Open Source Python Software - Page 70
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Python Software
Browse free open source Python Software and projects below. Use the toggles on the left to filter open source Python Software by OS, license, language, programming language, and project status.
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Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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NonVisual Desktop Access
Free, open source screen reader for Windows
A free and open source screen reader for the Microsoft Windows operating system. -
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7Zip-GUI
This is an alternative GUI for 7zip on Linux
This program is a Debian-based Linux alternative to 7zFM on Windows. It's easy to use. Thanks so much for Igor Pavlov! https://github.com/shampuan/7Zip-GUI Bu program, Windows tarafındaki 7zFM'in debian tabanlı linux'lar için alternatifidir. -
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FF Multi Converter is a simple graphical application which enables you to convert audio, video, image and document files between all popular formats, using and combining other programs. It uses ffmpeg for audio/video files, unoconv for document files and ImageMagick for image file conversions.
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Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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jdMinecraftLauncher
Unofficial classic styled Minecraft Launcher
jdMinecraftLauncher is a Minecraft launcher which Look and Feel is close to the the good old official Launcher. You need a Microsoft Account which owns Minecraft to use this Launcher This Launcher is completly fanmade and not supported by Mojang/Microsoft -
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VPython-wx
This project is no longer valid. See vpython.org.
This project is no longer valid. See vpython.org. -
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synergy-stable-builds
Share one mouse, one keyboard and one clipboard between your computers
Synergy combines your desktop devices together in to one cohesive experience. It's software for sharing your mouse and keyboard between multiple computers on your desk. It works on Windows, Mac OS X and Linux. -
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Wait and Pounce FT8
Wait to decode callsigns, then call them using UDP protocol
Neat alternative for JTAlert. Available for both Apple and Windows (10+). Make sure to automatically call any Wanted callsigns specified. Can also be used to monitor band opening. Can handle callsign exclusions. Can even handle wanted callsigns according to your worked before Rules. -
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GCompris : I got IT
Educational Software for children aged 2 to 10.
GCompris is a high quality educational software suite comprising of numerous activities for children aged 2 to 10. Some of the activities are game oriented, but nonetheless still educational. -
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This project is not maintained anymore. A new maintainer has been updating it in https://github.com/qazmlpok/quivi, but I'm not involved with it. Quivi is a comic / manga reader but also an general purpose image viewer for Windows which supports many file formats and compressed (zip, rar) files. It is aimed for fast & easy file browsing with keyboard or mouse.
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GHydraulics
Create EPANET models in QGIS
Open Source Hydraulic Network Analysis Software. A plug-in for Quantum GIS (QGIS) that allows you to create EPANET hydraulic analysis models. EPANET is a popular open source software to analyze water supply networks. -
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Wine Runner
A wine and qemu GUI runner to help you install and use easily.
Wine runner is a wine and qemu GUI runner to help you install and use wine easily. Also it can help you install windows easily because virtual machine tools can create virtual machine and run auto. Github: https://github.com/gfdgd-xi/deep-wine-runner/ Telegram: https://t.me/wine_runner 一个能让Linux用户更加方便运行Windows应用的程序，内置了对wine图形化的支持和各种Wine工具和自制Wine程序打包器、运行库安装工具等等。同时也内置了基于VirtualBox制作的小白Windows虚拟机安装工具，可以做到只需要用户下载系统镜像并点击安装即可，无需顾及虚拟机安装、创建、虚拟机的分区等等 Wine 运行器 QQ 交流群：762985460 -
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FontForge Windows builds
Unofficial Windows builds of FontForge
The aim of this project is to compile up-to-date Windows builds of FontForge. For 'stable' builds, see https://github.com/fontforge/fontforge/releases The build system used was based off that offered by Matthew Petroff (http://www.mpetroff.net/software/fontforge-windows/), but has since been practically rewritten. New in 11/07/2020: * Synced with the 20201107 release. New in 06/04/2020: * Updated to latest master, picks up a clipboard copying fix New in 14/03/2020: * Synced with the 20200314 release. New in 01/03/2020: * Updated to latest master, now built with CMake. (prerelease) New in 02/06/2019: * The 32-bit build now uses Python 3 (3.7) instead of Python 2. No further Python 2 builds will be provided. * The GDK3 backend is now used. VcXsrv is no longer bundled. New in 31/07/2017: KNOWN ISSUES: * CTRL-C from console no longer interrupts/stops FontForge -
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Nagstamon is a Nagios status monitor which resides in systray or desktop (Linux, macOS, Windows) as floating statusbar to inform you in realtime about the status of your hosts and services. It allows to connect to multiple Nagios based monitors. Currently supported are Nagios, Icinga, Opsview, Op5 Ninja, Check_MK Multisite, Centreon and Thruk.
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ADX MCP Server
A Model Context Protocol (MCP) server that enables AI assistants
The Azure Data Explorer MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to query and analyze Azure Data Explorer databases through standardized interfaces. It allows the execution of Kusto Query Language (KQL) queries and exploration of data within Azure Data Explorer clusters. -
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AI Data Science Team
An AI-powered data science team of agents
AI Data Science Team is a Python library and agent ecosystem designed to accelerate and automate common data science workflows by modeling them as specialized AI “agents” that can be orchestrated to perform tasks like data cleaning, transformation, analysis, visualization, and machine learning. It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. The project includes ready-to-use applications that showcase these agents in action, such as an exploratory data analysis copilot that generates reports, a pandas data analyst that combines wrangling and plotting, and SQL database agents that can query business databases and output results directly. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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AI Marketing Skills
Open-source AI marketing skills for Claude Code
AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into multiple domains such as growth experimentation, sales pipeline generation, content production, outbound marketing, SEO optimization, and financial analysis, effectively covering the entire revenue lifecycle of a business. Each skill functions as an executable capability that can be invoked on demand, enabling users to perform tasks like running A/B tests, generating high-quality content, or analyzing conversion funnels with minimal manual effort. -
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. The system emphasizes modularity, so teams can swap in new reasoning modules, data retrieval strategies, or domain knowledge bases depending on the research topic. Through self-supervised feedback loops, agents adjust their strategies based on prior outcomes, improving both the quality and relevance of results over time. -
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AI-Researcher
AI-Researcher: Autonomous Scientific Innovation
AI-Researcher is an open-source system designed to automate complex research tasks end-to-end using large language models and structured workflows, aiming to replicate parts of a human research assistant’s capabilities. It lets users input high-level research goals or questions in natural language and then automatically plans, decomposes, and executes tasks such as literature surveying, summarization, synthesis, experiment design, and draft generation. The system integrates retrieval mechanisms to pull in external knowledge sources, contextually analyze documents and papers, and build structured representations of ideas and arguments that can later be turned into coherent reports or drafts. Rather than simply generating text from prompts, AI-Researcher orchestrates sequences of subtasks — such as extracting definitions, identifying key experiments, and tracking citations — and uses self-refinement loops to iteratively improve outputs. -
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AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation. -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. It is intended to facilitate reproducible RL training on reasoning / agentic tasks, supporting scaling from single nodes to large GPU clusters. It can streamline the development of AI agents and reasoning systems. Support for algorithm and system co-design optimizations (to improve efficiency and stability). -
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ATX
Smart phone automation tool. Support iOS, Android, WebApp and game
ATX (AutomatorX) is an open source automated testing tool that supports testing native applications, games, and Web applications on iOS and Android platforms. Use Python to write test cases, and use image recognition and control positioning technology to complete the automation of the game. Attach a dedicated IDE to complete scripting quickly. The libraries for Android and iOS native application testing have been separated and can be used alone (it is strongly recommended to use it alone, firstly, it has less dependencies and high stability, and secondly, it can be automatically completed when writing code) -
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AWS IoT Device SDK for Python
SDK for connecting to AWS IoT from a device using Python
The AWS IoT Device SDK for Python allows developers to write Python script to use their devices to access the AWS IoT platform through MQTT or MQTT over the WebSocket protocol. By connecting their devices to AWS IoT, users can securely work with the message broker, rules, and the device shadow (sometimes referred to as a thing shadow) provided by AWS IoT and with other AWS services like AWS Lambda, Amazon Kinesis, Amazon S3, and more. It is a complete rework, built to improve reliability, performance, and security. We invite your feedback! The SDK is built on top of a modified Paho MQTT Python client library. Developers can choose from two types of connections to connect to AWS IoT. For MQTT over TLS (port 8883 and port 443), a valid certificate and a private key are required for authentication. For MQTT over the WebSocket protocol (port 443), a valid AWS Identity and Access Management (IAM) access key ID and secret access key pair are required for authentication.
