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        "author": "Pietro Giuffrida",
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        "description": "# sqlantipathy\nPython facilities to easily work with SQL databases\n\nOk, I don't love work with SQL databases. But the world works with SQL, then...\n\nDuring last years I wrote lot of function to work with MSSQL, MySQL, Oracle, SQLite...<br>\nThis project represent my personal attempt to systematize experiences, code,\nand approaches in few useful classes.\n\nOf course sqlalchemy is a sort of *de facto* standard in python/SQL approach,\nand my package will never be such mature... but in my opinion it is not so simple and not ever\nbackward compatibility is guaranteed with pyodbc and other low level libraries.\n\nAt this moment master branch only implements MSSQL routines.\nMySQL and Oracle rootines will be added as soon as possible.\n\n# Installation\n\nInstall sqlantipathy is as easy as run\n```pip install sqlantipathy```.\n\n# Usage\n\nA more accurate description of methods included in\nsqlantipathy will follow. By now, you can refers\nto main.py file content:\n\n```python\n#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nfrom sqlantipathy import MssqlAntipathy\nimport pandas as pd\n\nif __name__ == '__main__':\n\n    sql = MssqlAntipathy(\n        hostname=\"sql_hostname\",\n        user=\"sql_user\",\n        pwd=\"sql_pwd\",\n        driver=\"sql_driver_name\"\n    )\n\n    sql.connect()\n\n    database_list = sql.show_databases()\n\n    sql.use_database(\"mydb\")\n    mydb_tables = sql.show_tables()\n\n    qry = \"\"\"SELECT TOP 100 * FROM TABLENAME\"\"\"\n    data = sql.retrieve(\"sql_input_db\", qry)\n\n    list_of_dict = sql.retrieve(\"sql_input_db\", qry)\n    df = pd.DataFrame(list_of_dict)\n\n    sql.close_connection()\n\n    # A lot of code after...\n\n    sql.connect()\n    sql.cursor.execute(\"\"\"A SIMPLE QUERY\"\"\")\n    raw_data = sql.cursor.fetchall()\n```",
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