{
    "info": {
        "author": "Jack Maney",
        "author_email": "jackmaney@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2 :: Only",
            "Topic :: Utilities"
        ],
        "description": "When importing CSV files to databases, I sometimes find it tedious to create the table in a database first. This is a very basic app (and a work in progress) that grabs the rows of a CSV file (sampling, if specified), uses the sample to guess at the data types of the columns, and uses these guesses to output a SQL `CREATE TABLE` statement. Think of it as a version of `CREATE TABLE some_table AS SELECT * FROM <some CSV file>`.\n\nFor the moment, this is aimed towards PostgreSQL (although that will change) and for now, a very limited number of data types will be supported, namely `text`, `boolean`, `smallint`, `int`, `bigint`, `numeric`, `date`, and `timestamp` (which are the types that I find myself using the most often).\n\nTo install, you can use pip:\n\n```\nsudo pip install csv-to-table\n```\n\nor you can grab the code (via either a `git clone` or just downloading a zip file of the repository) and then doing a\n\n```\npython setup.py install\n```\n\nHere's the flowchart of the type guessing (it's also available in the `images` folder of this repo):\n\n![flowchart](https://github.com/jackmaney/csv-to-table/blob/master/images/type_guessing_flowchart.png?raw=true)\n\nHere's a quick example:\n\nInput:\n\n```\n$cat test.csv\na,b,c,d,e\n32,\"2013-12-28 22:16:57\",0,\"True\",\"Here's some text, and some more\"\n\"17.1\",\"2012-06-29 05:11:00\", -3,\"False\",\"Yep, more text\"\n```\n\nCode:\n\n```\nfrom typeguesser import TypeGuesser\n\ntg = TypeGuesser(\"test.csv\", header=True)\n\ntg.guessTypes()\n\nprint tg.getCreateStatement()\n```\n\nOutput:\n\n```\n$ python test.py\nCREATE TABLE test (\n    a numeric,\n    b timestamp,\n    c smallint,\n    d boolean,\n    e text\n);\n```\n\nOr, equivalently, you can use the included script `csv-to-table.py`:\n\n```\n$ ./csv-to-table.py -h\nusage: csv_to_table.py [-h] [--header] [--lowercase_header] [--sample SAMPLE]\n[--quotechar QUOTECHAR] [--delimiter DELIMITER]\n[--table_name TABLE_NAME] [--columns COLUMNS]\nfile\n\npositional arguments:\nfile                  The name (and path) of the target CSV file\n\noptional arguments:\n-h, --help            show this help message and exit\n--header              Indicate whether or not the file has a header\n--lowercase_header    Indicate whether or not to lowercase inferred column\nnames.\n--sample SAMPLE       Sampling probability (between 0 and 1). If set, this\ngives the sampling probability for rows of the given\nCSV file\n--quotechar QUOTECHAR\nThe quote character to use for the CSV file (default\n  '\"')\n  --delimiter DELIMITER\n  The delimiter to use for the CSV file (default ',')\n  --table_name TABLE_NAME\n  The name of the table desired in the output\n  --columns COLUMNS     A comma-delimited list of column names that you wish\n  to use\n\n```\n\nSo, in particular:\n\n```\n$ ./csv-to-table.py --header test.csv\nCREATE TABLE test (\n\ta numeric,\n\tb timestamp,\n\tc smallint,\n\td boolean,\n\te text\n);\n```",
        "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/jackmaney/csv_to_table.py.git",
        "keywords": null,
        "license": "MIT",
        "maintainer": null,
        "maintainer_email": null,
        "name": "csv_to_table",
        "package_url": "https://pypi.org/project/csv_to_table/",
        "platform": "UNKNOWN",
        "project_url": "https://pypi.org/project/csv_to_table/",
        "project_urls": {
            "Download": "UNKNOWN",
            "Homepage": "https://github.com/jackmaney/csv_to_table.py.git"
        },
        "release_url": "https://pypi.org/project/csv_to_table/0.0.3/",
        "requires_dist": null,
        "requires_python": null,
        "summary": "Generates a CREATE TABLE statement from a CSV file by guessing at column types",
        "version": "0.0.3"
    },
    "last_serial": 1331189,
    "releases": {
        "0.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "504525f52ef5137c1337b61e3accaec3",
                    "sha256": "6eb4e8a567698ac080696561b177eec34beb644953d7aac9535564b4f02ed1a4"
                },
                "downloads": -1,
                "filename": "csv_to_table-0.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "504525f52ef5137c1337b61e3accaec3",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5272,
                "upload_time": "2014-02-08T04:08:42",
                "url": "https://files.pythonhosted.org/packages/f5/4d/7d24679256bba71230128e0f4a083f08753904f3b226380c350935f74bb1/csv_to_table-0.0.1.tar.gz"
            }
        ],
        "0.0.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "3f7e3d9cb32e9125973d711df47089c2",
                    "sha256": "3d344db223e46da423ef34e21693b5b3561029643185838e3150afbd72050f7e"
                },
                "downloads": -1,
                "filename": "csv_to_table-0.0.2.tar.gz",
                "has_sig": false,
                "md5_digest": "3f7e3d9cb32e9125973d711df47089c2",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5487,
                "upload_time": "2014-02-12T00:34:12",
                "url": "https://files.pythonhosted.org/packages/e0/1f/b0182a7a413a80e3f9f6893c7fddbb69b2b137b73620af31d72b9aef172a/csv_to_table-0.0.2.tar.gz"
            }
        ],
        "0.0.3": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "c576220999a2050a8857b12448eba52a",
                    "sha256": "d260e322057830f382ee3846751721ea6993c1e4de6f49e6125819bf54d3cfaa"
                },
                "downloads": -1,
                "filename": "csv_to_table-0.0.3.tar.gz",
                "has_sig": false,
                "md5_digest": "c576220999a2050a8857b12448eba52a",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 5729,
                "upload_time": "2014-12-04T17:33:05",
                "url": "https://files.pythonhosted.org/packages/ea/6f/482c003d9566b21b73d1276039c9929e0b1990d64e2e48d0f461c336a152/csv_to_table-0.0.3.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "c576220999a2050a8857b12448eba52a",
                "sha256": "d260e322057830f382ee3846751721ea6993c1e4de6f49e6125819bf54d3cfaa"
            },
            "downloads": -1,
            "filename": "csv_to_table-0.0.3.tar.gz",
            "has_sig": false,
            "md5_digest": "c576220999a2050a8857b12448eba52a",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 5729,
            "upload_time": "2014-12-04T17:33:05",
            "url": "https://files.pythonhosted.org/packages/ea/6f/482c003d9566b21b73d1276039c9929e0b1990d64e2e48d0f461c336a152/csv_to_table-0.0.3.tar.gz"
        }
    ]
}