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This section shows some simple usage examples of these functions.Let’s get started with splitting a string containing one or more SQL statements into a list of single statements using for a full reference of supported options given as keyword arguments to that function.this can help determine what is being affected, including but not limited to schema, table, column.Quickly locate the primary key and/or foreign key in DDL scripts to figure out the complex relationship between the various tables.For example, when you need to do non-trivial operations on queries, like: The Postgres documentation gives a good overview how query execution is handled and what the intermediate tree representations of a query string are.Postgres already offers tooling to create a query tree from a given query string.This means that all nodes not expected in later stages of query execution can't be printed, for example INSERT/UPDATE/DELETE nodes - since later on these are all aggregated in a node.

python validating sql parser-32python validating sql parser-21

When using the is currently tested under Python 2.5, 2.6, 2.7, 3.2 and pypy.

As you can guess, my search wasn’t really successfull.

pyparsing needs a grammar, but I’m not really interested in writing a full-blown grammar for SQL with it’s various dialects.

The answer is: them is not possible, though some lexers go some steps in this direction in order to e.g. Also, error reporting is not the scope of Pygments.

module provides three simple functions on module level to achieve some common tasks when working with SQL statements.