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        "author": "Tim Lonsdale",
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        "description": "# SQL Interpolate\n\nA tool for safely building SQL queries using Python's f-Strings.\n\n## Purpose of this library\n\nWhen interfacing with the database, there are two main approaches one can use:\n\n  1. Building queries by writing explicitly parameterized SQL templates: *This allows for full control over the SQL but is verbose and hard to maintain - especially as the number of parameters grows.*\n  2. Building queries using an ORM: *This results in succinct and easy to maintain code but at the cost of losing control of the SQL that runs - sometimes with significant performance implications.*\n\nThe purpose of this library is therefore to provide a solution that results in terse code whilst also affording the user full control of the SQL that runs.\n\n## How does it work\n\nThe library exposes a single function that constructs a dynamic parameterized SQL query, along with its parameters: `build :: Thunk => ( SQL, Params )`. \n\nA `Thunk` is an alias for a function of type: `Wrapper => String`, where `Wrapper` is a function provided by the library that can wrap values that are to be interpolated in the following ways:\n\n  * If the value is itself a thunk, the `Wrapper` evaluates the thunk and returns the evaluated `String`. This allows you to compose SQL queries in a modular fashion.\n  * Else, the value is assigned to a unique parameter and the `Wrapper` returns the parameter template string.\n\n### Parameter formatting\n\nImporting `config` from the `sql_interpolate` package allows you to override how parameters are formatted. See the example below for details!\n\n## A quick example\n\n```python\nfrom sql_interpolate import build, config\n\n# Optionally override the default parameter formatting style of \"%(param)s\".\nconfig.format_fn = lambda x : \"$[ {0} ]\".format( x )\n\ndef sub_query( params ):\n    return lambda w : f\"\"\"other_val < { w( params[ \"min_val\" ] ) }\"\"\"\n\ndef query( params ):\n    return lambda w : f\"\"\"\n        SELECT * FROM table\n        WHERE id IN {\",\".join( w(x) for x in params[\"ids\"]}\n        AND val < { w( params[ \"max_val\" ] ) }\n        AND { w( sub_query( params ) ) }\n    \"\"\"\n\nparams = dict( ids = [ 1, 2, 3 ], max_val = 8, min_val = 5 )\nsql, params = build( query( params ) )\nprint( sql, params )\n```\n\nPrints the following:\n\n```python\n\"SELECT * FROM table\nWHERE id IN ( $[ param_1 ], $[ param_2 ], $[ param_3 ] )\nAND val < $[ param_4 ]\nAND other_val < $[ param_ 5 ]\"\n\n{ \"param_1\" : 1, \"param_2\" : 2, \"param_3\" : 3, \"param_4\" : 8, \"param_5\" : 5 }\n```\n\n\n",
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