web2ldap is a full-featured Web-based LDAPv3 client written in Python. It is designed to run either as with stand-alone built-in Web server or under the control of another Web server with FastCGI support (e.g. Apache with mod_fastcgi). It has support for various LDAPv3 bind methods and a powerful built-in schema browser. HTML templates are supported for displaying and editing entries, and LDIF templates can be used for quickly adding new entries. A built-in X.509 parser displays a detailed view of certificates and CRLs with active links.
IMDbPY is a Python package useful to retrieve and manage the data of the IMDb movie database about movies, people, characters, and companies. It can retrieve data from both the IMDb's Web server and a local copy of the whole database. The IMDbPY package can be very easily used by programmers and developers to provide access to the IMDb's data to their programs. Some simple example scripts are included in the package.
Gaby is a small personal database manager using GTK+ and GNOME (if available) for its GUI. It was designed to provide straight-forward access to the types of databases a casual user would normally use, while keeping the ability to easily create databases for other needs. It was designed with extensibility in mind and relies heavily on plug-ins.
Sqlkit provides a GUI named sqledit to edit data in a database, as well as a package (sqlkit) in PyGtk. Sqledit (the application) can be run from the command line with arguments and will pop directly into the table/mask of the data, or without arguments and will present an input mask to write the database URL. Sqlkit (the Python package) provides SqlMask and SqlTable, two widgets for editing database data. It is meant to be used as a base for database desktop applications.
Modeling Framework fills the gap between the Python object world and relational databases in that it allows users to transparently create, retrieve, update, or delete Python objects from a database without having to write a single line of SQL. Its main features include generation of database schema, generation of Python code templates ready to be used, support for transparent mapping of (class) inheritance in relational databases, object-oriented query language, use of standard Python getters to traverse relationships (the related objects are automatically fetched when needed and when appropriate), and automatic checking for referential-integrity constraints, etc. Supported databases are MySQL, Oracle, PostgreSQL, and SQLite.
PySQL aims to be a full replacement for sqlplus (and much more). It has features such as history, completion, and line editing. It has high level functions (searching for tables, indexes, count, explain plan, list of sessions, etc.), proper output for screen and files (CSV ready for inclusion in spreadsheets), support for user-defined SQL, background queries, graphical output for the schema data model, object dependencies, a PL/SQL package function call tree, and much more.