| Name | queryparser-python3 JSON |
| Version |
0.7.4
JSON |
| download |
| home_page | None |
| Summary | Package for parsing PostgreSQL/MySQL and translating ADQL to PostgreSQL/MySQL. |
| upload_time | 2025-08-18 12:54:33 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | Apache-2.0 |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
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](https://github.com/django-daiquiri/daiquiri)
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.**
[](https://github.com/aipescience/queryparser/actions/workflows/pytest.yml)
[](https://coveralls.io/github/aipescience/queryparser?branch=master)
[](https://github.com/aipescience/queryparser/blob/master/LICENSE)
[](https://pypi.org/project/queryparser-python3/)
Installation
------------
The easiest way to install the package is by using the pip tool:
```bash
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
```bash
wget http://www.antlr.org/download/antlr-4.13.1-complete.jar
```
After cloning the project run
```bash
make
```
and a `lib` directory will be created. After that, run
```bash
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](https://github.com/kimakan/pgsphere/tree/aiprdbms16) 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
```python
from queryparser.mysql import MySQLQueryProcessor
qp = MySQLQueryProcessor()
```
feeding it a MySQL query
```python
sql = "SELECT a FROM db.tab;"
qp.set_query(sql)
```
and running it with
```python
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:
```python
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
```python
from queryparser.adql import ADQLQueryTranslator
adql = "SELECT TOP 100 POINT('ICRS', ra, de) FROM db.tab;"
adt = ADQLQueryTranslator(adql)
```
and calling
```python
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
```bash
python -m pip install .[test]
```
then run the test suite with
```bash
python -m pytest lib/
```
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