Open Source Python Database Software
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Python Database Software
View 464 business solutionsBrowse free open source Python Database Software and projects below. Use the toggles on the left to filter open source Python Database Software by OS, license, language, programming language, and project status.
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Firebird
A powerful, cross platform, SQL database system
Firebird RDBMS offers ANSI SQL features & runs on Linux, Windows & several Unix platforms. Features excellent concurrency & performance & powerful stored procedure & trigger language. More information and downloads at https://firebirdsql.org/, issue tracker is https://github.com/FirebirdSQL/firebird/issues -
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LibreOffice
A free and powerful office suite
LibreOffice is a free and powerful office suite, and a successor to OpenOffice. Its clean interface and feature-rich tools help you unleash your creativity and enhance your productivity. LibreOffice is Free and Open Source Software (FOSS) – development is open to new talent and new ideas, and our software is tested and used daily by a large and devoted user community. Your documents will look professional and clean, regardless of their purpose: a letter, a master thesis, a brochure, financial reports, marketing presentations, technical drawings and diagrams. LibreOffice makes your work look great while you focus on the content, thanks to its powerful styles system and structuring tools. LibreOffice is compatible with a wide range of document formats such as Microsoft® Word (.doc, .docx), Excel (.xls, .xlsx), PowerPoint (.ppt, .pptx) and Publisher. But LibreOffice goes much further with its native support for a modern and open standard (OpenDocument Format). -
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SQLAlchemy
The Database Toolkit for Python
SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. SQLAlchemy provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language. An industrial strength ORM, built from the core on the identity map, unit of work, and data mapper patterns. These patterns allow the transparent persistence of objects using a declarative configuration system. Domain models can be constructed and manipulated naturally, and changes are synchronized with the current transaction automatically. A relationally-oriented query system, exposing the full range of SQL's capabilities explicitly, including joins, subqueries, correlation, and most everything else, in terms of the object model. Writing queries with the ORM uses the same techniques of relational composition you use when writing SQL. -
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The MonetDB project has moved to http://www.monetdb.org/.
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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MySQL for Python
MySQL database connector for Python programming
MySQLdb is a Python DB API-2.0-compliant interface; see PEP-249 for details. For up-to-date versions of MySQLdb, use the homepage link. Supported versions: * MySQL versions from 3.23 to 5.5; 5.0 or newer recommended. MariaDB should also work. * Python versions 2.4-2.7; Python 3 support coming soon. ZMySQLDA is a Database Adapter for Zope2. -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using pip install SpeechRecognition. The first software requirement is Python 2.6, 2.7, or Python 3.3+. This is required to use the library. PyAudio is required if and only if you want to use microphone input (Microphone). PyAudio version 0.2.11+ is required, as earlier versions have known memory management bugs when recording from microphones in certain situations. To hack on this library, first make sure you have all the requirements listed in the "Requirements" section. -
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SQL Explorer
Easily share data across your company via SQL queries
SQL Explorer aims to make the flow of data between people fast, simple, and confusion-free. It is a Django-based application that you can add to an existing Django site, or use as a standalone business intelligence tool. Quickly write and share SQL queries in a simple, usable SQL editor, preview the results in the browser, share links, download CSV, JSON, or Excel files (and even expose queries as API endpoints, if desired), and keep the information flowing! Comes with support for multiple connections, to many different SQL database types, a schema explorer, query history (e.g. lightweight version control), a basic security model, in-browser pivot tables, and more. SQL Explorer values simplicity, intuitive use, unobtrusiveness, stability, and the principle of least surprise. SQL Explorer is inspired by any number of great query and reporting tools out there. -
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WhatsApp Chat Exporter
A cross-platform tool for parsing WhatsApp chat databases
WhatsApp-Chat-Exporter is a customizable tool for parsing WhatsApp databases from Android and iOS devices. It extracts chat histories and exports them in HTML and JSON formats, supporting various encryption standards. -
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pagodo
Automate Google Hacking Database scraping and searching
pagodo automates Google searching for potentially vulnerable web pages and applications on the Internet. It replaces manually performing Google dork searches with a web GUI browser. There are 2 parts. The first is ghdb_scraper.py that retrieves the latest Google dorks and the second portion is pagodo.py that leverages the information gathered by ghdb_scraper.py. This version of pagodo also supports native HTTP(S) and SOCKS5 application support, so no more wrapping it in a tool like proxychains4 if you need proxy support. You can specify multiple proxies to use in a round-robin fashion by providing a comma-separated string of proxies using the -p switch. To start off, pagodo.py needs a list of all the current Google dorks. The repo contains a dorks/ directory with the current dorks when the ghdb_scraper.py was last run. It's advised to run ghdb_scraper.py to get the freshest data before running pagodo.py. -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Train models on your data in your datastore simply by querying without additional ingestion and pre-processing. -
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Barman for PostgreSQL
Backup and Recovery Manager for PostgreSQL
Barman (backup and recovery manager) is an administration tool for disaster recovery of PostgreSQL servers written in Python. It allows to perform remote backups of multiple servers in business critical environments and help DBAs during the recovery phase. Barman's most wanted features include backup catalogs, retention policies, remote recovery, archiving and compression of WAL files and backups. Barman is written and maintained by PostgreSQL professionals 2ndQuadrant. -
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A HUD and stats tracker for your poker games written in Python. Supports Holdem, Omaha, Stud, Razz and Draw games.
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imgSeek is a photo collection manager and viewer with content-based search and many other features. The query is expressed either as a rough sketch painted by the user or as another image you supply (or an image in your collection).
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Fapro
Fake Protocol Server
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 -
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Cinemagoer
Python package to retrieve and manage data of the IMDb
Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb movie database about movies, people, characters and companies. Platform-independent, it can retrieve data from both the IMDb's web server and a local copy of the whole db. -
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SQLModel
SQL databases in Python, designed for simplicity, compatibility
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. SQLModel is based on Python-type annotations, and powered by Pydantic and SQLAlchemy. -
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mongoaudit
A powerful MongoDB auditing and pentesting tool
mongoaudit is a CLI tool for auditing MongoDB servers, detecting poor security settings and performing automated penetration testing. It is widely known that there are quite a few holes in MongoDB's default configuration settings. This fact, combined with abundant lazy system administrators and developers, has led to what the press has called the MongoDB apocalypse. mongoaudit not only detects misconfigurations, known vulnerabilities and bugs but also gives you advice on how to fix them, recommends best practices and teaches you how to DevOp like a pro! MongoDB listens on a port different to default one. Server only accepts connections from whitelisted hosts / networks. MongoDB HTTP status interface is not accessible on port 28017. MongoDB is not exposing its version number. MongoDB version is newer than 2.4. TLS/SSL encryption is enabled. Authentication is enabled. SCRAM-SHA-1 authentication method is enabled. -
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ArangoDB-Community/pyArango
Python Driver for ArangoDB with built-in validation
PyArango is a Python driver for ArangoDB, a multi-model NoSQL database. It provides a Pythonic way to interact with ArangoDB, allowing developers to manage collections, execute AQL queries, and integrate ArangoDB's document, graph, and key-value storage models into Python applications. -
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Cinemagoer
Python package useful to retrieve and manage the data of IMDb
Cinemagoer (previously known as IMDbPY) is a Python package for retrieving and managing the data of the IMDb movie database about movies and people. You can use the search_movie method of the access object to search for movies with a given (or similar) title. Similarly, you can search for people and companies using the search_person and the search_company methods. Movie, person, and company objects have id attributes which -when fetched through the IMDb web server- store the IMDb id of the object. If you know the IMDb id of a movie, you can use the get_movie method to retrieve its data. It’s possible to retrieve the list of top 250 and bottom 100 movies. As on the IMDb site, each TV series and also each of a TV series’ episodes is treated as a regular title, just like a movie. The episodes of a series can be fetched using the “episodes” infoset. -
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Full Stack FastAPI and PostgreSQL
Full stack, modern web application generator
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. -
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mysqlclient
MySQL/MariaDB connector for Python
Summary: mysqlclient is a MySQL/MariaDB connector for Python, providing a convenient interface for database interactions. -
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The goal of PyTables is to enable the end user to efficiently and easily manipulate large datasets (both homogenous, i.e. arrays, and heterogenous, i.e. tables) on a persistent, hierarchical way.
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Finance Database
This is a database of 300.000+ symbols containing Equities, ETFs, etc.
As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). However, what else is out there is often unknown. This database tries to solve that. It features 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets. It, therefore, allows you to obtain a broad overview of sectors, industries, types of investments and much more. The aim of this database is explicitly not to provide up-to-date fundamentals or stock data as those can be obtained with ease (with the help of this database) by using yfinance, FundamentalAnalysis or ThePassiveInvestor. -
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TinyDB
Document oriented database optimized for you
TinyDB is a lightweight document oriented database optimized for your happiness :) It's written in pure Python and has no external dependencies. The target are small apps that would be blown away by a SQL-DB or an external database server. The current source code has 1800 lines of code (with about 40% documentation) and 1600 lines tests. Like MongoDB, you can store any document (represented as dict) in TinyDB. TinyDB is designed to be simple and fun to use by providing a simple and clean API. TinyDB neither needs an external server (as e.g. PyMongo) nor any dependencies from PyPI. TinyDB works on all modern versions of Python and PyPy. You can easily extend TinyDB by writing new storages or modify the behaviour of storages with Middlewares. TinyDB has been tested with Python 3.6 - 3.10 and PyPy3. -
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data-diff
Efficiently diff rows across two different databases
We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across hundreds of tables, with low latency and at a reasonable infrastructure cost is a hard problem, and most data teams we’ve talked to, have faced data quality issues in their replication processes. The hard truth is that the quality of the replication is the quality of the data. Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates.
