Open Source Python Software for ChromeOS
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Python Software for ChromeOS
Browse free open source Python Software for ChromeOS and projects below. Use the toggles on the left to filter open source Python Software for ChromeOS by OS, license, language, programming language, and project status.
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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GeographicLib
Geographic library
GeographicLib is a small C++ library for: geodesic and rhumb line calculations; conversions between geographic, UTM, UPS, MGRS, geocentric, and local cartesian coordinates; gravity (e.g., EGM2008) and geomagnetic field (e.g., WMM2020) calculations. -
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Little cms color engine
An ICC-based CMM for color management
Little cms is a color management library. Implements fast transforms between ICC profiles. It is focused on speed, and is portable across several platforms (MIT license) -
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SCons
A software construction tool
SCons is a software construction tool that is a superior alternative to the classic "Make" build tool that we all know and love. SCons is implemented as a Python script and set of modules, and SCons "configuration files" are actually executed as Python scripts. This gives SCons many powerful capabilities not found in other software build tools. We make SCons available in three distinct packages, for different purposes. - The scons package is the basic package to install SCons. You don't need any other package if you just want to try out SCons. - The scons-local package executes as a SCons standalone, out of a local directory. It's intended to be dropped in to and shipped with packages of other software for builds with SCons but not as a required install. - The scons-src package is the complete source tree, including everything we use to package SCons and all of the regression tests. -
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Pandas TA
Python 3 Pandas Extension with 130+ Indicators
Technical Analysis Indicators - Pandas TA is an easy-to-use Python 3 Pandas Extension with 130+ Indicators. Pandas Technical Analysis (Pandas TA) is an easy-to-use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns. Many commonly used indicators are included, such as: Candle Pattern(cdl_pattern), Simple Moving Average (sma) Moving Average Convergence Divergence (macd), Hull Exponential Moving Average (hma), Bollinger Bands (bbands), On-Balance Volume (obv), Aroon & Aroon Oscillator (aroon), Squeeze (squeeze) and many more. -
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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A cross-platform, open-source, alternative to NIST REFPROP. Based on reference-accuracy equations of state and transport property correlations for refrigerants like Water, CO2, R134a, Nitrogen, Argon, Ammonia, Air, R404a, R410a, Propane and many others. A selection of secondary working fluid properties are also available. Can also make use of REFPROP when available. In addition, calculations for Humid Air Properties based on ASHRAE RP-1485 are provided. Wrappers are available for MATLAB, Octave, Python, C#, Fortran and many more.
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely integrates large-scale reinforcement learning (RL) without relying on supervised fine-tuning, enabling the model to develop advanced reasoning capabilities. This approach has resulted in performance comparable to leading models like OpenAI's o1, while maintaining cost-efficiency. To further support the research community, DeepSeek has released distilled versions of the model based on architectures such as LLaMA and Qwen. -
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GPT4All
Run Local LLMs on Any Device. Open-source
GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This project also supports Python integrations for easy automation and customization. GPT4All is ideal for individuals and businesses seeking private, offline access to powerful LLMs. -
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kokoro-onnx
TTS with kokoro and onnx runtime
kokoro-onnx is a text-to-speech toolkit that wraps the Kokoro neural TTS model in an easy-to-use ONNX Runtime interface, so you can generate speech from Python with minimal setup. It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. It supports multiple languages and voices, with a curated voice list and configuration via a VOICES file hosted alongside the models. The package is distributed on PyPI, meaning you can integrate it directly into applications or scripts using standard Python tooling. It also recommends pairing with an external G2P package to improve pronunciation quality, especially for more complex languages or names, and is licensed under permissive MIT and Apache-style licenses. -
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DeepSeek-V3
Powerful AI language model (MoE) optimized for efficiency/performance
DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3 underwent supervised fine-tuning and reinforcement learning to fully realize its capabilities. Evaluations indicate that it outperforms other open-source models and rivals leading closed-source models, achieving this with a training duration of 55 days on 2,048 Nvidia H800 GPUs, costing approximately $5.58 million. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Bunkr Downloader
Yet bunkrr album downloader
Bunkr Downloader is a command-line media downloader designed specifically for retrieving and managing albums from the Bunkr platform. It is implemented in Python and focuses on providing a structured workflow for downloading, organizing, and synchronizing media collections. The tool allows users to input album URLs and automatically download all associated media while maintaining a local metadata database for tracking content. It includes features for managing albums as a persistent library, enabling users to add, remove, or sync albums over time without re-downloading existing files. bonkrr also categorizes downloaded content into different media types such as images, videos, and archives, improving organization and usability. The use of SQLite for local storage ensures efficient tracking of downloads and metadata synchronization. Overall, bonkrr is a practical utility for users who want to maintain organized offline collections of media from online album sources. -
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch. Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries, resource loaders, utilities for texture and buffer handling, and integration points for native event loops and input systems. The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. While being low-level, it also provides sensible defaults and helper abstractions that reduce boilerplate and help teams maintain clear, maintainable code. -
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Coomer Downloader App
Coomer downloader
CoomerDL is an open-source command-line tool designed to download and archive content from websites supported by the Coomer platform, which aggregates publicly available content from various creators. The tool enables users to automate the retrieval of media such as images, videos, and metadata associated with creator profiles. It is built to handle large volumes of content efficiently, allowing users to download entire collections or selectively retrieve specific posts. The application typically supports features such as authentication, rate limiting, and retry mechanisms to ensure reliable downloads even when dealing with unstable connections or restricted endpoints. It is often used for personal archiving, data collection, or offline access to content that may otherwise be difficult to manage manually. The tool operates through a command-line interface, making it suitable for scripting and integration into automated workflows. -
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Dispatcharr
Your Ultimate IPTV & Stream Management Companion
Dispatcharr is a self-hosted IPTV and streaming management platform built for people who want full control over their playlists, streams, and program guide (EPG) data. It lets you import M3U/EPG sources, curate and organize them with filtering and grouping, and serve them reliably to clients like Plex, Jellyfin, and Emby with advanced proxying and failover support. Designed with both simple personal use and larger self-hosted setups in mind, Dispatcharr offers real-time streaming statistics, automated EPG matching, and a responsive interface that helps you manage your video on demand (VOD) content alongside live channels. The project has evolved from a personal tool to a collaborative open-source effort with beta-phase features including a dashboard, flexible proxy engine, and compatibility with multiple output formats. With extensible plugin support and frequent contributions, Dispatcharr aims to unify and simplify IPTV workflows while staying entirely self-hosted. -
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WhatsApp Beacon
OSINT tool for tracking WhatsApp online status via Web automation
WhatsApp Beacon is an open source OSINT tool designed to monitor and analyze the online activity status of WhatsApp users through WhatsApp Web. It uses Selenium automation to interact with the web interface and detect when a target account goes online or offline. By continuously monitoring these changes, WhatsApp Beacon records connectivity patterns and builds a historical dataset of activity sessions. The collected information is stored in logs and a local database, allowing users to review behavioral patterns over time. In addition, the project supports exporting collected data to spreadsheet formats for further analysis or reporting. WhatsApp Beacon is designed to run across multiple operating systems and can operate in the background using headless browser automation. It is intended for educational and research purposes related to open-source intelligence (OSINT) and digital investigation. -
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DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN training — and produces more realistic, expressive, and natural-sounding singing. The method introduces a “shallow diffusion” mechanism: instead of diffusing over many steps, generation begins at a shallow step determined adaptively, which leverages prior knowledge learned by a simple mel-spectrogram decoder and speeds up inference. -
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fsociety
Modular CLI framework for managing penetration testing tools
fsociety is a modular penetration testing framework designed to provide a unified interface for running and managing a wide range of security tools. It focuses on simplifying penetration testing workflows by integrating multiple external security utilities into a single command line environment. Instead of implementing its own security scanners, the framework acts as a wrapper and orchestrator that helps users discover, install, and execute tools from various GitHub repositories. Its modular architecture organizes tools into categories such as information gathering, networking, web application security, and password testing. This structure allows users to quickly navigate through different security tasks while maintaining a consistent interface. fsociety can automatically clone and manage required tools, reducing the manual effort typically needed to set up a penetration testing toolkit. fsociety is distributed as a Python package. -
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malware-samples
A collection of malware samples and relevant dissection information
This repo is a public collection of malware samples and related dissection/analysis information, maintained by InQuest. It gathers various kinds of malicious artifacts, executables, scripts, macros, obfuscated documents, etc., with metadata (e.g., VirusTotal reports), file carriers, and sample hashes. It’s intended for malware analysts/researchers to help study how malware works, how they are delivered, and how it evolves. -
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Claude Code SDK Python
Python SDK for Claude Agent
claude-code-sdk-python is the Python SDK for Claude Code, Anthropic’s agentic coding system. It provides abstractions to easily query Claude Code (with streaming support) and conduct interactive sessions. The SDK includes core client classes, asynchronous query functions, and support for custom tools and hooks within Claude sessions. It is designed to integrate with local Python workflows and allow developers to embed Claude Code capabilities directly in their applications or scripts. The repo is MIT-licensed and includes documentation and installation instructions (requires Python 3.10+, Node installation of Claude Code). Example usage shows how to stream responses, parse structured message blocks, or create persistent client sessions. -
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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Stable Diffusion
High-Resolution Image Synthesis with Latent Diffusion Models
Stable Diffusion Version 2. The Stable Diffusion project, developed by Stability AI, is a cutting-edge image synthesis model that utilizes latent diffusion techniques for high-resolution image generation. It offers an advanced method of generating images based on text input, making it highly flexible for various creative applications. The repository contains pretrained models, various checkpoints, and tools to facilitate image generation tasks, such as fine-tuning and modifying the models. Stability AI's approach to image synthesis has contributed to creating detailed, scalable images while maintaining efficiency. -
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Retrogaming BIOS
Complete BIOS & firmware collection for retrogaming emulators
Retrogaming BIOS is a repository that provides a structured and curated collection of BIOS files required for running retro gaming emulators across multiple platforms. It is designed to simplify the often confusing process of obtaining and organizing BIOS files by presenting them in a consistent and ready-to-use format. The project focuses on compatibility with popular emulation environments, ensuring that the included BIOS files meet the requirements for various classic consoles and arcade systems. It also emphasizes organization, grouping BIOS files by system and providing a layout that can be easily integrated into emulator directories. By consolidating these essential files into a single resource, retrobios helps reduce setup errors and improves the reliability of emulation systems. The repository is particularly useful for users building retro gaming setups or emulation stations who want a streamlined configuration process. -
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Stable Diffusion
A latent text-to-image diffusion model
Stable Diffusion is a widely used open-source latent text-to-image diffusion model developed by the CompVis group for generating high-quality images from natural language prompts. The model operates by conditioning a diffusion process on text embeddings produced by a CLIP text encoder, enabling detailed and controllable image synthesis. It was trained on large-scale image datasets and later fine-tuned to produce 512×512 images with strong visual fidelity. Because the system runs efficiently on consumer hardware compared to earlier generative models, it helped popularize local AI image generation workflows. The repository includes reference scripts and model configurations that allow researchers and developers to reproduce, modify, or extend the architecture. Overall, stable-diffusion has become a foundational tool in the generative AI ecosystem for art creation, research, and multimodal experimentation. -
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Python
The Python programming language
Python is a powerful, high-level programming language known for its readability, simplicity, and versatility. It supports multiple programming paradigms including procedural, object-oriented, and functional styles. CPython, the reference implementation, is developed and maintained by the Python Software Foundation and the global open-source community. The language includes a vast standard library that accelerates development by providing built-in modules for file handling, networking, data manipulation, and more. Python runs seamlessly across platforms such as Linux, macOS, and Windows, making it ideal for both development and production environments. With constant updates, optimizations, and an active community, Python continues to be one of the most widely adopted languages worldwide. -
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Stand-alone application and Python tools for interactive and/or batch processing analysis of X-Ray Fluorescence Spectra. Graphical user interface (GUI) and batch processing capabilities provided.
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HanimeTV
Streaming application designed to provide a mobile-friendly interface
HanimeTV is an open-source streaming application designed to provide a mobile-friendly interface for browsing and consuming video content from external streaming sources. The app focuses on delivering a smooth playback experience by integrating video streaming, search functionality, and content categorization into a single interface. It is typically built with a modern Android-based architecture, allowing efficient handling of media playback and user interaction. The application includes features for browsing content libraries, filtering by categories, and accessing detailed metadata for each item. It emphasizes usability and performance, ensuring that users can navigate and stream content with minimal latency. The project is maintained as an open-source initiative, allowing developers to inspect, modify, and improve its functionality.
