README.md

queryparser

Tool for parsing and processing of (MySQL*)/PostgreSQL and translation of ADQL SELECT-like queries

Designed to be used in conjunction with django-daiquri as a query processing backend but it can be easily used as a stand-alone tool or integrated into another project.

*NOTE: Since version 0.7.0 MySQL is not supported (maintained) anymore.

Installation

The easiest way to install the package is by using the pip tool:

python -m pip install queryparser-python3

Alternatively, you can clone the repository and install it from there. However, this step also requires generating the parser which is a slightly more elaborate process (see below).

Generating the parser from the git repository

To generate the parsers you need python3 , java above version 7, and antlr4 (antlr-4.*-complete.jar has to be installed inside the /usr/local/lib/, /usr/local/bin/ or root directory of the project).

The current version of antlr-4.*-complete.jar can be downloaded via

wget http://www.antlr.org/download/antlr-4.13.1-complete.jar

After cloning the project run

make

and a lib directory will be created. After that, run

python -m pip install .

to install the generated parser in your virtual environment.

Additional requirements

The queryparser assumes that the PostgreSQL database has the extension pg_sphere installed. Although the pg_sphere is not required for the python module, the PostgreSQL queries will not run without this extension installed on the database.

Parsing MySQL and PostgreSQL

Since version 0.7, MySQL part of the parser is not maintained anymore. Thus, the MySQL related functionality cannot be guaranteed!

Parsing and processing of MySQL queries can be done by creating an instance of the MySQLQueryProcessor class

from queryparser.mysql import MySQLQueryProcessor
qp = MySQLQueryProcessor()

feeding it a MySQL query

sql = "SELECT a FROM db.tab;"
qp.set_query(sql)

and running it with

qp.process_query()

After the processing is completed, the processor object qp will include tables, columns, functions, and keywords used in the query or will raise a QuerySyntaxError if there are any syntax errors in the query.

Alternatively, passing the query at initialization automatically processes it.

PostgreSQL parsing is very similar to MySQL, except it requires importing the PostgreSQLProcessor class:

from queryparser.postgresql import PostgreSQLQueryProcessor
qp = PostgreSQLQueryProcessor()

The rest of the functionality remains the same.

Translating ADQL

Translation of ADQL queries is done similarly by first creating an instance of the ADQLQueryTranslator class

from queryparser.adql import ADQLQueryTranslator
adql = "SELECT TOP 100 POINT('ICRS', ra, de) FROM db.tab;"
adt = ADQLQueryTranslator(adql)

and calling

adt.to_postgresql()

which returns a translated string representing a valid MySQL query if the ADQL query had no errors. The PostgreSQL query can then be parsed with the PostgreSQLQueryProcessor in the same way as shown above.

Testing

First in the root directory of the project, install optional dependencies (PyYAML and pytest) by running

python -m pip install .[test]

then run the test suite with

python -m pytest lib/