{ "info": { "author": "MIT Probabilistic Computing Project", "author_email": "bayesdb@mit.edu", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha" ], "description": "BayesDB\r\n=======\r\n\r\nBayesDB, a Bayesian database, lets users query the probable implications\r\nof their data as easily as a SQL database lets them query the data\r\nitself. Using the built-in Bayesian Query Language (BQL), users with no\r\nstatistics training can solve basic data science problems, such as\r\ndetecting predictive relationships between variables, inferring missing\r\nvalues, simulating probable observations, and identifying statistically\r\nsimilar database entries.\r\n\r\nBayesDB is suitable for analyzing complex, heterogeneous data tables\r\nwith up to tens of thousands of rows and hundreds of variables. No\r\npreprocessing or parameter adjustment is required, though experts can\r\noverride BayesDB\u2019s default assumptions when appropriate.\r\n\r\nBayesDB\u2019s inferences are based in part on CrossCat, a new, nonparametric\r\nBayesian machine learning method, that automatically estimates the full\r\njoint distribution behind arbitrary data tables.\r\n\r\nInstallation\r\n============\r\n\r\nDocker\r\n~~~~~~\r\n\r\nBayesDB can also be accessed via a community-contributed `Docker\r\ncontainer`_. Install instructions for Docker can be found `here`_.\r\n\r\nOnce docker has been installed and configured enter the following\r\ncommand in your terminal to download and install the Docker container\r\n(this will take a few minutes):\r\n\r\n::\r\n\r\n docker pull bayesdb/bayesdb\r\n\r\nTo run:\r\n\r\n::\r\n\r\n docker run -t -i bayesdb/bayesdb /bin/bash\r\n\r\nLocal\r\n~~~~~\r\n\r\nBayesDB depends on CrossCat, so first install CrossCat by following its\r\nlocal installation instructions\r\n`here `__.\r\n\r\nBayesDB can be installed locally with:\r\n\r\n::\r\n\r\n git clone https://github.com/mit-probabilistic-computing-project/BayesDB.git\r\n cd BayesDB\r\n sudo python setup.py install\r\n\r\nIf you have trouble with matplotlib, you should try switching to a\r\ndifferent backend. Open a python prompt ($ python):\r\n\r\n::\r\n\r\n import matplotlib\r\n matplotlib.matplotlib_fname()\r\n\r\nThen, edit the file at the path that was outputted, changing \u2018backend\u2019\r\nto another one of the available values, until the matplotlib errors go\r\naway. Good ones to try are GTKAgg and Agg.\r\n\r\nDocumentation\r\n=============\r\n\r\n`Website`_\r\n\r\n`Documentation`_\r\n\r\nExample\r\n=======\r\n\r\nrun\\_dha\\_example.py (`github`_) is a basic example of analysis using\r\nBayesDB. For a first test, run the following from inside the top level\r\nBayesDB dir\r\n\r\n::\r\n\r\n python examples/dha/run_dha_example.py\r\n\r\nLicense\r\n=======\r\n\r\n`Apache License, Version 2.0`_\r\n\r\n.. _Docker container: https://registry.hub.docker.com/u/bayesdb/bayesdb/\r\n.. _here: https://docs.docker.com/installation/#installation\r\n.. _Website: http://probcomp.csail.mit.edu/bayesdb\r\n.. _Documentation: http://probcomp.csail.mit.edu/bayesdb/docs/0.2/\r\n.. _github: https://github.com/mit-probabilistic-computing-project/BayesDB/blob/master/examples/dha/run_dha_example.py\r\n.. _Apache License, Version 2.0: https://github.com/mit-probabilistic-computing-project/bayesdb/blob/master/LICENSE", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://probcomp.csail.mit.edu/bayesdb/", "keywords": "", "license": "Apache License, Version 2.0", "maintainer": "", "maintainer_email": "", "name": "BayesDB", "package_url": "https://pypi.org/project/BayesDB/", "platform": "", "project_url": "https://pypi.org/project/BayesDB/", "project_urls": { "Homepage": "http://probcomp.csail.mit.edu/bayesdb/" }, "release_url": "https://pypi.org/project/BayesDB/0.2.0/", "requires_dist": null, "requires_python": null, "summary": "A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself.", "version": "0.2.0" }, "last_serial": 5591121, "releases": { "0.2.0": [ { "comment_text": "", "digests": { "md5": "235bb3f5d084c7980a91f66cfe60b28e", "sha256": "3039c02e8bbec63ee0ba84a7e42f2c440c2a9f51fd9f4e9ea660daf2c09d8417" }, "downloads": -1, "filename": "BayesDB-0.2.0-py2.7.egg", "has_sig": false, "md5_digest": "235bb3f5d084c7980a91f66cfe60b28e", "packagetype": "bdist_egg", "python_version": "2.7", "requires_python": null, "size": 283065, "upload_time": "2015-02-22T23:17:53", "url": "https://files.pythonhosted.org/packages/c4/92/ff525f8972c2e6a26d1f8b05297eabca89c7fc7f4201a4ab8c1939fc513c/BayesDB-0.2.0-py2.7.egg" }, { "comment_text": "", "digests": { "md5": "6d86728464f209c29d9df0943e2db513", "sha256": "1463259b167dadf37d56b6ef3ecbb7c6c6190714ad3786bb3259069ba9dcdab1" }, "downloads": -1, "filename": "BayesDB-0.2.0-py2-none-any.whl", "has_sig": false, "md5_digest": "6d86728464f209c29d9df0943e2db513", "packagetype": "bdist_wheel", "python_version": "2.7", "requires_python": null, "size": 131944, "upload_time": "2015-02-22T23:18:24", "url": "https://files.pythonhosted.org/packages/e6/8d/3f96a84bde558a0c7e2586b26d8bb5bccac4d0f3d46a93cc8247c8b0fb1b/BayesDB-0.2.0-py2-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7f7e238c61c209421edd0b02b3c85b97", "sha256": "c72e92c29b52d2d9666c60650afb5cb19700ce6db72c93d58f79a64f38c6c524" }, "downloads": -1, "filename": "BayesDB-0.2.0.tar.gz", "has_sig": false, "md5_digest": "7f7e238c61c209421edd0b02b3c85b97", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 110674, "upload_time": "2015-02-22T23:17:23", "url": "https://files.pythonhosted.org/packages/cf/03/6f9835ed644e53f79c0238f04d757c640407a87b94067caffdee6a5c10cb/BayesDB-0.2.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "235bb3f5d084c7980a91f66cfe60b28e", "sha256": "3039c02e8bbec63ee0ba84a7e42f2c440c2a9f51fd9f4e9ea660daf2c09d8417" }, "downloads": -1, "filename": "BayesDB-0.2.0-py2.7.egg", "has_sig": false, "md5_digest": "235bb3f5d084c7980a91f66cfe60b28e", "packagetype": "bdist_egg", "python_version": "2.7", "requires_python": null, "size": 283065, "upload_time": "2015-02-22T23:17:53", "url": "https://files.pythonhosted.org/packages/c4/92/ff525f8972c2e6a26d1f8b05297eabca89c7fc7f4201a4ab8c1939fc513c/BayesDB-0.2.0-py2.7.egg" }, { "comment_text": "", "digests": { "md5": "6d86728464f209c29d9df0943e2db513", "sha256": "1463259b167dadf37d56b6ef3ecbb7c6c6190714ad3786bb3259069ba9dcdab1" }, "downloads": -1, "filename": "BayesDB-0.2.0-py2-none-any.whl", "has_sig": false, "md5_digest": "6d86728464f209c29d9df0943e2db513", "packagetype": "bdist_wheel", "python_version": "2.7", "requires_python": null, "size": 131944, "upload_time": "2015-02-22T23:18:24", "url": "https://files.pythonhosted.org/packages/e6/8d/3f96a84bde558a0c7e2586b26d8bb5bccac4d0f3d46a93cc8247c8b0fb1b/BayesDB-0.2.0-py2-none-any.whl" }, { "comment_text": "", "digests": { "md5": "7f7e238c61c209421edd0b02b3c85b97", "sha256": "c72e92c29b52d2d9666c60650afb5cb19700ce6db72c93d58f79a64f38c6c524" }, "downloads": -1, "filename": "BayesDB-0.2.0.tar.gz", "has_sig": false, "md5_digest": "7f7e238c61c209421edd0b02b3c85b97", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 110674, "upload_time": "2015-02-22T23:17:23", "url": "https://files.pythonhosted.org/packages/cf/03/6f9835ed644e53f79c0238f04d757c640407a87b94067caffdee6a5c10cb/BayesDB-0.2.0.tar.gz" } ] }