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        "author": "Maciej Brencz",
        "author_email": "maciej.brencz@gmail.com",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: System Administrators",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Database"
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        "description": "# sql-metadata\n\n[![PyPI](https://img.shields.io/pypi/v/sql_metadata.svg)](https://pypi.python.org/pypi/sql_metadata)\n[![Build Status](https://travis-ci.org/macbre/sql-metadata.svg?branch=master)](https://travis-ci.org/macbre/sql-metadata)\n\nUses tokenized query returned by [`python-sqlparse`](https://github.com/andialbrecht/sqlparse) and generates query metadata.\nExtracts column names and tables used by the query. Provides a helper for normalization of SQL queries.\n\nSupported queries syntax:\n\n* MySQL\n* PostgreSQL\n* [Apache Hive](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DML)\n\n### Usage\n\n```\npip install sql_metadata\n```\n\n```python\n>>> import sql_metadata\n\n>>> sql_metadata.get_query_tokens(\"SELECT * FROM foo\")\n[<DML 'SELECT' at 0x7F14FFDEB808>, <Wildcard '*' at 0x7F14FFDEB940>, <Keyword 'FROM' at 0x7F14FFDEBBB0>, <Name 'foo' at 0x7F14FFDEB9A8>]\n\n>>> sql_metadata.get_query_columns(\"SELECT test, id FROM foo, bar\")\n[u'test', u'id']\n\n>>> sql_metadata.get_query_tables(\"SELECT a.* FROM product_a.users AS a JOIN product_b.users AS b ON a.ip_address = b.ip_address\")\n['product_a.users', 'product_b.users']\n\n>>> sql_metadata.get_query_columns(\"INSERT /* VoteHelper::addVote xxx */  INTO `page_vote` (article_id,user_id,`time`) VALUES ('442001','27574631','20180228130846')\")\n['article_id', 'user_id', 'time']\n\n>>> sql_metadata.get_query_columns(\"SELECT a.* FROM product_a.users AS a JOIN product_b.users AS b ON a.ip_address = b.ip_address\")\n['a.*', 'a.ip_address', 'b.ip_address']\n\n>>> sql_metadata.get_query_tables(\"SELECT test, id FROM foo, bar\")\n[u'foo', u'bar']\n\n>>> sql_metadata.get_query_limit_and_offset('SELECT foo_limit FROM bar_offset LIMIT 50 OFFSET 1000')\n(50, 1000)\n\n>>> sql_metadata.get_query_limit_and_offset('SELECT foo_limit FROM bar_offset limit 2000,50')\n(50, 2000)\n```\n\n> See `test/test_query.py` file for more examples of a bit more complex queries.\n\n#### Queries normalization\n\n```python\n>>> from sql_metadata import generalize_sql\n>>> generalize_sql('SELECT /* Test */ foo FROM bar WHERE id in (1, 2, 56)')\n'SELECT foo FROM bar WHERE id in (XYZ)'\n```\n\n> See `test/test_normalization.py` file for more examples of a bit more complex queries.",
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