{"id":18985060,"url":"https://github.com/dobraczka/forayer","last_synced_at":"2025-06-25T20:04:36.905Z","repository":{"id":38192138,"uuid":"391938153","full_name":"dobraczka/forayer","owner":"dobraczka","description":"forayer is a library of first aid utilities for knowledge graph exploration with an entity centric approach.","archived":false,"fork":false,"pushed_at":"2024-03-05T15:10:39.000Z","size":1454,"stargazers_count":6,"open_issues_count":3,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-29T12:51:24.212Z","etag":null,"topics":["data-integration","entity-resolution","knowledge-graph"],"latest_commit_sha":null,"homepage":"https://forayer.readthedocs.io/en/latest/","language":"Jupyter Notebook","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/dobraczka.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":"2021-08-02T12:21:26.000Z","updated_at":"2022-05-23T12:33:34.000Z","dependencies_parsed_at":"2024-03-05T16:43:21.566Z","dependency_job_id":null,"html_url":"https://github.com/dobraczka/forayer","commit_stats":{"total_commits":101,"total_committers":1,"mean_commits":101.0,"dds":0.0,"last_synced_commit":"cab23052ffeeb2a6f79bf02c9cf3a9063784ff7f"},"previous_names":[],"tags_count":12,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2Fforayer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2Fforayer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2Fforayer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2Fforayer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dobraczka","download_url":"https://codeload.github.com/dobraczka/forayer/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249250814,"owners_count":21237961,"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":["data-integration","entity-resolution","knowledge-graph"],"created_at":"2024-11-08T16:24:31.072Z","updated_at":"2025-04-19T20:26:33.581Z","avatar_url":"https://github.com/dobraczka.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://github.com/dobraczka/forayer/raw/main/docs/forayerlogo.png\" alt=\"forayer logo\", width=200/\u003e\n\u003c/p\u003e\n\n\u003ch2 align=\"center\"\u003e forayer\u003c/h2\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://github.com/dobraczka/forayer/actions/workflows/main.yml\"\u003e\u003cimg alt=\"Tests\" src=\"https://github.com/dobraczka/forayer/actions/workflows/tests.yml/badge.svg?branch=main\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/dobraczka/forayer/actions/workflows/quality.yml\"\u003e\u003cimg alt=\"Linting\" src=\"https://github.com/dobraczka/forayer/actions/workflows/quality.yml/badge.svg?branch=main\"\u003e\u003c/a\u003e\n\u003ca href=\"https://pypi.org/project/forayer\"/\u003e\u003cimg alt=\"Stable python versions\" src=\"https://img.shields.io/pypi/pyversions/forayer\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/dobraczka/forayer/blob/main/LICENSE\"\u003e\u003cimg alt=\"MIT License\" src=\"https://img.shields.io/badge/license-MIT-blue\"\u003e\u003c/a\u003e\n\u003ca href=\"https://github.com/psf/black\"\u003e\u003cimg alt=\"Code style: black\" src=\"https://img.shields.io/badge/code%20style-black-000000.svg\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\nAbout\n=====\nForayer is a library of **f**irst aid utilities for kn**o**wledge g**r**aph explor**a**tion with an entit**y** c**e**ntric app**r**oach.\nIt is intended to make data integration of knowledge graphs easier. With entities as first class citizens forayer is a toolset to aid in knowledge graph exploration for data integration and specifically entity resolution.\n\nYou can easily load pre-existing entity resolution tasks:\n\n```python\n  \u003e\u003e\u003e from forayer.datasets import OpenEADataset\n  \u003e\u003e\u003e ds = OpenEADataset(ds_pair=\"D_W\",size=\"15K\",version=1)\n  \u003e\u003e\u003e ds.er_task\n  ERTask({DBpedia: (# entities: 15000, # entities_with_rel: 15000, # rel: 13359,\n  # entities_with_attributes: 13782, # attributes: 13782, # attr_values: 24995),\n  Wikidata: (# entities: 15000, # entities_with_rel: 15000, # rel: 13554,\n  # entities_with_attributes: 14376, # attributes: 14376, # attr_values: 114107)},\n  ClusterHelper(# elements:30000, # clusters:15000))\n```\n\nThis entity resolution task holds 2 knowledge graphs and a cluster of known matches. You can search in knowledge graphs:\n\n```python\n  \u003e\u003e\u003e ds.er_task[\"DBpedia\"].search(\"Dorothea\")\n  KG(entities={'http://dbpedia.org/resource/E801200': \n  {'http://dbpedia.org/ontology/activeYearsStartYear': '\"1948\"^^\u003chttp://www.w3.org/2001/XMLSchema#gYear\u003e',\n  'http://dbpedia.org/ontology/activeYearsEndYear': '\"2008\"^^\u003chttp://www.w3.org/2001/XMLSchema#gYear\u003e',\n  'http://dbpedia.org/ontology/birthName': 'Dorothea Carothers Allen',\n  'http://dbpedia.org/ontology/alias': 'Allen, Dorothea Carothers',\n  'http://dbpedia.org/ontology/birthYear': '\"1923\"^^\u003chttp://www.w3.org/2001/XMLSchema#gYear\u003e',\n  'http://purl.org/dc/elements/1.1/description': 'Film editor',\n  'http://dbpedia.org/ontology/birthDate': '\"1923-12-03\"^^\u003chttp://www.w3.org/2001/XMLSchema#date\u003e',\n  'http://dbpedia.org/ontology/deathDate': '\"2010-04-17\"^^\u003chttp://www.w3.org/2001/XMLSchema#date\u003e', \n  'http://dbpedia.org/ontology/deathYear': '\"2010\"^^\u003chttp://www.w3.org/2001/XMLSchema#gYear\u003e'}}, rel={}, name=DBpedia)\n```\n\nDecide to work with a smaller snippet of the resolution task:\n\n```python\n  \u003e\u003e\u003e ert_sample = ds.er_task.sample(100)\n  \u003e\u003e\u003e ert_sample\n  ERTask({DBpedia: (# entities: 100, # entities_with_rel: 6, # rel: 4,\n  # entities_with_attributes: 99, # attributes: 99, # attr_values: 274),\n  Wikidata: (# entities: 100, # entities_with_rel: 4, # rel: 4,\n  # entities_with_attributes: 100, # attributes: 100, # attr_values: 797)},\n  ClusterHelper(# elements:200, # clusters:100))\n```\n\nAnd much more can be found in the [user guide](https://forayer.readthedocs.io/en/latest/source/user_guide.html).\n\nInstallation\n============\n\nYou can install forayer via pip:\n\n```bash\n  pip install forayer\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdobraczka%2Fforayer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdobraczka%2Fforayer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdobraczka%2Fforayer/lists"}