{"id":13869926,"url":"https://github.com/hatchet/hatchet","last_synced_at":"2025-07-15T18:32:45.143Z","repository":{"id":37018549,"uuid":"106039141","full_name":"hatchet/hatchet","owner":"hatchet","description":"Analyze graph/hierarchical performance data using pandas dataframes","archived":false,"fork":false,"pushed_at":"2024-10-21T11:46:02.000Z","size":25965,"stargazers_count":107,"open_issues_count":26,"forks_count":37,"subscribers_count":9,"default_branch":"develop","last_synced_at":"2024-11-22T04:20:41.008Z","etag":null,"topics":["comparative-analysis","data-analytics","graphs","hierarchical-data","hpc","pandas","performance","performance-analysis","python","trees"],"latest_commit_sha":null,"homepage":"https://hatchet.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/hatchet.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","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}},"created_at":"2017-10-06T18:47:34.000Z","updated_at":"2024-11-14T06:40:46.000Z","dependencies_parsed_at":"2023-09-23T22:33:44.266Z","dependency_job_id":"ba71fd2a-221b-4577-aaf7-987ab0f3c046","html_url":"https://github.com/hatchet/hatchet","commit_stats":{"total_commits":479,"total_committers":22,"mean_commits":"21.772727272727273","dds":0.7369519832985386,"last_synced_commit":"9e1c6ecb1077d7598097c18ef7e3414d60b6e88e"},"previous_names":[],"tags_count":9,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hatchet%2Fhatchet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hatchet%2Fhatchet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hatchet%2Fhatchet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hatchet%2Fhatchet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hatchet","download_url":"https://codeload.github.com/hatchet/hatchet/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":226063111,"owners_count":17567950,"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","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":["comparative-analysis","data-analytics","graphs","hierarchical-data","hpc","pandas","performance","performance-analysis","python","trees"],"created_at":"2024-08-05T20:01:22.177Z","updated_at":"2024-11-23T15:32:19.436Z","avatar_url":"https://github.com/hatchet.png","language":"Python","readme":"# \u003cimg src=\"https://raw.githubusercontent.com/hatchet/hatchet/develop/logo.png\" height=\"120\" valign=\"middle\" alt=\"hatchet\"/\u003e\n\n[![Build Status](https://github.com/hatchet/hatchet/actions/workflows/unit-tests.yaml/badge.svg)](https://github.com/hatchet/hatchet/actions)\n[![Read the Docs](http://readthedocs.org/projects/hatchet/badge/?version=latest)](http://hatchet.readthedocs.io)\n[![codecov](https://codecov.io/gh/hatchet/hatchet/branch/develop/graph/badge.svg)](https://codecov.io/gh/hatchet/hatchet)\n[![Code Style: Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![Join slack](https://img.shields.io/badge/slack-hatchet--users-blue)](https://join.slack.com/t/hatchet-users/shared_invite/zt-twjzzdav-p1s7NUEJzBoejYdOAgeddg)\n\nHatchet is a Python-based library that allows [Pandas](https://pandas.pydata.org) dataframes to be indexed by structured tree and graph data. It is intended for analyzing performance data that has a hierarchy (for example, serial or parallel profiles that represent calling context trees, call graphs, nested regions’ timers, etc.). Hatchet implements various operations to analyze a single hierarchical data set or compare multiple data sets, and its API facilitates analyzing such data programmatically.\n\nTo use hatchet, install it with pip:\n\n```\n$ pip install hatchet\n```\n\nOr, if you want to develop with this repo directly, run the install script from\nthe root directory, which will build the cython modules and add the cloned\ndirectory to your `PYTHONPATH`:\n\n```\n$ source install.sh\n```\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://raw.githubusercontent.com/hatchet/hatchet/develop/screenshot.png\" width=800\u003e\n\u003c/p\u003e\n\n\n### Documentation\n\nSee the [Getting Started](https://hatchet.readthedocs.io/en/latest/getting_started.html) page for basic examples and usage. Full documentation is available in the [User Guide](https://hatchet.readthedocs.io/en/latest/user_guide.html).\n\nExamples of performance analysis using hatchet are available [here](https://hatchet.readthedocs.io/en/latest/analysis_examples.html).\n\n### Contributing\n\nHatchet is an open source project. We welcome contributions via pull requests,\nand questions, feature requests, or bug reports via issues.\n\nYou can connect with the hatchet community on\n[slack](https://join.slack.com/t/hatchet-users/shared_invite/zt-twjzzdav-p1s7NUEJzBoejYdOAgeddg).\nYou can also reach the hatchet developers by email at:\n[hatchet-help@listserv.umd.edu](mailto:hatchet-help@listserv.umd.edu).\n\n### Authors\n\nMany thanks go to Hatchet's\n[contributors](https://github.com/hatchet/hatchet/graphs/contributors).\n\nHatchet was created by Abhinav Bhatele, bhatele@cs.umd.edu.\n\n\n### Citing Hatchet\n\nIf you are referencing Hatchet in a publication, please cite the\nfollowing [paper](http://www.cs.umd.edu/~bhatele/pubs/pdf/2019/sc2019.pdf):\n\n * Abhinav Bhatele, Stephanie Brink, and Todd Gamblin. Hatchet: Pruning\n   the Overgrowth in Parallel Profiles. In Proceedings of the International\n   Conference for High Performance Computing, Networking, Storage and Analysis\n   (SC '19). ACM, New York, NY, USA. [DOI](\n   http://doi.acm.org/10.1145/3295500.3356219)\n\n### License\n\n\nHatchet is distributed under the terms of the MIT license.\n\nAll contributions must be made under the MIT license.  Copyrights in the\nHatchet project are retained by contributors.  No copyright assignment is\nrequired to contribute to Hatchet.\n\nSee [LICENSE](https://github.com/hatchet/hatchet/blob/develop/LICENSE) and\n[NOTICE](https://github.com/hatchet/hatchet/blob/develop/NOTICE) for details.\n\nSPDX-License-Identifier: MIT\n\nLLNL-CODE-741008\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhatchet%2Fhatchet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhatchet%2Fhatchet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhatchet%2Fhatchet/lists"}