been developed to support single and multimodal data for use with both supervised and unsupervised models.\nSome examples include: \n\n- Image-based unsupervised discovery in Rubin-LSST and HSC. (A. Ghosh, J.  Chatchadanoraset, D. Miura)\n- Spectra-based supervised clustering to study supernova Ia spectral diversity. (L. Cunningham, M. Dai)\n- Image-based supervised small body classification. (M. West++)\n- Multimodal time-series classification for ZTF alert follow-up. (A. Sasli, F. Fontinele-Nunes++)\n- Image-based unsupervised discovery of cluster-scale gravitationally lensed arcs. (G. Khullar++)\n- Searches for semi-resolved galaxies in HSC and LSST (P. Ferguson ++)\n\n## Collaborations and Contributions\nIf you are an astronomer interested in using Hyrax, please get in touch with us!\nWe are especially interested to hear about applications that Hyrax doesn't currently support.\n\nHyrax is open source and under active development.\nIf you would like to contribute, please contact us. We would be happy to work with you.\n\n\n## Acknowledgements\nThis project started as a collaboration between different units within the\n[LSST Discovery Alliance](https://lsstdiscoveryalliance.org/) --\nthe [LINCC Frameworks Team](https://lsstdiscoveryalliance.org/programs/lincc-frameworks/)\nand LSST-DA Catalyst Fellow, [Aritra Ghosh](https://ghosharitra.com/).\n\nThis project is supported by Schmidt Sciences and the John Templeton Foundation\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flincc-frameworks%2Fhyrax","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flincc-frameworks%2Fhyrax","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flincc-frameworks%2Fhyrax/lists"}