Open Source Python Software - Page 7
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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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PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
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Tribler
Privacy enhanced BitTorrent client with P2P content discovery
Tribler is a decentralized, privacy-enhanced BitTorrent client developed by researchers at Delft University of Technology. It introduces built-in anonymity using a Tor-like onion routing network and integrates its own blockchain for economic incentives and trust management. Tribler supports standard torrenting features along with distributed search, self-contained channels, and peer reputation. Its goal is to provide a fully autonomous file-sharing network without relying on external servers, search engines, or trackers. -
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YOLOv3
Object detection architectures and models pretrained on the COCO data
Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an expert. Students love YOLOv5 for its simplicity and there are many quickstart examples for you to get started within seconds. Export and deploy your YOLOv5 model with just 1 line of code. There are also loads of quickstart guides and tutorials available to get your model where it needs to be. Create state of the art deep learning models with YOLOv5 -
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Kivy
Innovative user interfaces made easy
Kivy is an open source, cross-platform UI framework that lets you develop applications that make use of innovative, multi-touch user interfaces. Written in Python with a graphics engine built over OpenGL ES 2, Kivy supports various input devices and protocols, and gives you access to over 20 widgets that are all highly extensible and have built-in multi-touch support. You can run the same codebase on Mac, Windows, Linux, Android and iOS. Kivy is 100% free and open source with a professionally developed and used toolkit, as well as a stable framework and well-documented API, so you can be confident in using it in a commercial product. -
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Volatility
An advanced memory forensics framework
Volatility is a widely used open-source framework for analyzing memory captures (RAM dumps) from Windows, Linux, and macOS systems. It enables investigators and malware analysts to extract process lists, network connections, DLLs, strings, artifacts, and more. Volatility supports many plugins for detecting hidden processes, malware, rootkits, and event tracing. It’s essential in digital forensics and incident response workflows. -
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motionEyeOS
A video surveillance OS for single-board computers
motionEyeOS is a Linux distribution that turns a single-board computer into a video surveillance system. The OS is based on BuildRoot and uses motion as a backend and motionEye for the frontend. Compatible with most USB cameras as well as with the Raspberry PI camera module. Motion detection with email notifications and working schedule. JPEG files for still images, AVI files for videos. Connects to your local network using ethernet or wifi. File storage on SD card, USB drive or network SMB share. Uploading of media files to cloud storage services (Google Drive, Dropbox), media files are visible in the local network as SMB shares. Media files can also be accessed through the built-in FTP server or SFTP server. -
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FastAPI
FastAPI framework, high performance, easy to learn, fast to code
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. 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. Fewer bugs. Get production-ready code. With automatic interactive documentation. Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. If you are building a CLI app to be used in the terminal instead of a web API, check out Typer. Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. In summary, you declare once the types of parameters, body, etc. as function parameters. You do that with standard modern Python types. You don't have to learn a new syntax, the methods or classes of a specific library, etc. -
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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. -
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Bottles
Run Windows software and games on Linux
Bottles lets you run Windows software on Linux, such as applications and games. It introduces a workflow that helps you organize by categorizing each software to your liking. Bottles provide several tools and integrations to help you manage and optimize your applications. Bottles introduces a new way to handle Windows prefixes using environments, a combination of ready-to-use settings, libraries and dependencies. -
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GPT-SoVITS
1 min voice data can also be used to train a good TTS model
GPT‑SoVITS is a state-of-the-art voice conversion and TTS system that enables zero‑shot and few‑shot synthesis based on a short vocal sample (e.g., 5 seconds). It supports cross‑lingual speech synthesis across English, Chinese, Japanese, Korean, Cantonese, and more. It's powered by VITS architecture enhanced for few‑sample adaptation and real‑time usability. -
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guiscrcpy
Full fledged GUI integration for the Android screen mirroring system
A simple, pluggable, graphical user interface for the fastest Android screen mirroring software, scrcpy. guiscrcpy is a multiplatform, ready-to-use GUI layer for Android to PC screen mirroring written in the advancing programming language python3 for the most award-winning open-source android screen mirroring system. -
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Audio toolkit for streaming, aiming at complex Internet radio systems. Our stream generator is highly extensible and flexible. Script based, it can be a fully automatic daemon streamer, but is also used for live shows with an user-friendly GUI.
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Demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The repository includes pretrained models for common tasks such as isolating vocals, drums, bass, and accompaniment from stereo music, achieving state-of-the-art results in benchmarks like MUSDB18. Demucs supports GPU-accelerated inference and can process multi-channel audio with chunked streaming for real-time or batch operation. It also provides training scripts and utilities to fine-tune on custom datasets, along with remixing and enhancement tools. -
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TikTok-ViewBot
ViewBot using requests updated 2025
TikTok-ViewBot explores automated interactions with TikTok’s viewing mechanisms for research and educational purposes. The code demonstrates how scripted traffic might be generated and measured, highlighting the kinds of heuristics a platform could use to validate or discount views. It is often used to study rate limits, signature schemes, request patterns, and the fragility of naïve automation. Because it touches on automation against a third-party service, responsible use and adherence to platform terms are emphasized; using such tools to manipulate metrics or violate policies is unethical and can be unlawful. From a security research perspective, understanding these patterns helps both defenders and platform engineers improve abuse detection. For developers, the repo also serves as a cautionary example of how brittle unofficial integrations can be and why resilient, compliant APIs matter. -
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Salix is a linux distribution based on Slackware that is simple and easy to use. Salix aims to be completely backwards compatible with Slackware, so Slackware users can benefit from Salix repositories.
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. The repository includes inference and training scripts, a model zoo with different pretrained models (including general and anime-oriented variants), and support for batch and arbitrary scaling, making it adaptable for diverse enhancement tasks. It emphasizes usability with utilities that handle alpha channels, gray/16-bit images, and tiled inference for large inputs, and can be run via Python scripts or portable executables. -
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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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CDemu - a virtual CD/DVD drive for Linux. Project includes Linux kernel module & userspace utilities.
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. Place widgets on the canvas, connect them, load your datasets and harvest the insight! When teaching data mining, we like to illustrate rather than only explain. -
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Pillow
The friendly Python Imaging Library fork
If you've ever wondered or worried about the future of Python's Imaging Library, it's time to stop. Pillow is here to answer your concerns, and offer you more. Pillow is the friendly fork of the Python Imaging Library or PIL, a library that adds image processing capabilities to your Python interpreter. Why turn to Pillow? Aside from offering extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities, Pillow is setuptools compatible. While PIL is not officially over yet, with Pillow you can be assured of continuous integration testing, publicized development activity, and regular releases to the Python Package Index. -
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lxml
The lxml XML toolkit for Python
A Python library for efficient XML and HTML processing, known for speed and compatibility. The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all CPython versions from 3.6 to 3.12. See the introduction for more information about the background and goals of the lxml project. -
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FLUX.2
Official inference repo for FLUX.2 models
FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved. It supports high-resolution output (up to ~4 megapixels), which allows for photography-quality images, detailed product shots, infographics or UI mockups rather than just low-resolution drafts. FLUX.2 is built with a modern architecture (a flow-matching transformer + a revamped VAE + a strong vision-language encoder), enabling strong prompt adherence, correct rendering of text/typography in images, reliable lighting, layout, and physical realism, and consistent style/character/product identity across multiple generations or edits. -
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EasyABC
EasyABC is an open source ABC editor
EasyABC allows the user to create, edit, view, play, convert music written in the ABC music notation language. The program was originally written in Python 2.7 and WxPython by Nils Liberg and runs on Windows, OSX, and Linux. Jan Wybren de Jong has converted to run on Python 3.8 or higher. Frédéric Aupépin has been supporting EasyABC on OSX. EasyABC depends upon other external programs like abc2midi, abcm2ps, fluidsynth. If you install the Windows or Mac executables most of these programs are automatically included. -
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YOLOv5
YOLOv5 is the world's most loved vision AI
Introducing Ultralytics YOLOv8, the latest version of the acclaimed real-time object detection and image segmentation model. YOLOv8 is built on cutting-edge advancements in deep learning and computer vision, offering unparalleled performance in terms of speed and accuracy. Its streamlined design makes it suitable for various applications and easily adaptable to different hardware platforms, from edge devices to cloud APIs. Explore the YOLOv8 Docs, a comprehensive resource designed to help you understand and utilize its features and capabilities. Whether you are a seasoned machine learning practitioner or new to the field, this hub aims to maximize YOLOv8's potential in your projects. -
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WSA-Script
Integrate Magisk root and Google Apps into WSA
WSA-Script is a community-driven automation and scripting toolkit that helps Windows users extend the Windows Subsystem for Android (WSA) by integrating optional features like Magisk (for root access) and Google Apps into the otherwise vanilla WSA environment, leveraging GitHub Actions and scripted installers to do much of the heavy lifting. The project provides a way to download and unpack custom builds of the WSA package that bundle these enhancements and guide users through installation using automated batch and PowerShell scripts so that Android apps requiring Google Play Services or root can run in WSA on Windows 10 or 11. Because Microsoft’s default WSA lacks these extended capabilities, WSA-Script fills a niche for enthusiasts who need a more flexible Android experience on desktop Windows, managing downloads, registrations, and configuration steps in a repeatable workflow.
