{ "info": { "author": "Pablo Torres", "author_email": "pablo.torres@insight-centre.org", "bugtrack_url": null, "classifiers": [ "Programming Language :: Python :: 3.6" ], "description": "# Entity Search\n\nThis is an entity search framework based on stationary distributions on random walks with diffusion kernel.\n\n## Development\nYou will need to include the configuration for this repo to your git local configuration.\n\n``\ngit config --local include.path ../.gitconfig\n``\nThis step removes the result section in the json document for each execution in the notebooks.\n\n\n## Testing\nIn oder to execute the tests, you will need the development dataset. This dataset can be created from the following [repo](https://gitlab.insight-centre.org/ptorres/entity-search-development-data). Once the dataset is created, you need to registered in the configuration file. To simplify this step, just use the incorporated subcommnad `config` where you can defined the development data folder.\n\nFor instance, if the dataset is installed in this directory `/data/dev-es`, then you need to execute config as follows:\n\n``\npython setup.py config --config-datafolder=/data/dev-es\n``\n\nThis command will create a configuration file in `etc/` with the proper setup.\n\nOnce the configuration file is created, you can execute the tests, as shown below:\n\n``\npython setup.py test\n``\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/ptorrest/entity-search", "keywords": "", "license": "GNU", "maintainer": "", "maintainer_email": "", "name": "entity-search", "package_url": "https://pypi.org/project/entity-search/", "platform": "", "project_url": "https://pypi.org/project/entity-search/", "project_urls": { "Homepage": "https://github.com/ptorrest/entity-search" }, "release_url": "https://pypi.org/project/entity-search/0.0.4/", "requires_dist": [ "colorlog", "gensim", "krovetz", "matplotlib", "nltk", "numba", "numpy", "pandas", "scipy", "sparse" ], "requires_python": "", "summary": "Entity Search", "version": "0.0.4" }, "last_serial": 5512537, "releases": { "0.0.4": [ { "comment_text": "", "digests": { "md5": "4d33abab112f6d92e0e3a91098be09c9", "sha256": "b96a9a8465ebd9d23bae16f5f67621316871eb4dabbcfe869bfe0442be61c509" }, "downloads": -1, "filename": "entity_search-0.0.4-py3-none-any.whl", "has_sig": false, "md5_digest": "4d33abab112f6d92e0e3a91098be09c9", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 74767, "upload_time": "2019-07-10T15:02:44", "url": "https://files.pythonhosted.org/packages/25/a9/a4572f9545c745852dcf282268050ac8d3763b1c95b688af2503479dd8a0/entity_search-0.0.4-py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "4d33abab112f6d92e0e3a91098be09c9", "sha256": "b96a9a8465ebd9d23bae16f5f67621316871eb4dabbcfe869bfe0442be61c509" }, "downloads": -1, "filename": "entity_search-0.0.4-py3-none-any.whl", "has_sig": false, "md5_digest": "4d33abab112f6d92e0e3a91098be09c9", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 74767, "upload_time": "2019-07-10T15:02:44", "url": "https://files.pythonhosted.org/packages/25/a9/a4572f9545c745852dcf282268050ac8d3763b1c95b688af2503479dd8a0/entity_search-0.0.4-py3-none-any.whl" } ] }