{ "info": { "author": "Savio Abuga", "author_email": "savioabuga@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4" ], "description": "PII Analyzer\n===========\nAnalyzing PII in datasets\n\n\nClassifying datasets and resources into \u2018PII\u2019 and \u2018Not PII\u2019.\n===========\n\nThe task requires creation of a tool that will detect whether new datasets uploaded to HDX contain any personally\nidentifiable information - data that can be used on its own or with other information to identify, contact, or\nlocate a single person, or to identify an individual in context.\n\nThe tool should then alert the HDX data manager whether any such data sets have been uploaded\nand also alert the data owner about this.\n\nMy Solution\n----\n\nI decided to use the following tools for the above task:\n\n1. `Pandas `_: for reading the data files into python and manipulating the datasets.\n\n2. `Common Regular expressions `_: for extracting some types of 'PII' such as email addresses, phone numbers, street addresses,\n credit card numbers,\n\n3. `Stanford Named Entity Tagger `_: for extracting the locations, organizations and peoples names.\n\n\nThe analyzer opens the provided file, analyses it and returns a summary of the types of data that are in the provided dataset.\nWith this information the data manager can easily classify the data.\n\n\nUsage\n-----\n\n\n>>> from piianalyzer.analyzer import PiiAnalyzer\n>>> filepath = '/path/or/url/to/your/file.csv'\n>>> piianalyzer = PiiAnalyzer(filepath)\n>>> analysis = piianalyzer.analysis()\n\n\n\nInstallation\n------------\n\n\n\nRequirements\n^^^^^^^^^^^^\n\nRequires the Stanford Named Entity Recognizer. It can be downloaded here: http://nlp.stanford.edu/software/CRF-NER.shtml\n\n\nCompatibility\n-------------\n\nLicence\n-------\n\nTODO\n----\n* Reading other file types such as excel, text, html etc\n*\n\nAuthors\n-------\n\n`piianalyzer` was written by `Savio Abuga `_.", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/github/piianalyzer", "keywords": null, "license": "UNKNOWN", "maintainer": null, "maintainer_email": null, "name": "piianalyzer", "package_url": "https://pypi.org/project/piianalyzer/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/piianalyzer/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/github/piianalyzer" }, "release_url": "https://pypi.org/project/piianalyzer/0.1.0/", "requires_dist": null, "requires_python": null, "summary": "Analyzing PII in datasets", "version": "0.1.0" }, "last_serial": 1702607, "releases": { "0.1.0": [ { "comment_text": "", "digests": { "md5": "c4cd96b34488df9442abb2011ed20ea7", "sha256": "8806e66c72ddc2f4ac9ece06d597565d1c6c6bba00f00c3fe9bc5a3e81ad0d9d" }, "downloads": -1, "filename": "piianalyzer-0.1.0.tar.gz", "has_sig": false, "md5_digest": "c4cd96b34488df9442abb2011ed20ea7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2992, "upload_time": "2015-09-01T07:12:23", "url": "https://files.pythonhosted.org/packages/10/2d/13abe570f01549806885c20b1d32665bef7d448ee6e2fb1b945ad364bf23/piianalyzer-0.1.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "c4cd96b34488df9442abb2011ed20ea7", "sha256": "8806e66c72ddc2f4ac9ece06d597565d1c6c6bba00f00c3fe9bc5a3e81ad0d9d" }, "downloads": -1, "filename": "piianalyzer-0.1.0.tar.gz", "has_sig": false, "md5_digest": "c4cd96b34488df9442abb2011ed20ea7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2992, "upload_time": "2015-09-01T07:12:23", "url": "https://files.pythonhosted.org/packages/10/2d/13abe570f01549806885c20b1d32665bef7d448ee6e2fb1b945ad364bf23/piianalyzer-0.1.0.tar.gz" } ] }