Open Source Python Database Software - Page 8

ERAlchemy generates Entity Relation (ER) diagram from databases or from SQLAlchemy models. The simplest way to install eralchemy on OSX is by using Homebrew. ERAlchemy requires GraphViz to generate the graphs and Python. Both are available for Windows, Mac and Linux. Thanks to it's modular architecture, it can be connected to other ORMs/ODMs/OGMs/O*Ms. Some tests require a local postgres database with a schema named test in a database named test all owned by a user named postgres with a password of postgres. ERAlchemy was inspired by erd, though it is able to render the ER diagram directly from the database and not just only from the ER markup language.

A semantic memory software tool “reflects” one's “imagination”. In it, arbitrary concepts may be described, stored, arranged, transformed, and shared. One may verbalize thoughts as they arise in the mind to externalize and digitize “mental obj

FEAS steht für "Flugdaten Erfassungs- und Auswertungs- System". Es erleichtert die Führung von Flugbüchern, Bordbüchern und die Gebührenabrechnung.

FGL is a tightly-integrated self-contained development & execution environment utilizing best-of-breed programming tools and methodologies, optimized web/application server, highly-scalable relational/object database, and robust extension interface.

Fapro is an open-source asset discovery and vulnerability scanning tool developed by Fofa Pro. It assists in identifying and managing network assets, detecting potential vulnerabilities, and enhancing overall security posture

XML-RPC/FastRPC/MySQL console with Python-like syntax

FastVersion is a Qgis plugin for data versioning in a Postgis database. This plugin provides data versioning to tables with geometry stored in postgis. It allows to create, changes and eliminate versions, and within each version , to insert, modify and eliminate elements. It is possible carry out the processes of “post” from one version to another, with conflict resolution functionality. The system uses algorithms and data structures so that information is not duplicated each time a version is created. We recommend downloading it from the Qgis app. Plugins->Manage and Install Plugins->Settings->Show also experimental plugins Plugins->Manage and Install Plugins->Search FastVersion If downloaded from sourceforge, it must be unzipped in \.qgis2\python\plugins

A database and a web front end for physiologic data on animal feeding, developed with PostgreSQL and Django at NESCent (http://www.nescent.org) for Mammalian Feeding Working Group (http://www.feedexp.org). Current development of the codebase is on Github at http://github.com/NESCent/feedingdb.

File and Database Generator for windows and linux

fbdbinfo is a tiny python script which creates xhtml files that display information about a Firebird database. The data can as well be exported to xhtml files.

The Flamenco search and browse interface framework uses hierarchical faceted metadata to allow users to both refine and expand queries, while maintaining a consistent representation of a collection and seamlessly integrating keyword queries.

FleXTriad is a bundle of : Apache 2.2, MySQL 5.0, PHP 5.1, Perl 5.8, FileZila FTP Server 0.9 and QK SMTP Server 3. Tools included: xPanel, phpMyAdmin, MySQL Administrator 1.2 and FleXTriad Monitor. All latest stables.

FlightFeather's goal is "social networking for everyone". This means that anyone should have a chance to run a popular social networking site -- on minimal hardware, and without wasting bandwidth.

FreeGee is an integrated application framework for Python and C++. Included modules are: Python (scripting), PostgreSQL (database), wxWidgets/wxWindows (GUI), GnuPG (crypto), omniORB (OO middleware), Apache (Web), and other fine tools (see Home Page).

Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic interactive documentation. Many other features including automatic validation, serialization, interactive documentation, authentication with OAuth2 JWT tokens, etc. Celery worker that can import and use models and code from the rest of the backend selectively. REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time.

Python program to convert the morphologically parsed Greek New Testament (provided by UPenn's CCAT and James Tauber http://morphgnt.org/) into an Emdros (http://emdros.org/) MQL database.

GNUccess aims to provide the Open Source Community with the alternative for using proprietary tools like for example MSAccess or PowerBuilder. It will allows creating, managing and running database applications.

Gaby is a small personal databases manager for Linux using GTK+ and Gnome (if available) for its GUI.

GameFAQs board and user indexer fetches pages from GameFAQs and stores board and user names in a database for browsing.

Forms development tool for PostgreSQL in Python on GTK.

This framework allows the definition of attributes, entities and relations as used in entity-relationship (ER) models. It will then handle input and representation of data appropriately.

Complete and modular solution for storing school marks in electronical form.

The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks. It is recommended to explore them. All of the commands and features supported by graph notebook are explained in detail with examples within the sample notebooks. You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder.

GraphQLmap is a Python-based scripting engine designed to interact with GraphQL endpoints for penetration testing purposes. It can connect to a target GraphQL endpoint, dump the schema (if introspection is enabled), query it interactively, and fuzz fields for NoSQL/SQL injection vectors, thereby revealing hidden attack surfaces. GraphQL endpoints represent a relatively newer attack vector compared to REST, and GraphQLmap helps bridge this gap by providing tooling tailored to the GraphQL paradigm. Because many modern applications adopt GraphQL for flexibility, this tool is useful when scanning and attacking API back ends where typical REST-based tools fall short. For a pentester, GraphQLmap speeds up discovery and exploitation workflows: you don’t just test known endpoints—you enumerate schema, fuzz fields, and chain queries. It offers a CLI, supports various HTTP methods, custom headers, proxies, and is designed to work with real-world GraphQL deployments.

In Green Cloud here is a central global server which does the work of global database management along with providing complex analysis services for the users (farmers, scientists) through the client machines and the public access web portal. The existing agricultural databases throughout the world can also be used for inference purposes and their data may also be updated by our server. The meteorological servers can be accessed for climate data.This server-client architecture mandatory in present and even near-future circumstances as the client machine has to be low-power and low-cost for the feasibility of the system in Indian context. Therefore, the complex analysis (Expert system analysis in accordance with world-wide data) has to be done on server. The environment data is collected via sensors is uploaded to the website