Open Source Python Software - Page 55
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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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The Missing Semester
The Missing Semester of Your CS Education
The Missing Semester is a course and repository that teaches the engineering skills often skipped in traditional computer science curricula: command-line fluency, shell scripting, editors, version control, debugging, data wrangling, and automation. It includes lecture notes, exercises, and sample solutions that encourage hands-on practice rather than passive reading. The curriculum demystifies tools like bash, vim, git, and make, showing how to combine them into efficient workflows that scale from homework to production systems. Lessons dig into practical topics such as environment management, job control, shell pipelines, profiling, and reproducibility, with an emphasis on habits that save time and prevent errors. The materials are designed to be approachable for beginners yet still valuable to advanced users who want to sharpen their tooling. By the end, learners can work faster and more reliably because they understand the mechanics of their everyday tools. -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost weights, feature extractors, or initialization networks end-to-end. The implementation supports batched optimization on GPU, robust losses, damping strategies, and custom factors, making it practical for real-time systems. Helper packages provide geometry primitives and utilities for composing priors, relative constraints, and measurement models. Theseus bridges the gap between classical optimization and deep learning, enabling hybrid systems that learn components. -
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
Three.js Object Sculptor is a Codex plugin that converts a reference image into a procedural Three.js object written entirely in code. It first evaluates whether the image is suitable and produces an ObjectSculptSpec describing geometry, materials, lighting, hierarchy, pivots, and quality targets. Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for animation, transformation, physics, and destruction. Reference and rendered screenshots can be combined for AI vision review and scored self-correction. The workflow targets browser-friendly props and stylized reconstructions rather than photogrammetry or exact mesh extraction. -
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ToolUniverse
Democratizing AI scientists with ToolUniverse
ToolUniverse is a comprehensive open-source ecosystem designed to transform any large language model into an autonomous “AI scientist” capable of performing real scientific research tasks through structured tool interaction. It standardizes how AI systems discover, select, and execute tools by introducing a unified AI-Tool Interaction Protocol that allows models to seamlessly connect with hundreds of scientific resources, including machine learning models, datasets, APIs, and analytical packages. Instead of requiring custom pipelines or fine-tuning, ToolUniverse wraps around existing models and enables them to reason, experiment, and iterate on complex workflows such as drug discovery, data analysis, and hypothesis testing. The platform abstracts tool usage behind a consistent interface, allowing AI agents to compose multi-step workflows, refine tool definitions automatically, and even generate new tools from natural language descriptions. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Trellis AI
All-in-one AI framework & toolkit for Claude Code & Cursor
Trellis is an advanced workflow and agent orchestration framework designed for building, managing, and scaling intelligent applications that coordinate numerous autonomous components. At its core, Trellis lets developers define units of work — called tasks or agents — and compose them into rich workflows that can operate with concurrency, conditional logic, and dynamic branching, all without sacrificing readability or control. It emphasizes modular design, encouraging users to encapsulate logic into reusable pieces that can be tested, versioned, and reused across projects. Trellis also includes tooling for monitoring, scheduling, and tracing the execution of complex multi-step jobs, helping teams maintain visibility into how work progresses and where bottlenecks emerge. The platform can integrate with external services, databases, and model endpoints, making it suitable for automation, ETL pipelines, AI-driven processes, and business logic orchestration. -
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Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects like memory access patterns and parallel execution. The project leverages LLVM and MLIR to compile code into efficient GPU instructions, supporting both NVIDIA and AMD hardware. It is widely used in research and production environments where custom tensor operations are required, offering both high performance and developer-friendly syntax. -
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Unofficial TikTok API in Python
The Unofficial TikTok API Wrapper In Python
This is an unofficial API wrapper for TikTok in python. With this API you are able to call most trending and fetch specific user information as well as much more. If you run into an issue please check the closed issues on GitHub, although feel free to re-open a new issue if you find an issue that's been closed for a few months. The codebase can and does run into similar issues as it has before because TikTok changes things up. To run the example scripts from the repository root, make sure you use them an option on python. You can access the dictionary type of an object using .as_dict. On a video, this may look like this, although TikTok changes its structure from time to time so it's worth investigating the structure of the dictionary when you use this package. You'll probably need to use this beyond just for legacy support since not all attributes are parsed out and attached to the different objects. -
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VERBI
A modular voice assistant application for experimenting
Verbi is a modular Python voice assistant for experimenting with speech recognition, language model responses, and text-to-speech generation. Its component-based design lets developers replace individual models without rewriting the full application. The project integrates hosted services such as OpenAI, Groq, Deepgram, ElevenLabs, and Cartesia while also supporting local model workflows through Ollama and Piper. It records speech from a microphone, converts it into text, generates a response, and plays synthesized audio. Centralized configuration and environment variables manage providers, model selections, endpoints, and API credentials. The repository is intended for voice technology research, rapid prototyping, and comparison of different processing pipelines. It requires Python 3.10 or newer and includes scripts and sample assets for running the assistant. -
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VOID
Video Object and Interaction Deletion
VOID is an advanced AI video processing system developed by Netflix that focuses on removing objects from videos while preserving the physical and visual realism of the surrounding environment. Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. One of its most notable capabilities is its ability to simulate realistic scene behavior after object removal, such as causing an object to fall naturally if its support is removed, which significantly enhances realism. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Wanwu AI Agent Platform
Enterprise AI agent platform for workflows, models, and RAG apps
Wanwu is an enterprise-grade AI agent development platform designed to help organizations build and deploy intelligent applications at scale. It provides a multi-tenant environment that enables teams to create AI agents, orchestrate workflows, and implement retrieval-augmented generation systems within a unified framework. Wanwu integrates large language models with business process automation, allowing developers to design complex, production-ready AI solutions tailored to enterprise needs. It includes comprehensive model lifecycle management capabilities, enabling users to configure, monitor, and manage different models efficiently. Wanwu also supports knowledge base construction, allowing organizations to incorporate structured and unstructured data into their AI applications. With a focus on openness and extensibility, it encourages developers to build on top of its ecosystem while maintaining a secure and compliant architecture for business use cases. -
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Watermark Anything
Official implementation of Watermark Anything with Localized Messages
Watermark Anything (WAM) is an advanced deep learning framework for embedding and detecting localized watermarks in digital images. Developed by Facebook Research, it provides a robust, flexible system that allows users to insert one or multiple watermarks within selected image regions while maintaining visual quality and recoverability. Unlike traditional watermarking methods that rely on uniform embedding, WAM supports spatially localized watermarks, enabling targeted protection of specific image regions or objects. The model is trained to balance imperceptibility, ensuring minimal visual distortion, with robustness against transformations and edits such as cropping or motion. -
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WhatsApp MCP Server
WhatsApp MCP server enabling AI access to chats and messaging
whatsapp-mcp is an open source Model Context Protocol (MCP) server that enables AI agents to interact directly with a user’s WhatsApp account through a structured interface. It acts as a bridge between WhatsApp and large language models, allowing controlled access to messages, chats, and contacts. whatsapp-mcp is composed of two main components: a Go-based bridge that connects to the WhatsApp Web API and stores data locally, and a Python-based MCP server that exposes tools for AI interaction. All message data is stored in a local SQLite database and is only accessed when explicitly requested through defined tools, giving users control over how their data is used. It supports both sending and receiving messages, including various media types such as images, audio, videos, and documents. It integrates with AI applications like Claude through MCP, enabling conversational automation and contextual message retrieval. -
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X's Recommendation Algorithm
Source code for the X Recommendation Algorithm
The Algorithm is Twitter’s open source release of the core ranking system that powers the platform’s home timeline. It provides transparency into how tweets are selected, prioritized, and surfaced to users, reflecting Twitter’s move toward openness in recommendation algorithms. The repository contains the recommendation pipeline, which incorporates signals such as engagement, relevance, and content features, and demonstrates how they combine to form ranked outputs. Written primarily in Scala, it shows the architecture of large-scale recommendation systems, including candidate sourcing, ranking, and heuristics. While certain components (such as safety layers, spam detection, or private data) are excluded, the release provides valuable insights into the design of real-world machine learning–driven ranking systems. The project is intended as a reference for researchers, developers, and the public to study, experiment with, and better understand the mechanisms behind social media content. -
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Xorbits Inference
Replace OpenAI GPT with another LLM in your app
Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy and serve your or state-of-the-art built-in models using just a single command. Whether you are a researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full potential of cutting-edge AI models. -
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Xteam
All-in-one command-line toolkit for security testing and OSINT tools
Xteam is a command-line security toolkit designed to provide multiple penetration testing and information-gathering utilities in a single interface. It combines several modules and external tools to help users perform security research tasks related to mobile devices, wireless networks, and online services. It acts as a centralized launcher that integrates scripts and third-party tools, allowing users to access different testing functions through a menu-based command line workflow. Xteam includes features such as Instagram information gathering, phishing utilities, wireless attack tools, and Android security testing capabilities. Xteam’s architecture uses a main bash script that serves as the hub for running internal modules or downloading and executing external projects when needed. It can operate on Linux systems as well as Android devices using Termux, making it accessible in both desktop and mobile environments. -
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Zendriver
A blazing fast, async-first, undetectable webscraping
Zendriver is a modern Python web automation and scraping framework that leverages the Chrome DevTools Protocol to provide fast, asynchronous control over real browser instances. Unlike traditional tools that rely on Selenium or WebDriver, Zendriver communicates directly with the browser through CDP, enabling higher performance and more precise control over browser behavior. The framework is designed to be difficult to detect by anti-bot systems, making it suitable for advanced scraping and automation use cases where stealth is important. It features an async-first architecture that allows developers to build highly concurrent workflows, improving efficiency when handling multiple tasks or large-scale scraping operations. Zendriver also includes built-in utilities for managing cookies, browser profiles, and element selection, simplifying common automation tasks. -
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any-llm
Communicate with an LLM provider using a single interface
any-llm is a unified SDK and platform developed by Mozilla AI that allows developers to interact with multiple large language model providers through a single, consistent interface. Instead of rewriting code for each provider, developers can switch between services like OpenAI, Anthropic, Mistral, and Ollama simply by changing configuration parameters. The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being tied to a specific stack. It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. The gateway exposes an OpenAI-compatible API, allowing existing tools and workflows to connect without modification. The system emphasizes developer experience with clear error handling, strong typing, and minimal configuration overhead. -
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auto-cpufreq
Automatic CPU speed & power optimizer for Linux
Automatic CPU speed & power optimizer for Linux. Actively monitors laptop battery state, CPU usage, CPU temperature, and system load, ultimately allowing you to improve battery life without making any compromises. -
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blinker-py
Blinker python library for hardware. Works with Raspberry Pi
blinker-py is a Python library for connecting hardware projects to the Blinker IoT platform. It is designed for Raspberry Pi, Banana Pi, Linux devices, and similar single-board or embedded systems. The library helps developers control hardware through the Blinker mobile app, where users can build graphical interfaces with drag-and-drop widgets. It supports common IoT communication patterns such as Wi-Fi, MQTT, WebSocket, and BLE-related platform workflows. The project is useful for makers, students, and hardware developers who want a faster way to connect sensors, switches, relays, and small automation projects to a mobile control panel. It is best suited for lightweight IoT prototyping rather than large industrial deployments. -
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book-to-skill
Turn any technical book PDF into a Claude Code skill
book-to-skill is a Claude Code skill that turns technical books and documents into reusable AI reference skills. It extracts content from PDFs and EPUBs, then organizes the material so an assistant can study, reference, and apply it while working. The project is useful for transforming dense manuals, textbooks, internal documentation, or technical guides into practical agent-accessible knowledge. It includes an extraction script and a SKILL.md workflow that guides how the resulting content should be used. The goal is not simply to summarize a book, but to make its knowledge available during problem solving and implementation. book-to-skill is best suited for developers and researchers who want AI assistants to work from specific long-form source material. -
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brython
Implementation of Python 3 running in the browser
Brython (Browser Python) is an implementation of Python 3 running in the browser, with an interface to the DOM elements and events. Brython supports the syntax of Python 3, including comprehensions, generators, metaclasses, imports, etc. and many modules of the CPython distribution. Since version 3.8.0, Brython implements the Python version of the same major/minor version number. It includes libraries to interact with DOM elements and events, and with existing Javascript libraries such as jQuery, D3, Highcharts, Raphael etc. It supports the latest specs of HTML5/CSS3, and can use CSS Frameworks like Bootstrap3, LESS, SASS etc. The most simple way to get started, without anything to install, is to use the distribution available online through jsDelivr. -
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claude-obsidian
Claude + Obsidian knowledge companion
claude-obsidian is an AI-powered knowledge engine that transforms an Obsidian vault into a self-organizing, continuously evolving wiki. Instead of acting as a simple chat assistant, it autonomously creates, links, and maintains structured knowledge based on user inputs and external sources. The system follows the LLM Wiki pattern, where information is stored as persistent markdown files that grow richer over time through cross-referencing and synthesis. It includes features such as contradiction detection, orphaned note identification, and automatic indexing. A persistent memory layer ensures continuity across sessions, eliminating the need for repeated context. It also performs autonomous research to fill knowledge gaps and expand the knowledge base. Overall, it turns note-taking into an active, compounding intelligence system. -
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fpdf2
Simple PDF generation for Python
fpdf2 is a library for simple & fast PDF document generation in Python. It is a fork and the successor of PyFPDF. Compared with other PDF libraries, fpdf2 is fast, versatile, easy to learn and to extend (example). It is also entirely written in Python and has very few dependencies: Pillow, defusedxml, & fontTools. It is a fork and the successor of PyFPDF. -
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gpt-engineer
Full stack AI software engineer
gpt-engineer is an open-source platform designed to help developers automate the software development process using natural language. The platform allows users to specify software requirements in plain language, and the AI generates and executes the corresponding code. It can also handle improvements and iterative development, giving users more control over the software they’re building. Built with a terminal-based interface, gpt-engineer is customizable, enabling developers to experiment with AI-assisted programming and refine their development process. It is especially useful for automating the coding and iterative feedback loop in software development. -
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jetson-stats
Simple package for monitoring and control your NVIDIA Jetson
jetson_stats is a Python package for monitoring and controlling NVIDIA Jetson boards. It supports Jetson platforms such as Orin, Xavier, Nano, TX, and newer Jetson families. The project includes jtop, a terminal-based dashboard that gives users a live view of CPU, GPU, memory, power, temperature, engine usage, and system status. It can also be imported into Python scripts, which makes it useful for custom monitoring, robotics dashboards, automation, and diagnostics. Developers working with embedded AI systems can use it to understand performance limits and troubleshoot hardware behavior during deployment. Its main value is giving Jetson users a practical, readable, and scriptable view of board health and resource usage.
