{ "info": { "author": "Rajkumar", "author_email": "rajkumar.s@imaginea.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 2.7", "Topic :: Software Development :: Build Tools" ], "description": "CSV-anamoly-detector :\n\tA tool to detect anamolies in CSV files (especially large files)\n\nDescription of the tool :\n\n\tThis tool is handy if you are working with a large csv file wherein scanning each\n\tline for anamolies is a daunting task. Even if the file is received from a reliable\n\tsource it is always safe to verify the veracity of the file before proceeding further.\n\n\tEach column has a title, all of which will be mentioned in the very first line of any \n\tcsv file which we shall refer as \"HEADER\" throughout this page.\n\n\tThe tool takes a header-wise scanning approach.After scanning each Header, the dominant\n\tdatatype is identified and any another datatype is assumed (\"we are not concluding \n\tbecause the final decision rests with the user\") to be defective. \n\n\tDatatypes described in the tool are so exhaustive that even what plain eye may miss \n\twill be detected by the tool.\n\tEx.R0HAN is different from ROHAN (notice zero instead of 'o' in the first case.)\n\n\nCommand line execution:\n\n\tLet us assume that we have a file named mock.csv & our source code is in automation.py\n\t\n\tTo view the headers of the file:\t\n\t\tpython automation.py columns --filename=mock.csv\n\n\tWe will be shown the following result:\n\t\t['id', 'first_name', 'last_name', 'email', 'country', 'ip_address']\n\twhere each element of the above array is a header\n\t\n\tTo find out the anamolies in each header (say email) :\n\t\tpython automation.py executeColumns --filename=mock.csv --columns=email\n\n\tUpon completion of the scanning process, you will see either of these two responses:\n\t1) This Column appears bug free.\n\t2) PLEASE OPEN improperData.txt (this file contains all the error prone entries)\n\n\tTo know the commands available:\n\t\tpython automation.py --help\n\n\tPlease \"avoid\" spacing in the following areas:\n\t\t--filename = mock.csv (will throw error)\n\t\t--filename= mock.csv (will throw error)\n\t\t--filename =mock.csv(will throw error)\n\t\t--filename=mock.csv (will give result)\n\n\t\tThe above set of rules also apply for --columns", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "github.com/raj040492/CSV-anomaly-detector", "keywords": "detect Anamolies in CSV files", "license": "MIT", "maintainer": null, "maintainer_email": null, "name": "CSV-anomaly-detector", "package_url": "https://pypi.org/project/CSV-anomaly-detector/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/CSV-anomaly-detector/", "project_urls": { "Download": "UNKNOWN", "Homepage": "github.com/raj040492/CSV-anomaly-detector" }, "release_url": "https://pypi.org/project/CSV-anomaly-detector/1.2.17/", "requires_dist": null, "requires_python": null, "summary": "A Python tool to detect Anamolies", "version": "1.2.17" }, "last_serial": 1535297, "releases": { "1.2.10": [], "1.2.11": [ { "comment_text": "", "digests": { "md5": "e4261fde81593eb0d50a28185753be9b", "sha256": "d627197ac28873e03a95e9f6e16f845337af62598c7c4883d76340ecc1634391" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.11.tar.gz", "has_sig": false, "md5_digest": "e4261fde81593eb0d50a28185753be9b", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2622, "upload_time": "2015-05-06T06:56:12", "url": "https://files.pythonhosted.org/packages/ef/08/257a0179e1e9271948818ea6e12fc962b8a0b74e1178fb12cbfdc755576d/CSV-anomaly-detector-1.2.11.tar.gz" } ], "1.2.12": [ { "comment_text": "", "digests": { "md5": "d3c65afd84cf792652ea1e3d9eceb7b2", "sha256": "42628b23682b4932b6a11026c5a951895724ac08f29c25f8b8a6ebd2a1c48c5c" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.12.tar.gz", "has_sig": false, "md5_digest": "d3c65afd84cf792652ea1e3d9eceb7b2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2623, "upload_time": "2015-05-06T06:59:28", "url": "https://files.pythonhosted.org/packages/a2/ae/85bca1373aa7cdf0a0bd9d4d2ed50e826e5ef11eaac1077937ee18123ed9/CSV-anomaly-detector-1.2.12.tar.gz" } ], "1.2.13": [ { "comment_text": "", "digests": { "md5": "7ebf747a042050401f06f0fea31f2c68", "sha256": "2392b5ec59c16b25d0ae88c0dd02cdc07f7bde87e2af512d7ef5af7415ed3dec" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.13.tar.gz", "has_sig": false, "md5_digest": "7ebf747a042050401f06f0fea31f2c68", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2554, "upload_time": "2015-05-06T07:17:25", "url": "https://files.pythonhosted.org/packages/f8/eb/453c6958b2664bd0de33e0c8a06127b46dbad8d3e6fdddaaf1b24cac237d/CSV-anomaly-detector-1.2.13.tar.gz" } ], "1.2.14": [ { "comment_text": "", "digests": { "md5": "9442d0e0e077579e59e8fb1672a290e3", "sha256": "e5f1da55495b7dce9cacd5be73a543b1140bca0fb3781cfc33d43933466380e3" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.14.tar.gz", "has_sig": false, "md5_digest": "9442d0e0e077579e59e8fb1672a290e3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2454, "upload_time": "2015-05-06T07:20:41", "url": "https://files.pythonhosted.org/packages/d2/fa/71f7aa3a1b62a5f3c0f903006f573e486ba78d2a9c6faa96793f695cf9f1/CSV-anomaly-detector-1.2.14.tar.gz" } ], "1.2.15": [ { "comment_text": "", "digests": { "md5": "59d42ab1f9d250f0b088f51d4c7b3521", "sha256": "17b4d4168ee6f9e90f060922a7ea2e1bb70782f3a205f037bdd8b0a3e8f16d39" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.15.tar.gz", "has_sig": false, "md5_digest": "59d42ab1f9d250f0b088f51d4c7b3521", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2458, "upload_time": "2015-05-06T07:38:03", "url": "https://files.pythonhosted.org/packages/81/9b/453531c29a30efc05472cf397e35dceec9b60be7c503093a82b4e7a26f3d/CSV-anomaly-detector-1.2.15.tar.gz" } ], "1.2.16": [ { "comment_text": "", "digests": { "md5": "22910346b38cfccba9c10e42928376a2", "sha256": "0ca62b0ea5b7530cff8fc7136ee444ecc9b2a8d0eef4412a9e62eb0eb992ea8d" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.16.tar.gz", "has_sig": false, "md5_digest": "22910346b38cfccba9c10e42928376a2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 313681, "upload_time": "2015-05-06T07:46:43", "url": "https://files.pythonhosted.org/packages/84/4b/af772562cc2a5e0a90b18b0b354cbe560a240cc3ee78716291f6623709eb/CSV-anomaly-detector-1.2.16.tar.gz" } ], "1.2.17": [ { "comment_text": "", "digests": { "md5": "4d2abfe5fe1d2f1f94689c1757866a6a", "sha256": "c75f87fb0f2b6d3b7b568f31c6e806bf3277d1f5a4e6fa197bdfe3f2ca968024" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.17.tar.gz", "has_sig": false, "md5_digest": "4d2abfe5fe1d2f1f94689c1757866a6a", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 313986, "upload_time": "2015-05-06T09:16:59", "url": "https://files.pythonhosted.org/packages/0c/c8/f54793628ad6c06793e4e3611d33188b961b7c6d4d0fd7335a60ffe69236/CSV-anomaly-detector-1.2.17.tar.gz" } ], "1.2.7": [ { "comment_text": "", "digests": { "md5": "ff7fda8f8e1fc897d4f2c92125cbd6af", "sha256": "70c92b143f0f94bf5b3a7f939ead12511bd4057e80511e3bfecb548fff9a697c" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.7.tar.gz", "has_sig": false, "md5_digest": "ff7fda8f8e1fc897d4f2c92125cbd6af", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 308289, "upload_time": "2015-05-04T06:43:24", "url": "https://files.pythonhosted.org/packages/3f/44/cfd3547ff5b3e81a6a9c39327d0e0f2bf9ed65deb840ba15afaa9ff04c2f/CSV-anomaly-detector-1.2.7.tar.gz" } ], "1.2.8": [ { "comment_text": "", "digests": { "md5": "22947c59792762fafe1aeadb6342b7e9", "sha256": "be55b3ad55f440cb7f64d7900414c911cfdc663dc25bd8e4c41cf89d83ef0844" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.8.tar.gz", "has_sig": false, "md5_digest": "22947c59792762fafe1aeadb6342b7e9", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 310356, "upload_time": "2015-05-04T11:53:59", "url": "https://files.pythonhosted.org/packages/e9/ad/780cb80e04b30bd85fa71d5bc952cf7ae3fe473fd1e6b9a58cc28fbccc55/CSV-anomaly-detector-1.2.8.tar.gz" } ], "1.2.9": [ { "comment_text": "", "digests": { "md5": "10e2d2969a78dbed2502064bb4f8d93d", "sha256": "4edb0fd998051490721d5bfe44b62d625bde9b3b595d4b1f883fbad2c4cc8317" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.9.tar.gz", "has_sig": false, "md5_digest": "10e2d2969a78dbed2502064bb4f8d93d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 311543, "upload_time": "2015-05-05T15:33:10", "url": "https://files.pythonhosted.org/packages/2b/0c/53d7ca1566301b28716c04791286722b1072a2070edae40054798b79c7ac/CSV-anomaly-detector-1.2.9.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "4d2abfe5fe1d2f1f94689c1757866a6a", "sha256": "c75f87fb0f2b6d3b7b568f31c6e806bf3277d1f5a4e6fa197bdfe3f2ca968024" }, "downloads": -1, "filename": "CSV-anomaly-detector-1.2.17.tar.gz", "has_sig": false, "md5_digest": "4d2abfe5fe1d2f1f94689c1757866a6a", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 313986, "upload_time": "2015-05-06T09:16:59", "url": "https://files.pythonhosted.org/packages/0c/c8/f54793628ad6c06793e4e3611d33188b961b7c6d4d0fd7335a60ffe69236/CSV-anomaly-detector-1.2.17.tar.gz" } ] }