pyPgSQL is a package of two modules that provide a Python DB-API 2.0 compliant interface to PostgreSQL databases. The first module, libpq, exports the PostgreSQL C API to Python. This module is written in C, and can be compiled into Python, or can be dynamically loaded on demand. The second module, PgSQL, provides the DB-API 2.0 compliant interface, and support for various PostgreSQL data types, such as INT8, NUMERIC, MONEY, BOOL, ARRAYS, BYTEA, etc. This module is written in Python, and works with PostgreSQL 7.0 or later, and Python 2.0 or later. Use of Python 2.1 or later, and PostgreSQL 7.1 or later is highly recommended. NB: pyPgSQL was previously released under the name 'PgSQL'.
| Tags | Database Front-Ends Software Development Libraries |
|---|---|
| Licenses | Python |
| Operating Systems | OS Independent |
| Implementation | C Python |
Recent releases


Changes: PgTypes are now hashable, and PgNumeric support was improved. The creation of large objects can now be rolled back, as it no longer automatically performs a commit. Sub-classed String and long types are now quoted properly. A possible buffer overrun condition in libPQquoteString was fixed.


Changes: This version includes support for PostgreSQL 7.3 2, UNICODE, and PostgreSQL reference cursors. The build process was improved, and should now build 'out of the box' on most popular systems. There is also improved support for the PostgreSQL NUMERIC type, and there were various bugfixes.


Changes: Access to PostgreSQL columns is now case insensitive. There are various bugfixes for the numeric data type and the database row type (PgResultSet).


Changes: Support for PostgreSQL transaction levels, improvements to performance and reduced memory consumption in PgResultSet, and other minor fixes and improvements.


Changes: This release is a 'real' Python package (i.e. a directory with an __init__.py file). pyPgSQL supplied types can now be pickled. A major memory leak has been plugged. Various problems with Large Objects have been fixed.
Uses rsync to manage archives of clients across multiple logical partitions.