{ "info": { "author": "Artem Golubin", "author_email": "me@rushter.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5" ], "description": "=====\nheamy\n=====\n\n.. image:: https://img.shields.io/pypi/v/heamy.svg\n :target: https://pypi.python.org/pypi/heamy\n\n.. image:: https://img.shields.io/travis/rushter/heamy.svg\n :target: https://travis-ci.org/rushter/heamy\n\n.. image:: https://coveralls.io/repos/github/rushter/heamy/badge.svg?branch=master\n :target: https://coveralls.io/github/rushter/heamy?branch=master\n\nA set of useful tools for competitive data science.\n\n\nInstallation\n------------\n\nTo install Heamy, simply:\n\n.. code:: bash\n\n $ pip install -U heamy\n\n\nFeatures\n--------\n* Automatic caching (data preprocessing, predictions from models)\n* Ensemble learning (stacking, blending, weighted average, etc.).\n\n\nDocumentation\n-------------\n\n* Documentation: http://heamy.readthedocs.io/en/latest/ \n* Examples: https://github.com/rushter/heamy/tree/master/examples\n\n\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/rushter/heamy", "keywords": "heamy", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "heamy", "package_url": "https://pypi.org/project/heamy/", "platform": "", "project_url": "https://pypi.org/project/heamy/", "project_urls": { "Homepage": "https://github.com/rushter/heamy" }, "release_url": "https://pypi.org/project/heamy/0.0.7/", "requires_dist": null, "requires_python": "", "summary": "A set of useful tools for competitive data science.", "version": "0.0.7" }, "last_serial": 2603194, "releases": { "0.0.6": [ { "comment_text": "", "digests": { "md5": "1e7cf094aa9f051801935019de6039d3", "sha256": "f1db9b9f162564e24e1fdcd9470c94c7e340dc21705309f0da96666d89140365" }, "downloads": -1, "filename": "heamy-0.0.6.tar.gz", "has_sig": false, "md5_digest": "1e7cf094aa9f051801935019de6039d3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 33324, "upload_time": "2016-08-16T17:21:34", "url": "https://files.pythonhosted.org/packages/56/28/45cf3be2d21c1a38e4f00ce396ae9b801fb364f730809461e8daf3c0b1c7/heamy-0.0.6.tar.gz" } ], "0.0.7": [ { "comment_text": "", "digests": { "md5": "5842993afb4fe736bfd8c0eda60d6167", "sha256": "bfbdf60e088ff73d8e83ec8ebda9fc2f5343037cbf2018ef7abbd5a93478b6a7" }, "downloads": -1, "filename": "heamy-0.0.7.tar.gz", "has_sig": false, "md5_digest": "5842993afb4fe736bfd8c0eda60d6167", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 30546, "upload_time": "2017-01-28T03:08:34", "url": "https://files.pythonhosted.org/packages/20/32/2f3e1efa38a8e34f790d90b6d49ef06ab812181ae896c50e89b8750fa5a0/heamy-0.0.7.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "5842993afb4fe736bfd8c0eda60d6167", "sha256": "bfbdf60e088ff73d8e83ec8ebda9fc2f5343037cbf2018ef7abbd5a93478b6a7" }, "downloads": -1, "filename": "heamy-0.0.7.tar.gz", "has_sig": false, "md5_digest": "5842993afb4fe736bfd8c0eda60d6167", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 30546, "upload_time": "2017-01-28T03:08:34", "url": "https://files.pythonhosted.org/packages/20/32/2f3e1efa38a8e34f790d90b6d49ef06ab812181ae896c50e89b8750fa5a0/heamy-0.0.7.tar.gz" } ] }